Ändra sökning
Avgränsa sökresultatet
1234567 1 - 50 av 1164
RefereraExporteraLänk till träfflistan
Permanent länk
Referera
Referensformat
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Annat format
Fler format
Språk
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Annat språk
Fler språk
Utmatningsformat
  • html
  • text
  • asciidoc
  • rtf
Träffar per sida
  • 5
  • 10
  • 20
  • 50
  • 100
  • 250
Sortering
  • Standard (Relevans)
  • Författare A-Ö
  • Författare Ö-A
  • Titel A-Ö
  • Titel Ö-A
  • Publikationstyp A-Ö
  • Publikationstyp Ö-A
  • Äldst först
  • Nyast först
  • Skapad (Äldst först)
  • Skapad (Nyast först)
  • Senast uppdaterad (Äldst först)
  • Senast uppdaterad (Nyast först)
  • Disputationsdatum (tidigaste först)
  • Disputationsdatum (senaste först)
  • Standard (Relevans)
  • Författare A-Ö
  • Författare Ö-A
  • Titel A-Ö
  • Titel Ö-A
  • Publikationstyp A-Ö
  • Publikationstyp Ö-A
  • Äldst först
  • Nyast först
  • Skapad (Äldst först)
  • Skapad (Nyast först)
  • Senast uppdaterad (Äldst först)
  • Senast uppdaterad (Nyast först)
  • Disputationsdatum (tidigaste först)
  • Disputationsdatum (senaste först)
Markera
Maxantalet träffar du kan exportera från sökgränssnittet är 250. Vid större uttag använd dig av utsökningar.
  • 1.
    Chi, Zhexiang
    et al.
    Department of Industrial Engineering, Tsinghua University, Beijing, China.
    Lin, Jing
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Chen, Ruoran
    Department of Industrial Engineering, Tsinghua University, Beijing, China.
    Huang, Simin
    Department of Industrial Engineering, Tsinghua University, Beijing, China.
    Data-driven approach to study the polygonization of high-speed railway train wheel-sets using field data of China’s HSR train2020Ingår i: Measurement, ISSN 0263-2241, E-ISSN 1873-412X, Vol. 149, artikel-id 107022Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Environmental factors, like seasonality, have been proved to exert significant impact on reliability of China high-speed rail train wheels in this article. Most studies on polygonization of train wheels are based on physical models, mathematical models or simulation systems. Normally, characteristics and mechanisms of wheel polygonization are studied under ideal conditions without considering the impact of the environment. However, in practical use, there are many irregular wear wheels and irregular wear cannot be explained by theoretical models with assumptions of ideal conditions. We look at two possible factors in polygonization: seasonality and proximity to engines. Our analysis of field data shows the environmental factor has more impact on wheel polygonization than the mechanical factor. Based on the Bayesian models, the mean time to failure of the wheels under different operation conditions is conducted. A case study of China’s HSR train wheels is conducted to confirm the finding. The case study shows the degree of polygonal wear is much more severe in summer than other seasons. The finding may give a totally new research perspective on polygonization of train wheels. We use Bayesian analysis because this method is useful for small and incomplete data sets. We propose three Bayesian data-driven models.

  • 2.
    Liu, B.
    et al.
    Department of Management Science, University of Strathclyde, Glasgow, United Kingdom.
    Lin, Jing
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Zhang, Liangwei
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik. Department of Industrial Engineering, Dongguan University of Technology, Dongguan, China.
    Kumar, Uday
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    A Dynamic Prescriptive Maintenance Model Considering System Aging and Degradation2019Ingår i: IEEE Access, E-ISSN 2169-3536, Vol. 7, s. 94941-94943, artikel-id 8762155Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper develops a dynamic maintenance strategy for a system subject to aging and degradation. The influence of degradation level and aging on system failure rate is modeled in an additive way. Based on the observed degradation level at the inspection, repair or replacement is carried out upon the system. Previous researches assume that repair will always lead to an improvement in the health condition of the system. However, in our study, repair reduces the system age but on the other hand, increases the degradation level. Considering the two-fold influence of maintenance actions, we perform reliability analysis on system reliability as a first step. The evolution of system reliability serves as a foundation for establishing the maintenance model. The optimal maintenance strategy is achieved by minimizing the long-run cost rate in terms of the repair cycle. At each inspection, the parameters of the degradation processes are updated with maximum a posteriori estimation when a new observation arrives. The effectiveness of the proposed model is illustrated through a case study of locomotive wheel-sets. The maintenance model considers the influence of degradation and aging on system failure and dynamically determines the optimal inspection time, which is more flexible than traditional stationary maintenance strategies and can provide better performance in the field.

  • 3.
    Bektas, Oguz
    et al.
    Warwick Manufacturing Group, University of Warwick, Coventry, UK.
    Jones, Jeffrey A.
    Warwick Manufacturing Group, University of Warwick, Coventry, UK.
    Sankararaman, Shankar
    Data Science and Analytics Manager,Pricewaterhouse Cooper, San Jose, USA.
    Roychoudhury, Indranil
    Stinger Ghaffarian Technologies, Inc.NASA Ames Research Center, Moffett Field, USA.
    Goebel, Kai
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik. NASA Ames Research Center, Moffett Field, USA.
    A neural network filtering approach for similarity-based remaining useful life estimation2019Ingår i: The International Journal of Advanced Manufacturing Technology, ISSN 0268-3768, E-ISSN 1433-3015, Vol. 101, nr 1-4, s. 87-103Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The role of prognostics and health management is ever more prevalent with advanced techniques of estimation methods. However, data processing and remaining useful life prediction algorithms are often very different. Some difficulties in accurate prediction can be tackled by redefining raw data parameters into more meaningful and comprehensive health level indicators that will then provide performance information. Proper data processing has a significant importance on remaining useful life predictions, for example, to deal with data limitations or/and multi-regime operating conditions. The framework proposed in this paper considers a similarity-based prognostic algorithm that is fed by the use of data normalisation and filtering methods for operational trajectories of complex systems. This is combined with a data-driven prognostic technique based on feed-forward neural networks with multi-regime normalisation. In particular, the paper takes a close look at how pre-processing methods affect algorithm performance. The work presented herein shows a conceptual prognostic framework that overcomes challenges presented by short-term test datasets and that increases the prediction performance with regards to prognostic metrics.

  • 4.
    Bektas, Oguz
    et al.
    Warwick Manufacturing Group, University of Warwick, Coventry, United Kingdom.
    Jones, Jeffrey A.
    Warwick Manufacturing Group, University of Warwick, Coventry, United Kingdom.
    Sankararaman, Shankar
    Pricewaterhouse Cooper, San Jose, CA, United States.
    Roychoudhury, Indranil
    Stinger Ghaffarian Technologies, Inc., NASA Ames Research Center, Moffett Field, CA, United States.
    Goebel, Kai
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik. NASA Ames Research Center, Moffett Field, CA, United States.
    A neural network framework for similarity-based prognostics2019Ingår i: MethodsX, ISSN 1258-780X, E-ISSN 2215-0161, Vol. 6, s. 383-390Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Prognostic performance is associated with accurately estimating remaining useful life. Difficulty in accurate prognostic applications can be tackled by processing raw sensor readings into more meaningful and comprehensive health condition indicators that will then provide performance information for remaining useful life estimations. To that end, typically, multiple tasks on data pre-processing and predictions have to be carried out such that tasks can be assessed using different methodological aspects. However, incompatible methods may result in poor performance and consequently lead to undesirable error rates.

    The present research evaluates data training and prediction stages. A data-driven prognostic method based on a feed-forward neural network framework is first defined to calculate the performance of a complex system. Then, the health indicators are used in a similarity based remaining useful life estimation method. This framework presents a conceptual prognostic protocol that overcomes challenges presented by multi-regime condition monitoring data.

  • 5.
    Illankoon, Prasanna
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Tretten, Phillip
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Kumar, Uday
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    A prospective study of maintenance deviations using HFACS-ME2019Ingår i: International Journal of Industrial Ergonomics, ISSN 0169-8141, E-ISSN 1872-8219, Vol. 74, artikel-id 102852Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The factors initiating aviation accidents are usually hidden behind various steps, systems, and tasks, and systematic root-cause analysis is required to uncover the initial factor(s). To reduce the risk of unfavourable events, it is more appropriate to study their causal factors. We argue that an in-depth study on maintenance process deviations could assist in uncovering hidden causal factors. We therefore analyse reported maintenance deviations from an aviation organisation using the Human Factor Analysis and Classification System-Maintenance Extension (HFACS-ME) taxonomy to aggregate and map hidden causal factors. We find attention and memory errors and inadequacy of processes and documentation are major causal factors. We argue a well-run organisation can capture hidden causal factors and reduce the risk of incidents and accidents. More specifically, we show how situation awareness (SA) interventions can assist in the mitigation of maintenance deviations and capture hidden causal factors.

  • 6.
    Khajehei, Hamid
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Ahmadi, Alireza
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Soleimanmeigouni, Iman
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Nissen, Arne
    Trafikverket, Luleå, Sweden.
    Allocation of effective maintenance limit for railway track geometry2019Ingår i: Structure and Infrastructure Engineering, ISSN 1573-2479, E-ISSN 1744-8980Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The objective of this study has been to develop an approach to the allocation of an effective maintenancelimit for track geometry maintenance that leads to a minimisation of the total annual maintenancecost. A cost model was developed by considering the cost associated with inspection, preventivemaintenance, normal corrective maintenance and emergency corrective maintenance. The standarddeviation and extreme values of isolated defects of the longitudinal level were used as quality indicatorsfor preventive and corrective maintenance activities. The Monte Carlo technique was used tosimulate the track geometry behaviour under different maintenance limit scenarios and the effectivelimit was determined which minimises the total maintenance cost. The applicability of the model wastested in a case study on the Main Western Line in Sweden. Finally, a sensitivity analysis was carriedout on the inspection intervals, the emergency corrective maintenance cost and the maintenanceresponse time. The results show that there is an optimal region for selecting an effective limit.However, by considering the safety aspects in track geometry maintenance planning, it is suggestedthat the lower bound of the optimal region should be selected.

  • 7.
    Chen, Jiayu
    et al.
    Beihang University, Beijing, China.
    Zhou, Dong
    Beihang University, Beijing, China.
    Guo, Ziyue
    Beihang University, Beijing, China.
    Lin, Jing
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    LYU, Chuan
    Beihang University, Beijing, China.
    LU, Chen
    Beihang University, Beijing, China.
    An Active Learning Method Based on Uncertainty and Complexity for Gearbox Fault Diagnosis2019Ingår i: IEEE Access, E-ISSN 2169-3536, Vol. 7, s. 9022-9031Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    It is crucial to implement an effective and accurate fault diagnosis of a gearbox for mechanical systems. However, being composed of many mechanical parts, a gearbox has a variety of failure modes resulting in the difficulty of accurate fault diagnosis. Moreover, it is easy to obtain raw vibration signals from real gearbox applications, but it requires significant costs to label them, especially for multi-fault modes. These issues challenge the traditional supervised learning methods of fault diagnosis. To solve these problems, we develop an active learning strategy based on uncertainty and complexity. Therefore, a new diagnostic method for a gearbox is proposed based on the present active learning, empirical mode decomposition-singular value decomposition (EMD-SVD) and random forests (RF). First, the EMD-SVD is used to obtain feature vectors from raw signals. Second, the proposed active learning scheme selects the most valuable unlabeled samples, which are then labeled and added to the training data set. Finally, the RF, trained by the new training data, is employed to recognize the fault modes of a gearbox. Two cases are studied based on experimental gearbox fault diagnostic data, and a supervised learning method, as well as other active learning methods, are compared. The results show that the proposed method outperforms the two common types of methods, thus validating its effectiveness and superiority.

  • 8.
    An, Bolun
    et al.
    School of Civil Engineering, Beijing Jiaotong University, Beijing, China. Beijing Key Laboratory of Track Engineering, Beijing, China. Beijing Engineering Research Centre of Rail Traffic Line Safety and Disaster, Beijing, China.
    Gao, Liang
    School of Civil Engineering, Beijing Jiaotong University, Beijing, China. Beijing Key Laboratory of Track Engineering, Beijing , China. Beijing Engineering Research Centre of Rail Traffic Line Safety and Disaster, Beijing, China.
    Xin, Tao
    School of Civil Engineering, Beijing Jiaotong University, Beijing, China. Beijing Key Laboratory of Track Engineering, Beijing, China. Beijing Engineering Research Centre of Rail Traffic Line Safety and Disaster, Beijing, China.
    Lin, Jing
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    An approach to evaluate wheel-rail match properties considering the flexibility of ballastless track: Comparison of rigid and flexible track models in wheel-rail profile matching2019Ingår i: International Journal of COMADEM, ISSN 1363-7681, Vol. 22, nr 3, s. 5-13Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Many different wheel/rail profiles are used in the China high-speed railway, and vehicle operation safety and comfort will decrease if the inappropriate wheel-rail profile pair is used. To solve the problem of estimating the wheel-rail match, many numerical models, including vehicle system dynamic models and wheel-rail rolling contact models, have been established to analyse the wheel-rail dynamic responses. Both methods have less consideration of the flexibility and vibration characteristics of ballastless track, leading to deviations in the calculation of middle and high frequency vibration. This paper proposes a vehicle-flexible track coupling model and compares it with the vehicle dynamic model (vehicle-rigid track model). In the rigid track model, only the track irregularities are considered in the track module; the vibrations and deformations of rails, track slab and the foundation are considered in the flexible track model. Taking Chinese CRH3 series wheel profile S1002CN and rail profile CHN60 as examples and considering different track excitations, the two models are compared. The wheel-rail interaction forces, wheel-rail wear depths, wear volumes and vehicle accelerations are chosen as analysis indices for the comparative study.

    The results show that the wheel-rail forces of the flexible track model are larger than the rigid track model in the frequency range from 70 to 120Hz, while they decrease obviously in the frequency range above 150Hz. The differences in wear depths and volumes between the two models exceed 10%. Therefore, the flexible track model should be considered when studying the match properties of different wheel-rail pairs.

  • 9.
    Cai, Baoping
    et al.
    China University of Petroleum, Qingdao, Shandong, China.
    Kong, Xiangdi
    China University of Petroleum, Qingdao, Shandong, China.
    Liu, Yonghong
    China University of Petroleum, Qingdao, Shandong, China.
    Lin, Jing
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik. China University of Petroleum, Qingdao, Shandong, China.
    Yuan, Xiaobing
    China University of Petroleum, Qingdao, Shandong, China.
    Xu, Hongqi
    Rongsheng Machinery Manufacture Ltd. of Huabei Oilfield, Hebei, Renqiu, China.
    Ji, Renjie
    China University of Petroleum, Qingdao, Shandong, China.
    Application of Bayesian Networks in Reliability Evaluation2019Ingår i: IEEE Transactions on Industrial Informatics, ISSN 1551-3203, E-ISSN 1941-0050, Vol. 15, nr 4, s. 2146-2157Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The Bayesian network (BN) is a powerful model for probabilistic knowledge representation and inference and is increasingly used in the field of reliability evaluation. This paper presents a bibliographic review of BNs that have been proposed for reliability evaluation in the last decades. Studies are classified from the perspective of the objects of reliability evaluation, i.e., hardware, structures, software, and humans. For each classification, the construction and validation of a BN-based reliability model are emphasized. The general procedural steps for BN-based reliability evaluation, including BN structure modeling, BN parameter modeling, BN inference, and model verification and validation, are investigated. Current gaps and challenges in reliability evaluation with BNs are explored, and a few upcoming research directions that are of interest to reliability researchers are identified.

  • 10.
    Stenström, Christer
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Söderholm, Peter
    Luleå tekniska universitet, Institutionen för ekonomi, teknik och samhälle, Industriell Ekonomi.
    Applying Eurostat’s ESS handbook for quality reports on railway maintenance data2019Ingår i: Proceedings of the International Heavy Haul Association STS Conference (IHHA 2019), 2019, s. 473-480Konferensbidrag (Refereegranskat)
    Abstract [en]

    The importance of data quality has become more evident with the digitalization trend and development of new asset management frameworks. Digitalization has changed maintenance work by an increasing share of condition monitoring and digitalized work order processes, which for rail infrastructure and rolling stock give rise to data sets qualifying as big data. Asset management in turn, has progressed significantly the last decades as a response to digitalization, as well as due to a changing organisational culture. ISO 55000, perhaps the best known asset management guidelines, has been adapted to railways by UIC (International Union of Railways), and the EU-projects In2Rail and In2Smart. However, the quality of the data collected has become a growing concern that has not been adequately addressed in asset management. In this study, Eurostat’s ESS (European Statistical System) handbook for quality reports has been adapted and applied to railway maintenance data. The results include a case study on data quality reporting and performance indicator specification. Practical implications are believed to be that the study will support a more structured process towards data quality management, which in turn can aid decision-making, for example by more accurate cost-benefit analysis of preventive maintenance.

  • 11.
    Mansouri, Sina Sharif
    et al.
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Arranz, Miguel Castano
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Kanellakis, Christoforos
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Nikolakopoulos, George
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Autonomous MAV Navigation in Underground Mines Using Darkness Contours Detection2019Konferensbidrag (Refereegranskat)
    Abstract [en]

    This article considers a low-cost and light weight platform for the task of autonomous flying for inspection in underground mine tunnels. The main contribution of this paper is integrating simple, efficient and well-established methods in the computer vision community in a state of the art vision-based system for Micro Aerial Vehicle (MAV) navigation in dark tunnels. These methods include Otsu's threshold and Moore-Neighborhood object tracing. The vision system can detect the position of low-illuminated tunnels in image frame by exploiting the inherent darkness in the longitudinal direction. In the sequel, it is converted from the pixel coordinates to the heading rate command of the MAV for adjusting the heading towards the center of the tunnel. The efficacy of the proposed framework has been evaluated in multiple experimental field trials in an underground mine in Sweden, thus demonstrating the capability of low-cost and resource-constrained aerial vehicles to fly autonomously through tunnel confined spaces.

  • 12.
    Sierra, G.
    et al.
    Department of Electrical Engineering, University of Chile, Santiago.
    Orchard, M.
    Department of Electrical Engineering, University of Chile, Santiago, Chile.
    Goebel, Kai
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik. NASA Ames Research Center, Moffett Field, CA, USA.
    Kulkarni, C.
    SGT Inc., NASA Ames Research Center, Moffett Field, CA, USA.
    Battery Health Management for Small-size Battery-powered Rotary-wing Unmanned Aerial Vehicles: An Efficient Approach for Constrained Computing Platforms2019Ingår i: Reliability Engineering & System Safety, ISSN 0951-8320, E-ISSN 1879-0836, Vol. 182, s. 166-178Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This article presents a holistic framework for the design, implementation and experimental validation of Battery Management Systems (BMS) in rotatory-wing Unmanned Aerial Vehicles (UAVs) that allows to accurately (i) estimate the State of Charge (SOC), and (ii) predict the End of Discharge (EOD) time of lithium-polymer batteries in small-size multirotors by using a model-based prognosis architecture that is efficient and feasible to implement in low-cost hardware. The proposed framework includes a simplified battery model that incorporates the electric load dependence, temperature dependence and SOC dependence by using the concept of Artificial Evolution to estimate some of its parameters, along with a novel Outer Feedback Correction Loop (OFCL) during the estimation stage which adjusts the variance of the process noise to diminish bias in Bayesian state estimation and helps to compensate problems associated with incorrect initial conditions in a non-observable dynamic system. Also, it provides an aerodynamic-based characterization of future power consumption profiles. A quadrotor has been used as validation platform. The results of this work will allow making decisions about the flight plan and having enough confidence in those decisions so that the mission objectives can be optimally achieved.

  • 13.
    Bo, Lin
    et al.
    The State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing, China.
    Xu, Guanji
    The State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing, China.
    Liu, Xiaofeng
    The State Key Laboratory of Mechanical Transmissions, Chongqing University, Chongqing, China.
    Lin, Jing
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Bearing Fault Diagnosis Based on Subband Time-Frequency Texture Tensor2019Ingår i: IEEE Access, E-ISSN 2169-3536, Vol. 7, s. 37611-37619Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The texture feature tensor established from a subband time–frequency image (TFI) was extracted and used to identify the fault states of a rolling bearing. The TFI of adaptive optimal-kernel distribution was optimally partitioned into TFI blocks based on the minimum frequency band entropy. The texture features were extracted from the co-occurrence matrix of each TFI block. Based on the order of the segmented frequency bands, the texture feature tensor was constructed using the multidimensional feature vectors from all the blocks; this preserved the inherent characteristic of the TFI structure and avoided the information loss caused by vectorizing multidimensional features. The linear support higher order tensor machine based on the feature tensor was applied to identify the fault states of the rolling bearing.

  • 14.
    Kansal, Y.
    et al.
    Amity Institute of Information Technology, Amity University, Noida, India.
    Kapur, P.K.
    Amity Centre for Interdisciplinary Research, Amity University, Noida, India.
    Kumar, Uday
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Coverage-based vulnerability discovery modeling to optimize disclosure time using multiattribute approach2019Ingår i: Quality and Reliability Engineering International, ISSN 0748-8017, E-ISSN 1099-1638, Vol. 35, nr 1, s. 62-73Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Software vulnerabilities trend over time has been proposed by various researchers and academicians in recent years. But none of them have considered operational coverage function in vulnerability discovery modeling. In this research paper, we have proposed a generalized statistical model that determines the relationship between operational coverage function and the number of expected vulnerabilities. During the operational phase, possible vulnerable sites are covered and vulnerabilities present at a particular site are discovered with some probability. We have assumed that the proposed model follows the nonhomogeneous Poisson process properties; thus, different distributions are used to formulate the model. The numerical illustration shows that the proposed model performs better and has the good fitness to the Google Chrome data. The second focus of this research paper is to evaluate the total cost incurred by the developer after software release and to identify the optimal vulnerability disclosure time through multiobjective utility function. The proposed vulnerability discovery helps in optimization. The optimal time problem depends on the combined effect of cost, risk, and effort.

  • 15.
    Thaduri, Adithya
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Al-Jumaili, Mustafa
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Kour, Ravdeep
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Karim, Ramin
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Cybersecurity for eMaintenance in Railway Infrastructure: Risks and Consequences2019Ingår i: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 10, nr 2, s. 149-159Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Recently, due to the advancements in the ICT (Information and Communication Technology), there has been lot of emphasis on digitization of the existing and newly developed infrastructure. In transportation infrastructure, in general, 80% of the assets are already in place and there has been tremendous push to move to the digital era. For efficient and effective design, construction, operation and maintenance of the infrastructure, due to this digitization, there is increasing research trend in data-driven decision-making algorithms that are proved to be effective because of several advantages. Since railway is the backbone of the society, the data-driven approaches will ensure the continuous operation, efficient maintenance, planning and potential future investments. The breach and leak of this potential data to the wrong hands might result in havoc, risk, trust, hazards and serious consequences. Hence, the main purpose of this paper is to stress the potential challenges, consequences, threats, vulnerabilities and risk management of data security in the railway infrastructure in context of eMaintenance. In addition, this paper also identifies the research methods to obtain and secure this data for potential possible research.

  • 16.
    Kour, Ravdeep
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Tretten, Phillip
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Karim, Ramin
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Singh, Sarbjeet
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Cybersecurity Workforce in Railway: A Case Study2019Ingår i: Proceedings of the 5th International Workshop & Congress on eMaintenance 2019, 2019Konferensbidrag (Refereegranskat)
    Abstract [en]

    Railway will continue to adapt new digital solutions which are necessary and vulnerable to cyber threats. The history of cyber-attacks on critical infrastructures including railway suggests that there is a need for cybersecurity awareness. Both for employees and the general public. The very first step in cyber hygiene is cybersecurity training and awareness for the workforce. A well-educated workforce plays a vital role in building more cyber resiliency across the organization's operation and maintenance. The objective of this research is to evaluate the cybersecurity maturity level for workforce management in three railway organizations. The results show that there is a cybersecurity workforce gap and there is a need to eliminate this gap by enhancing cybersecurity workforce culture. Henceforth, this gap can be improved by developing cybersecurity culture, including cybersecurity training and awareness and by following recommendations provided in this paper.

  • 17.
    Li, Z.
    et al.
    Department of Mechanical and Aerospace Engineering, University of Central Florida, Orlando, United States.
    Goebel, Kai
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik. NASA Ames Research Center, Moffett Field, United States.
    Wu, D.
    Department of Mechanical and Aerospace Engineering, University of Central Florida, Orlando, United States.
    Degradation Modeling and Remaining Useful Life Prediction of Aircraft Engines Using Ensemble Learning2019Ingår i: Journal of engineering for gas turbines and power, ISSN 0742-4795, E-ISSN 1528-8919, Vol. 41, nr 4, artikel-id 041008Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Degradation modeling and prediction of remaining useful life (RUL) are crucial to prognostics and health management of aircraft engines. While model-based methods have been introduced to predict the RUL of aircraft engines, little research has been reported on estimating the RUL of aircraft engines using novel data-driven predictive modeling methods. The objective of this study is to introduce an ensemble learning-based prognostic approach to modeling an exponential degradation process due to wear as well as predicting the RUL of aircraft engines. The ensemble learning algorithm combines multiple base learners, including random forests (RFs), classification and regression tree (CART), recurrent neural networks (RNN), autoregressive (AR) model, adaptive network-based fuzzy inference system (ANFIS), relevance vector machine (RVM), and elastic net (EN), to achieve better predictive performance. The particle swarm optimization (PSO) and sequential quadratic optimization (SQP) methods are used to determine optimum weights that are assigned to the base learners. The predictive model trained by the ensemble learning algorithm is demonstrated on the data generated by the commercial modular aero-propulsion system simulation (C-MAPSS) tool. Experimental results have shown that the ensemble learning algorithm predicts the RUL of the aircraft engines with considerable robustness as well as outperforms other prognostic methods reported in the literature. 

  • 18.
    Saari, Juhamatti
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik. Luleå tekniska universitet, SKF-LTU University Technology Centre.
    Strömbergsson, Daniel
    Luleå tekniska universitet, Institutionen för teknikvetenskap och matematik, Maskinelement. Luleå tekniska universitet, SKF-LTU University Technology Centre.
    Lundberg, Jan
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Thomson, A.
    SKF (U.K), Livingston, Scotland, United Kingdom.
    Detection and identification of windmill bearing faults using a one-class support vector machine (SVM)2019Ingår i: Measurement, ISSN 0263-2241, E-ISSN 1873-412X, Vol. 137, s. 287-301Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The maintenance cost of wind turbines needs to be minimized in order to keep their competitiveness and, therefore, effective maintenance strategies are important. The remote location of wind farms has led to an opportunistic maintenance strategy where maintenance actions are postponed until they can be handled simultaneously, once the optimal opportunity has arrived. For this reason, early fault detection and identification are important, but should not lead to a situation where false alarms occur on a regular basis. The goal of the study presented in this paper was to detect and identify wind turbine bearing faults by using fault-specific features extracted from vibration signals. Automatic identification was achieved by training models by using these features as an input for a one-class support vector machine. Detection models with different sensitivity were trained in parallel by changing the model tuning parameters. Efforts were also made to find a procedure for selecting the model tuning parameters by first defining the criticality of the system and using it when estimating how accurate the detection model should be. Method was able to detect the fault earlier than using traditional methods without any false alarms. Optimal combination of features and model tuning parameters was not achieved, which could identify the fault location without using any additional techniques.

  • 19.
    Khan, Saad Ahmed
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Effects of top-of-rail friction modifiers on the friction, wear and cracks of railway rails2019Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    The railway is an economical and environmentally friendly mode of transport for long distances and heavy loads. The demands on the operators are increasing with increased competition in the market, and therefore they are currently demanding more track capacity. In the short term, the existing network is expected to deliver the increased capacity. In order to achieve increased capacity without introducing double track, either the axle load or the number of trains (i.e. the annual gross tonnage) needs to be increased, which will decrease the life of the rail and thus increase the maintenance cost. To increase the lifetime of the rails without compromising with regard to the axle load and speed, one must increase the strength of the rails, decrease the traction forces between the rails and wheels, or introduce a third body with anti-wear and anti-crack properties that can reduce the wear and rolling contact fatigue (RCF) without reducing the traction forces below the safety limit.

    The traction forces depend on several variables, for example third bodies in the wheel-rail interface, the train dynamics, the wheel and rail profiles, etc. Third bodies in the wheel-rail interface are one of the important influencing factors. The additive third bodies with anti-wear properties and friction reduction capabilities reduces both the wear and the RCF. However, a friction coefficient in the wheel tread and the top of the rail below 0.3 can cause slippage and a long braking distance. To reduce the degree of utilised friction to a value close to 0.35 from dry conditions with a value of 0.55, and thereby reduce the wear, a product known as top-of-rail friction modifier (TOR-FM) was developed in North America and presented in 2003 at the heavy haul conference. The TOR-FM manufacturers claim that their products provide a fixed range of friction coefficients (μ) and Kalker’s coefficients in the wheel-rail interface. Kalker’s coefficient considers the tendency of creepage between the rail and wheel as a function of the traction forces at lower creepage levels. Field and laboratory tests in the USA, Canada and China have determined the benefits of using friction control products, which include the reduction of RCF, wear, corrugation, bogie hunting, noise, and fuel consumption without any side effects. In contrast, researchers at Luleå University of Technology (LTU) have found that such products in certain conditions give unacceptably low friction that can cause long braking distances and slippage. Initial measurements performed using a wayside TOR-FM system on the Iron Ore Line (IOL – “Malmbanan” in Swedish) could not find any benefits of implementing such systems.

    Trafikverket is considering the implementation of the TOR-FM technology on the IOL. Directly implementing such technology can be inappropriate and expensive, because the reliability of a TOR-FM system has never been assessed for the conditions of the IOL. The IOL is the northernmost railway line in Sweden and is experiencing the problem of RCF, especially on its curves. This railway line is a single track and is mainly utilised by the ore freight trains operated by the Swedish mining company LKAB. The freight trains run by LKAB have an axle load of 30 tonnes, which is the heaviest in Europe. At present LKAB is planning to increase the axle load of their heavy haul trains to 32.5 tonnes, which will increase the RCF and wear issues.

    The present research investigated the effects of TOR-FMs using computer-based simulations, laboratory tests and field tests. The results from all the tests and simulations were used to calculate the life cycle cost of wayside and on-board systems. The simulation results have shown that by reducing the friction, the RCF can be reduced. This reduction in the RCF is greater on narrow curves than on larger curves as the traction forces decrease with an increase in the curve radius. Curves with a radius larger than m are not prone to RCF. The damage index method used in the simulation has also shown that on circular curves with a radius smaller than 300 m, the so-called “magic wear” rate can be achieved. Magic wear means that the wear rate due to normal operation is equal to the crack generation rate. The field results obtained using a handheld tribometer have shown that by using a TOR-FM, both the wear and the friction coefficients can be reduced. The content of the TOR-FM can have a significant effect on the carry distance and, generally, non-drying FMs have a longer carry distance. Excessive use of TOR-FM may cause unacceptably low friction and a high operational cost, and only result in an insignificant increase in the carry distance. In addition, it was also concluded that in the case of the wayside system during extreme winters, the equipment could have maintenance issues and thus a high operational cost. The on-board system is an economical alternative to the wayside system, as it has lower operation and maintenance costs. The results have also shown that snow and ice formation in the winter act as a lubricant. However, further investigations are needed to provide knowledge of the efficiency of such natural lubricants and their retention on the rail. The present research has taken the IOL as a case study, but the results will be applicable all over the world.

     

  • 20.
    Kour, Ravdeep
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Al-Jumaili, Mustafa
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Karim, Ramin
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Tretten, Phillip
    Luleå tekniska universitet, Institutionen för ekonomi, teknik och samhälle. Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    eMaintenance in railways: Issues and challenges in cybersecurity2019Ingår i: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit, ISSN 0954-4097, E-ISSN 2041-3017, Vol. 233, nr 10, s. 1012-1022Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The convergence of information technology and operation technology and the associated paradigm shift toward Industry 4.0 in complex systems, such as railways has brought significant benefits in reliability, maintainability, operational efficiency, capacity, as well as improvements in passenger experience. However, with the adoption of information and communications technologies in railway maintenance, vulnerability to cyber threats has increased. It is essential that organizations move toward security analytics and automation to improve and prevent security breaches and to quickly identify and respond to security events. This paper provides a statistical review of cybersecurity incidents in the transportation sector with a focus on railways. It uses a web-based search for data collection in popular databases. The overall objective is to identify cybersecurity challenges in the railway sector.

  • 21.
    Haidong, Shao
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik. State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, China. College of Mechanical and Vehicle Engineering, Hunan University, Changsha, China.
    Junsheng, Cheng
    State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, China. College of Mechanical and Vehicle Engineering, Hunan University, Changsha, China.
    Hongkai, Jiang
    School of Aeronautics, Northwestern Polytechnical University, Xi’an, China.
    Yu, Yang
    State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, China. College of Mechanical and Vehicle Engineering, Hunan University, Changsha, China.
    Zhantao, Wu
    State Key Laboratory of Advanced Design and Manufacturing for Vehicle Body, Hunan University, Changsha, China. College of Mechanical and Vehicle Engineering, Hunan University, Changsha, China.
    Enhanced deep gated recurrent unit and complex wavelet packet energy moment entropy for early fault prognosis of bearing2019Ingår i: Knowledge-Based Systems, ISSN 0950-7051, E-ISSN 1872-7409Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Early fault prognosis of bearing is a very meaningful yet challenging task to improve the security of rotating machinery. For this purpose, a novel method based on enhanced deep gated recurrent unit and complex wavelet packet energy moment entropy is proposed in this paper. First, complex wavelet packet energy moment entropy is defined as a new monitoring index to characterize bearing performance degradation. Second, deep gated recurrent unit network is constructed to capture the nonlinear mapping relationship hidden in the defined monitoring index. Finally, a modified training algorithm based on learning rate decay strategy is developed to enhance the prognosis capability of the constructed deep model. The proposed method is applied to analyze the simulated and experimental signals of bearing. The results demonstrate that the proposed method is more superior in sensibility and accuracy to the existing methods.

  • 22.
    Goebel, Kai
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik. Palo Alto Research Center, Palo Alto, CA, United States.
    Smith, Brian
    NASA Ames Research Center, Moffett Field, CA, United States.
    Bajawa, Anupa
    NASA Ames Research Center, Moffett Field, CA, United States.
    Ethics in prognostics and health management2019Ingår i: International Journal of Prognostics and Health Management, ISSN 2153-2648, E-ISSN 2153-2648, Vol. 10, nr 1, artikel-id 012Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    As we are entering an era where intelligent systems are omnipresent and where they also penetrate Prognostics and Health Management (PHM), the discussion of moral machines or ethics in engineering will inevitably engulf PHM as well. This article explores the topic of ethics within the PHM domain: how it is relevant, and how it may be dealt with in a conscientious way. The paper provides a historical perspective on ethics-related developments that resulted in the formulation of engineering ethics codes, regulations, and policies. By virtue of these developments, ethics has already been encapsulated in PHM systems. The specific areas that have traditionally driven ethics considerations include safety and security, and they increasingly include privacy, and environmental protection. During the course of future technology development, innovations will increasingly impact all of these topics. It is argued that consciously embracing these issues will increase the competitive advantage of a PHM technology solution. As a guideline, specific ethics attributes are derived from professional engineering ethics codes, and a path towards insertion into a requirements flowdown is suggested.

  • 23.
    Normark, Carl Jörgen
    et al.
    Luleå tekniska universitet, Institutionen för ekonomi, teknik och samhälle, Människa och teknik.
    Tretten, Phillip
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Guidelines for a mobile tool to address human factors issues in aircraft maintenance2019Ingår i: International Journal of Human Factors and Ergonomics, ISSN 2045-7804, E-ISSN 2045-7812Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Highly specialised personnel are dependent on others and diverse systems to perform error-free aircraft maintenance. Research has shown that the maintenance process can be improved to reduce errors and increase usability by using a mobile tool. The goal of this project was to draw on theories of user-centred design to explore what human factors issues for maintenance personnel can be addressed by a mobile tool to make the most out of maintenance planning, execution, and follow-up. Military aircraft maintenance personnel at an air force unit were interviewed and observed. The following six problem areas that could be improved by the use of a mobile tool were identified: several information sources must constantly be consulted; information is constantly transferred between different locations and media types; technical documentation can be inconsistent and hard to access; there are strict hierarchies and certifications of personnel; the means of recording and transferring communicative information are insufficient; and there can be a long lag time for updates, error reporting and feedback of actions. A correctly designed mobile tool could solve these problems by combining all the information sources and recording relevant maintenance information.

  • 24.
    Zhang, Bo
    et al.
    Infrastructure Inspection Research Institute, China Academy of Railway Sciences Corporation Limited, Beijing, China.
    Liu, Xiubo
    Infrastructure Inspection Research Institute, China Academy of Railway Sciences Corporation Limited, Beijing, China.
    Lin, Jing
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Identification of span of Multi-span Simply Supported Girders by the Longitudinal Level Waveforms2019Ingår i: International Journal of COMADEM, ISSN 1363-7681, Vol. 22, nr 3, s. 19-22Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In high-speed railways, the periodic component of longitudinal level on the top surface of the track can be observed for multi-span simply supported girders. To monitor this component, the paper proposes a method to determine the locating position of simply supported girders using longitudinal level waveforms. The method first applies time-frequency analysis to determine the locating position of simply supported girder bridges in the longitudinal level waveform. Then it adopts a local minimum detection strategy to identify the locating position of the girders. The method is evaluated using the longitudinal level data of a 100km high-speed railway in China; the results show good locating performance.

  • 25.
    Alsyouf, Imad
    et al.
    Industrial Engineering and Engineering Management, University of Sharjah, Sharjah, United Arab Emirates.
    Kumar, Uday
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Al-Ash, Lubna
    Industrial Engineering and Engineering Management, University of Sharjah, Sharjah, United Arab Emirates.
    Al-Hammadi, Muna
    Industrial Engineering and Engineering Management, University of Sharjah, Sharjah, United Arab Emirates.
    Improving baggage flow in the baggage handling system at a UAE-based airline using lean Six Sigma tools2019Ingår i: Quality Engineering, ISSN 0898-2112, E-ISSN 1532-4222, Vol. 30, nr 3, s. 432-452Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper presents a real successful implementation of lean six sigma methodology to continuously improve the baggage flow in a baggage handling system (BHS), by identifying the causes of mishandled baggage, and deriving solutions to enhance BHS performance. The results show that the main critical problems were low system reliability and the high number of bags passing through manual-encoding-stations. This research illustrates how to avoid baggage congestion and provides applicable and cost-effective solutions. The success of this project made the organisation aware of the opportunities that the application of lean Six Sigma methodology created in the aviation and airport sector.

  • 26.
    Zhang, Chuntian
    et al.
    State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University.
    Gao, Yuan
    State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University.
    Yang, Lixing
    State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University.
    Kumar, Uday
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Gao, Ziyou
    State Key Laboratory of Rail Traffic Control and Safety, Beijing Jiaotong University.
    Integrated optimization of train scheduling and maintenance planning on high-speed railway corridors2019Ingår i: Omega: The International Journal of Management Science, ISSN 0305-0483, E-ISSN 1873-5274, Vol. 87, s. 86-104Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Regular maintenances on high-speed railway facilities are performed in every night in China, and during regular maintenances, high-speed railway is not available for the sunset-departure and sunrise-arrival trains (SDSA-trains). In order to reduce the influence of regular maintenances on SDSA-trains, three operation modes are used in practice, which mainly consist of route selections between high-speed railway and normal-speed railway. In this paper, we use some linearization techniques to formulate a mixed integer linear programming (MILP) model to identify the operation modes and the timetable of SDSA-trains, by integrating the time window selection of regular maintenances on high-speed railways. The objective of the model is to minimize the total travel time of SDSA-trains. In the formulation of the model, we introduce state variables to indicate whether a train is running on high-speed railway or not, which makes it conveniently express the selection of operation modes. Based on the real data of Beijing-Guangzhou high-speed and normal-speed railway corridors in China, numerical experiments are carried out to test the proposed model and optimization method.

  • 27.
    Teymourian, Kiumars
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Seneviratne, Dammika
    Tecnalia Research and Innovation, La Almunia, Zaragoza, Spain.
    Galar, Diego
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik. Tecnalia Research and Innovation, La Almunia, Zaragoza, Spain.
    Integrating Ergonomics in Maintanability: A Case Study from Manufacturing Industry2019Ingår i: Journal of Industrial Engineering and Management Science, E-ISSN 2446-1822, Vol. 2018, nr 1, s. 131-150, artikel-id 8Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Maintainability is key part of Reliability, Availability, Maintainability and Safety (RAMS) estimation and prediction in complex assets. Indeed, availability calculation comprises accurate estimation of maintainability and frequently, it is just a time stamp for mean time to repair (MTTR) estimations. However, maintainability is a human related figure where the skill, capabilities, tools and the design of the asset play key role in its performance. The aim of this article is to describe the effects of ergonomists’ contribution during maintainability process for system/products design. System designer thinking in system and its subsystem in a way of technical functionality. On the other hand, ergonomists are expertise in human capability and limitation. If human become a part of system than their interface and interaction become crucial factors in a success of system performance and its sustainability. In this paper, it has discussed three main issues that help the process of maintainability design. These issues are safety, task analysis and risk analysis. It has also touched reliability engineer’s task to increase Overall Equipment Effectiveness (OEE). These issues are explained via a case study from a manufacturing industry.

  • 28.
    Yazdi, Mohammad
    et al.
    Centre for Marine Technology and Ocean Engineering (CENTEC), Instituto Superior Técnico Universidade de Lisboa.
    Soltanali, Hamzeh
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik. Department of Biosystems Engineering Ferdowsi University of Mashhad.
    Knowledge acquisition development in failure diagnosis analysis as an interactive approach2019Ingår i: International Journal on Interactive Design and Manufacturing, ISSN 1955-2513, E-ISSN 1955-2505, Vol. 13, nr 1, s. 193-210Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Safety and reliability analysis is an important issue to prevent an event which may to occurrence of catastrophic accident in process industries. In this context, conventional safety and reliability assessment technique like as fault tree analysis have been widely used in this regards; however, they still suffer in subjective uncertainty processing and dynamic structure representation which are important in risk assessment procedure. In this paper, a new framework based on 2-tuple intuitionistic fuzzy numbers and Bayesian network mechanism is proposed to evaluate system reliability, to deal with mentioned drawbacks, and to recognize the most critical system components which affects the system reliability. The reliability and safety guarantee of such system in the aspect of continuity operations and enhancing the safety of operators and vehicle drivers are crucial. The results revealed that the proposed model could be useful for diagnosing the systems’ faults compared with listing approaches of safety and reliability analysis.

  • 29.
    Saari, Esi
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    KPI framework for maintenance management through eMaintenance: Development, implementation, assessment, and optimization2019Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    Performance measurement is critical if any organization wants to thrive. The motivation for the thesis originated from the project “Key Performance Indicators (KPI) for control and management of maintenance process through eMaintenance (in Swedish: Nyckeltal för styrning och uppföljning av underhållsverksamhet m h a eUnderhåll)”, initiated and financed by a mining company in Sweden. The main purpose of this project is to propose an integrated KPI system for the mining company’s maintenance process through eMaintenance, including development, implementation, assessment, and optimization.

    There are gaps in the research, however, resulting in the following challenges. First, no KPI framework considers both technical and soft KPIs, so developing a system is problematic. Second, few studies have focused on implementing KPI measurement through eMaintenance. Third, there are gaps in KPI assessment. In assessing system availability, for example, the current analytical (e.g., Markov/semi-Markov) or simulation approaches (e.g., Monte Carlo simulation-based) cannot handle complicated state changes or are computationally expensive. In addition, few researchers have revealed the connections between technical and soft KPIs.  For those soft KPIs for which the distribution of data collected from eMaintenance systems (e.g., work orders) is not easily determined, studies are insufficient. Fourth, the current continuous improvement process for the KPIs is very time-consuming. In short, there is a need for a new approach.

    The thesis develops an integrated KPI framework consisting of technical KPIs (linked to machines) and soft KPIs (linked to maintenance workflow) to control and monitor the entire maintenance process to achieve the overall goals of the organization.  The proposed KPI framework makes use of four hierarchical levels and has 134 KPIs divided into technical and soft KPIs as follows: asset operation management has 23 technical KPIs, maintenance process management has 85 soft KPIs and maintenance resources management has 26 soft KPIs.

    The thesis discusses the proposed KPI framework; it lists the KPIs and provides timelines, definitions and general formulas for each specified KPI. Results will be used by the mining company to guide the implementation of the proposed KPIs in an eMaintenance environment.

    To suggest novel approaches to KPI assessment, the thesis takes system availability in the operational stage as an example.  It proposes parametric Bayesian approaches to assess system availability. With these approaches, Mean Time to Failure (MTTF) and Mean Time to Repair (MTTR) can be treated as distributions instead of being “averaged” by point estimation. This better reflects reality.  Markov Chain Monte Carlo (MCMC) approach is adopted to take advantage of both analytical and simulation methods. Because of MCMC’s high dimensional numerical integral calculation, the selection of prior information and descriptions of reliability/maintainability can be more flexible and realistic. The limitations of data sample size can also be compensated for. In the case studies, Time to Failure (TTF) and Time to Repair (TTR) are determined using a Bayesian Weibull model and a Bayesian lognormal model, respectively. The proposed approach can integrate analytical and simulation methods for system availability assessment and could be applied to other technical problems in asset management (e.g., other industries, other systems). By comparing the results with and without considering the threshold for censoring data, the research shows the connection between technical and soft KPIs, and suggests the threshold can be used as a monitoring line for continuous improvement in the mining company. For those soft KPIs for which the distribution of data collected from the eMaintenance system (e.g., work orders) is not easily determined, other approaches, such as time series analysis (if the data are “fast moving”), the Croston method (if the data are “intermittent”), or the bootstrap method (if the data are “slow moving”) could be applied. 

    To ensure the KPI framework can be improved continuously, the thesis performs a comparison study to find the gaps between current and proposed KPIs in the mining company. It adapts a roadmap from the railway industry to show how optimization can be promoted by reviewing and improving the KPI framework.

    Results from this study will be applied to the company and guide its development, implementation and assessment of the KPIs through eMaintenance with continuous improvement. The proposed approaches could also be applied to other technical problems in asset management (e.g., other industries, other system).

  • 30.
    Illankoon, Prasanna
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Manathunge, Yamuna
    Department of Education and Training, University of Vocational Technology, Ratmalana, Sri Lanka.
    Tretten, Phillip
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Abeysekara, John
    Work Science Academy, Kandana, Sri Lanka.
    Singh, Sarbjeet
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Lockout and Tagout in a Manufacturing Setting from a Situation Awareness Perspective2019Ingår i: Safety, ISSN 2313-576X, Vol. 5, nr 2Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Applying lockouts during maintenance is intended to avoid accidental energy release, whereas tagging them out keeps employees aware of what is going on with the machine. In spite of regulations, serious accidents continue to occur due to lapses during lockout and tagout (LOTO) applications. Few studies have examined LOTO effectiveness from a user perspective. This article studies LOTO processes at a manufacturing organization from a situation awareness (SA) perspective. Technicians and machine operators were interviewed, a focus group discussion was conducted, and operators were observed. Qualitative content analysis revealed perceptual, comprehension and projection challenges associated with different phases of LOTO applications. The findings can help lockout/tagout device manufacturers and organizations that apply LOTO to achieve maximum protection.

  • 31.
    Esmaeili Kelishomi, A.
    et al.
    Xi'an Jiaotong University, Xi'an, China.
    Garmabaki, Amir Soleimani
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Bahaghighat, M.
    Raja University, Qazvin, Iran.
    Dong, J.
    Xi'an Jiaotong University, Xi'an, China.
    Mobile User Indoor-Outdoor Detection Through Physical Daily Activities2019Ingår i: Sensors, ISSN 1424-8220, E-ISSN 1424-8220, nr 3, artikel-id 511Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    An automatic, fast, and accurate switching method between Global Positioning System and indoor positioning systems is crucial to achieve current user positioning, which is essential information for a variety of services installed on smart devices, e.g., location-based services (LBS), healthcare monitoring components, and seamless indoor/outdoor navigation and localization (SNAL). In this study, we proposed an approach to accurately detect the indoor/outdoor environment according to six different daily activities of users including walk, skip, jog, stay, climbing stairs up and down. We select a number of features for each activity and then apply ensemble learning methods such as Random Forest, and AdaBoost to classify the environment types. Extensive model evaluations and feature analysis indicate that the system can achieve a high detection rate with good adaptation for environment recognition. Empirical evaluation of the proposed method has been verified on the HASC-2016 public dataset, and results show 99% accuracy to detect environment types. The proposed method relies only on the daily life activities data and does not need any external facilities such as the signal cell tower or Wi-Fi access points. This implies the applicability of the proposed method for the upper layer applications.

  • 32.
    Illankoon, Prasanna
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Tretten, Phillip
    Kumar, Uday
    Modelling human cognition of abnormal machine behaviour2019Ingår i: Human-Intelligent Systems Integration, ISSN 2524-4876, Vol. 1, nr 1, s. 3-26Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Despite the advances in intelligent systems, there is no guarantee that those systems will always behave normally. Machine abnormalities, unusual responses to controls or false alarms, are still common; therefore, a better understanding of how humans learn and respond to abnormal machine behaviour is essential. Human cognition has been researched in many domains. Numerous theories such as utility theory, three-level situation awareness and theory of dual cognition suggest how human cognition behaves. These theories present the varieties of human cognition including deliberate and naturalistic thinking. However, studies have not taken into consideration varieties of human cognition employed when responding to abnormal machine behaviour. This study reviews theories of cognition, along with empirical work on the significance of human cognition, including several case studies. The different propositions of human cognition concerning abnormal machine behaviour are compared to dual cognition theories. Our results show that situation awareness is a suitable framework to model human cognition of abnormal machine behaviour. We also propose a continuum which represents varieties of cognition, lying between explicit and implicit cognition. Finally, we suggest a theoretical approach to learn how the human cognition functions when responding to abnormal machine behaviour during a specific event. In conclusion, we posit that the model has implications for emerging waves of human-intelligent system collaboration.

  • 33.
    Strömbergsson, Daniel
    et al.
    Luleå tekniska universitet, Institutionen för teknikvetenskap och matematik, Maskinelement.
    Marklund, Pär
    Luleå tekniska universitet, Institutionen för teknikvetenskap och matematik, Maskinelement.
    Berglund, Kim
    Luleå tekniska universitet, Institutionen för teknikvetenskap och matematik, Maskinelement.
    Saari, Juhamatti
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Thomson, Allan
    Industrial Digitalisation & Solutions, Livingston, Scotland.
    Mother wavelet selection in the discrete wavelet transform for condition monitoring of wind turbine drivetrain bearings2019Ingår i: Wind Energy, ISSN 1095-4244, E-ISSN 1099-1824Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Although the discrete wavelet transform has been used for diagnosing bearing faults for two decades, most work in this field has been done with test rig data. Since field data starts to be made more available, there is a need to shift into application studies.

    The choice of mother wavelet, ie, the predefined shape used to analyse the signal, has previously been investigated with simulated and test rig data without consensus of optimal choice in literature. Common between these investigations is the use of the wavelet coefficients' Shannon entropy to find which mother wavelet can yield the most useful features for condition monitoring.

    This study attempts to find the optimal mother wavelet selection using the discrete wavelet transform. Datasets from wind turbine gearbox accelerometers, consisting of enveloped vibration measurements monitoring both healthy and faulty bearings, have been analysed. The bearing fault frequencies' excitation level has been analysed with 130 different mother wavelets, yielding a definitive measure on their performance. Also, the applicability of Shannon entropy as a ranking method of mother wavelets has been investigated.

    The results show the discrete wavelet transforms ability to identify faults regardless of mother wavelet used, with the excitation level varying no more than 4%. By analysing the Shannon entropy, broad predictions to the excitation level could be drawn within the mother wavelet families but no direct correlation to the main results. Also, the high computational effort of high order Symlet wavelets, without increased performance, makes them unsuitable.

  • 34.
    Zhang, Xiaoge
    et al.
    Department of Civil and Environmental Engineering, Vanderbilt University, Nashville, USA.
    Mahadevan, Sankaran
    Department of Civil and Environmental Engineering, Vanderbilt University, Nashville, USA..
    Goebel, Kai
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik. Systems Sciences Lab, Palo Alto Research Center, Palo Alto, CA, USA.
    Network Reconfiguration for Increasing Transportation System Resilience Under Extreme Events2019Ingår i: Risk Analysis, ISSN 0272-4332, E-ISSN 1539-6924, Vol. 39, nr 9, s. 2054-2075Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Evacuating residents out of affected areas is an important strategy for mitigating the impact of natural disasters. However, the resulting abrupt increase in the travel demand during evacuation causes severe congestions across the transportation system, which thereby interrupts other commuters' regular activities. In this article, a bilevel mathematical optimization model is formulated to address this issue, and our research objective is to maximize the transportation system resilience and restore its performance through two network reconfiguration schemes: contraflow (also referred to as lane reversal) and crossing elimination at intersections. Mathematical models are developed to represent the two reconfiguration schemes and characterize the interactions between traffic operators and passengers. Specifically, traffic operators act as leaders to determine the optimal system reconfiguration to minimize the total travel time for all the users (both evacuees and regular commuters), while passengers act as followers by freely choosing the path with the minimum travel time, which eventually converges to a user equilibrium state. For each given network reconfiguration, the lower-level problem is formulated as a traffic assignment problem (TAP) where each user tries to minimize his/her own travel time. To tackle the lower-level optimization problem, a gradient projection method is leveraged to shift the flow from other nonshortest paths to the shortest path between each origin-destination pair, eventually converging to the user equilibrium traffic assignment. The upper-level problem is formulated as a constrained discrete optimization problem, and a probabilistic solution discovery algorithm is used to obtain the near-optimal solution. Two numerical examples are used to demonstrate the effectiveness of the proposed method in restoring the traffic system performance.

  • 35.
    Anandika, Rayendra
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Stenström, Christer
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Lundberg, Jan
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Non-destructive measurement of artificial near-surface cracks for railhead inspection2019Ingår i: Insight (Northampton), ISSN 1354-2575, E-ISSN 1754-4904, Vol. 61, nr 7, s. 373-379Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper delivers a study involving the inspection of artificial surface cracks with depths ranging from 0.25-2.5 mm from the surface and with a crack angle of 30°, which is a typical angle for surface cracks in railheads. The inspections were conducted using three different techniques: phased array ultrasonics, single-element ultrasonics and alternating current potential drop (ACPD). For the ultrasonic techniques, the study focused on employing either longitudinal or shear wave signals. In the railway industry, shallow surface cracks in railheads are caused by rolling contact fatigue (RCF). In this study, artificial defects were made, allowing the authors to explore the extent to which the ultrasonic measurement techniques can detect such defects. The negative effect of a dead zone near to the surface in the ultrasonic tests was reduced by using a wedge attachment. A discussion on the extent to which the techniques can be used in field tests was also provided. The most important result is that shallow cracks ranging from 0.25-2.5 mm were successfully characterised with acceptable accuracy. The 2.5 mm-deep crack can be measured with an accuracy of 0.8% using a 20 MHz single-element probe and with an accuracy of 3.5% using a 5 MHz phased array (64 elements, 0.6 mm pitch). The characterisations were performed using a filtering method that was developed in this study.

    1675605

  • 36.
    Saari, Esi
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Lin, Jing
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Liu, Bin
    Department of Management Science, University of Strathclyde, Glasgow, UK .
    Zhang, Liangwei
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik. Department of Industrial Engineering, Dongguan University of Technology, Dongguan, China .
    Karim, Ramin
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Novel Bayesian Approach to Assess System Availability using a Threshold to Censor Data2019Ingår i: International Journal of Performability Engineering, ISSN 0973-1318, Vol. 15, nr 5, s. 1314-1325Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Assessment of system availability has been studied from the design stage to the operational stage in various system configurations using either analytic or simulation techniques. However, the former cannot handle complicated state changes, and the latter is computationally expensive. This study proposes a Bayesian approach to evaluate system availability. In this approach: 1) Mean Time to Failure (MTTF) and Mean Time to Repair (MTTR) are treated as distributions instead of being "averaged" to better describe real scenarios and overcome the limitations of data sample size; 2) Markov Chain Monte Carlo (MCMC) simulations are applied to take advantage of the analytical and simulation methods; and 3) a threshold is set up for Time to Failure (TTR) data and Time to Repair (TTR) data, and new datasets with right-censored data are created to reveal the connections between technical and "Soft" KPIs. To demonstrate the approach, the paper considers a case study of a balling drum system in a mining company. In this system, MTTF and MTTR are determined by a Bayesian Weibull model and a Bayesian lognormal model, respectively. The results show that the proposed approach can integrate the analytical and simulation methods to assess system availability and could be applied to other technical problems in asset management (e.g., other industries, other systems). By comparing the results with and without considering the threshold for censoring data, we show the threshold can be used as a monitoring line for continuous improvement in the investigated mining company.

  • 37.
    Soltanali, Hamzeh
    et al.
    Ferdowsi University of Mashhad, Mashhad, Iran.
    Rohani, Abbas
    Ferdowsi University of Mashhad, Mashhad, Iran.
    Tabasizadeh, Mohammad
    Ferdowsi University of Mashhad, Mashhad, Iran.
    Hossein Abbaspour-Fard, Mohammad
    Ferdowsi University of Mashhad, Mashhad, Iran.
    Parida, Aditya
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Operational reliability evaluation-based maintenance planning for automotive production line2019Ingår i: Quality Technology & Quantitative Management, ISSN 1684-3703, E-ISSN 1811-4857Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Reliability evaluation plays a critical role in upgrading the availability and productivity of automotive manufacturing industries by adopting the well-planned maintenance. Due to the lack of operation management studies in automotive industry, this paper addresses an operational reliability evaluation through failure behavior trend in an automotive production line. The main approaches for reliability analysis in this study include statistical structure and Monte Carlo simulation model. The statistical structure consists of three steps: data acquisition and homogenization process, validity of the trend hypothesis and parameters estimation. The reliability evaluation under statistical approach identified the main bottlenecks through the recognized behavior trend of system so that needs to be considered as a priority. Besides, K–R algorithm as Monte Carlo simulation was carried out to simulate reliability regarding failure distribution function. The result of Monte Carlo simulation with different iterations provides a high prediction accuracy of reliability with the lowest error. In addition, regarding the computed reliability through the proposed approaches and total expected cost, a reliability-based maintenance optimization model was conducted. The proposed maintenance intervals could be useful for improving the operational performance of critical components in automotive system.

  • 38.
    Zhang, Shuangsheng
    et al.
    School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China.Xuzhou Urban Water Resources Management Office, Xuzhou, China.
    Liu, Hanhu
    School of Environment Science and Spatial Informatics, China University of Mining and Technology, Xuzhou, China..
    Qiang, Jing
    School of Mathematics, China University of Mining and Technology, Xuzhou, China.
    Gao, Hongze
    GHD Services, Inc, Waterloo, Ontario, Canada.
    Galar, Diego
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Lin, Jing
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Optimization of Well Position and Sampling Frequency for Groundwater Monitoring and Inverse Identification of Contamination Source Conditions Using Bayes’ Theorem2019Ingår i: CMES - Computer Modeling in Engineering & Sciences, ISSN 1526-1492, E-ISSN 1526-1506, Vol. 119, nr 2, s. 373-394Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Coupling Bayes’ Theorem with a two-dimensional (2D) groundwater solute advection-diffusion transport equation allows an inverse model to be established to identify a set of contamination source parameters including source intensity (M ), release location ( X0 , Y0) and release time (T0), based on monitoring well data. To address the issues of insufficient monitoring wells or weak correlation between monitoring data and model parameters, a monitoring well design optimization approach was developed based on the Bayesian formula and information entropy. To demonstrate how the model works, an exemplar problem with an instantaneous release of a contaminant in a confined groundwater aquifer was employed. The information entropy of the model parameters posterior distribution was used as a criterion to evaluate the monitoring data quantity index. The optimal monitoring well position and monitoring frequency were solved by the two-step Monte Carlo method and differential evolution algorithm given a known well monitoring locations and monitoring events. Based on the optimized monitoring well position and sampling frequency, the contamination source was identified by an improved Metropolis algorithm using the Latin hypercube sampling approach. The case study results show that the following parameters were obtained: 1) the optimal monitoring well position (D) is at (445, 200); and 2) the optimal monitoring frequency (Δt) is 7, providing that the monitoring events is set as 5 times. Employing the optimized monitoring well position and frequency, the mean errors of inverse modeling results in source parameters (M, X0 ,Y0 ,T0 ) were 9.20%, 0.25%, 0.0061%, and 0.33%, respectively. The optimized monitoring well position and sampling frequency can effectively safeguard the inverse modeling results in identifying the contamination source parameters. It was also learnt that the improved Metropolis-Hastings algorithm (a Markov chain Monte Carlo method) can make the inverse modeling result independent of the initial sampling points and achieves an overall optimization, which significantly improved the accuracy and numerical stability of the inverse modeling results.

  • 39.
    Raposo, Hugo
    et al.
    Coimbra University-UC, Department of Mechanical Engineering, Centre for Mechanical Engineering, Materials and Processes (CEMMPRE), Coimbra, Portugal.
    Torres Farinha, José
    Coimbra University-UC, Department of Mechanical Engineering, Centre for Mechanical Engineering, Materials and Processes (CEMMPRE), Coimbra, Portugal.
    Fonseca, Inácio
    Coimbra University-UC, Department of Mechanical Engineering, Centre for Mechanical Engineering, Materials and Processes (CEMMPRE), Coimbra, Portugal.
    Galar, Diego
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Predicting condition based on oil analysis: A case study2019Ingår i: Tribology International, ISSN 0301-679X, E-ISSN 1879-2464, Vol. 135, s. 65-74Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The paper presents and discusses a model for condition monitoring. Using data from the oil in the Diesel engines of a fleet of urban buses, it studies the evolution of degradation and develops a predictive maintenance policy for oil replacement. Based on the analysis of the oil condition, the intervals of oil replacement can be expanded, allowing increased availability. The paper links time series forecasting with the statistical behavior of some oil effluents, like soot. This exercise can be expanded to include other variables, and the model has the potential to be applied to other physical assets to achieve the best availability based on a condition monitoring policy.

  • 40.
    Soleimanmeigouni, Iman
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Predictive Models for Railway Track Geometry Degradation2019Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    Railways are a vital and effective means of mass transportation and play a vital role in modern transportation and social development. The benefits of the railway compared to other transportation modes are a high capacity, high efficiency and low pollution, and owing to these advantages, railways are nowadays experiencing a higher demand for the transportation of passengers and goods. This is in turn imposing higher demands on the railway capacity and service quality. As a result, infrastructure managers are being driven to develop new strategies and plans to fulfil new requirements, which include a higher level of resilience against failure, a more robust and available infrastructure, and cost reduction. This can be achieved by making efficient and effective maintenance decisions by applying RAMS (reliability, availability, maintainability, and safety) analysis and LCC (life cycle cost) assessment.

    A major part of the railway maintenance burden is related to track geometry maintenance. Due to the forces induced on the track by traffic, the railway degrades over time, causing deviations from the designed vertical and horizontal alignment. When the track geometry degrades to an unacceptable level, this can cause catastrophic consequences, such as derailment. Maintenance actions are used to control the degradation of the track and restore the geometry condition of the track sections to an acceptable state.

    With the current advancements in the field of technologies for railway track geometry measurement, a large amount of event data and condition monitoring data is available. Such technologies, along with advances in predictive analytics, are providing the possibility of predicting the track geometry condition in support of a predictive maintenance strategy. The aim of the research conducted for this thesis has been to develop methodologies and tools for the prediction of railway track geometry degradation, in order to facilitate and enhance the capability of making effective decisions for inspection and maintenance planning. To achieve the purpose of this research, literature studies, case studies and simulations have been conducted.

    Firstly, a literature review was performed to identify the existing knowledge gaps and challenges for track geometry degradation modelling and maintenance planning. Secondly, a case study was conducted to analyse the effect of tamping on the track geometry condition. By considering the track geometry condition before tamping as the predictor, a probabilistic approach was utilised to model the recovery after tamping interventions. Thirdly, a two-level piecewise linear framework was developed to model the track geometry evolution over a spatial and temporal space. This model was implemented in a comprehensive case study. Fourthly, a data-driven analytical model was developed to predict the occurrence of track geometry defects. This model enables infrastructure managers to predict the occurrence of severe isolated geometry defects. Finally, an integrated model was created to investigate the effect of different inspection intervals on the track geometry condition.

  • 41.
    Kansal, Yogita
    et al.
    Amity Institute of Information Technology, Amity University.
    Kapur, Parmad Kumar
    Amity Center for Interdisciplinary Research, Amity University.
    Kumar, Uday
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Kumar, Deepak
    Amity Institute of Information Technology, Amity University.
    Prioritizing Vulnerabilities using ANP and Evaluating their Optimal Discovery and Patch Release Time2019Ingår i: International Journal of Mathematics in Operational Research (IJMOR), ISSN 1757-5850, E-ISSN 1757-5869, Vol. 14, nr 2, s. 236-267Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Method for filtering and identifying a vulnerability class that has high probability of occurrence is needed by organisations to patch their software in a timely manner. In this paper, our first step is to filter the most frequently observed vulnerability type/class through a multi-criteria decision making that involves dependency among various criteria and feedback from various alternatives, known as analytic network process. We will also formulate a cost model to provide a solution to the developers facing high revenue debt because of the occurrence of highly exploited vulnerabilities belonging to the filtered group. The main aim of formulating the cost model is to evaluate the optimal discovery and patch release time such that the total developer's cost could be minimised subject to risk constraints. To illustrate the proposed approach, reported vulnerabilities of Google Chrome with high exploitability have been examined at its source level.

  • 42.
    Thaduri, Adithya
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Famurewa, Stephen Mayowa
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Verma, Ajit Kumar
    Western Norway University of Applied Sciences, Haugesund .
    Kumar, Uday
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Process Mining for Maintenance Decision Support2019Ingår i: System Performance and Management Analytics / [ed] P. K. Kapur, Yury Klochkov, Ajit Kumar Verma, Gurinder Singh, Springer, 2019, s. 279-293Kapitel i bok, del av antologi (Refereegranskat)
    Abstract [en]

    In carrying out maintenance actions, there are several processes running simultaneously among different assets, stakeholders, and resources. Due to the complexity of maintenance process in general, there will be several bottlenecks for carrying out actions that lead to reduction in maintenance efficiency, increase in unnecessary costs and a hindrance to operations. One of the tools that is emerging to solve the above issues is the use Process Mining tools and models. Process mining is attaining significance for solving specific problems related to process such as classification, clustering, discovery of process, prediction of bottlenecks, developing of process workflow, etc. The main objective of this paper is to utilize the concept of process mining to map and comprehend a set of maintenance reports mainly repair or replacement from some lines on the Swedish railway network. To attain the above objective, the reports were processed to extract out time related maintenance parameters such as  administrative, logistic and repair times. Bottlenecks are identified in the maintenance process and this information will be useful for maintenance service providers, infrastructure managers, asset owners and other stakeholders for improvement and maintenance effectiveness.

  • 43.
    Hulse, Daniel
    et al.
    School of Mechanical, Industrial and Manufacturing Engineering, Oregon State University, Corvallis, Oregon, USA.
    Hoyle, Christopher
    School of Mechanical, Industrial and Manufacturing Engineering, Oregon State University, Corvallis, Oregon, USA.
    Goebel, Kai
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik. Discovery and Systems Health, Intelligent Systems Division, NASA Ames Research Center, Moffett Field, California, USA.
    Tumer, Irem Y.
    School of Mechanical, Industrial and Manufacturing Engineering, Oregon State University, Corvallis, Oregon, USA.
    Quantifying the Resilience-Informed Scenario Cost Sum: A Value-Driven Design Approach for Functional Hazard Assessment2019Ingår i: Journal of mechanical design (1990), ISSN 1050-0472, E-ISSN 1528-9001, Vol. 141, nr 2, artikel-id MD-18-1503Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Complex engineered systems can carry risk of high failure consequences, and as a result, resilience—the ability to avoid or quickly recover from faults—is desirable. Ideally, resilience should be designed-in as early in the design process as possible so that designers can best leverage the ability to explore the design space. Toward this end, previous work has developed functional modeling languages which represent the functions which must be performed by a system and function-based fault modeling frameworks have been developed to predict the resulting fault propagation behavior of a given functional model. However, little has been done to formally optimize or compare designs based on these predictions, partially because the effects of these models have not been quantified into an objective function to optimize. The work described herein closes this gap by introducing the resilience-informed scenario cost sum (RISCS), a scoring function which integrates with a fault scenario-based simulation, to enable the optimization and evaluation of functional model resilience. The scoring function accomplishes this by quantifying the expected cost of a design's fault response using probability information, and combining this cost with design and operational costs such that it may be parameterized in terms of designer-specified resilient features. The usefulness and limitations of using this approach in a general optimization and concept selection framework are discussed in general, and demonstrated on a monopropellant system design problem. Using RISCS as an objective for optimization, the algorithm selects the set of resilient features which provides the optimal trade-off between design cost and risk. For concept selection, RISCS is used to judge whether resilient concept variants justify their design costs and make direct comparisons between different model structures.

  • 44.
    Martinetti, Alberto
    et al.
    Design, Production and Management Department, University of Twente, Enschede, The Netherlands.
    Costa Marques, Henrique
    Logistics Engineering Laboratory, Aeronautics Institute of Technology, São José dos Campos, Brazil.
    Singh, Sarbjeet
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    van Dongen, Leo
    Design, Production and Management Department, University of Twente, Enschede, The Netherlands.
    Reflections on the Limited Pervasiveness of Augmented Reality in Industrial Sectors2019Ingår i: Applied Sciences, E-ISSN 2076-3417, Vol. 9, nr 16, artikel-id 3382Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The paper aims to investigate the reasons why Augmented Reality (AR) has not fully broken the industrial market yet, or found a wider application in industries. The main research question the paper tries to answer is: what are the factors (and to what extent) that are limiting AR? Firstly, a reflection on the state of art of AR applications in industries is proposed, to discover the sectors more commonly chosen for deploying the technology so far. Later, based on a survey conducted after that, three AR applications have been tested on manufacturing, automotive, and railway sectors, and the paper pinpoints key aspects that are conditioning its embedding in the daily working life. In order to compare whether the perception of employees from railway, automotive, and manufacturing sectors differs significantly, a one-way analysis of variance (ANOVA) has been used. Later, suggestions are formulated in order to improve these aspects in the industry world. Finally, the paper indicates the main conclusions, highlighting possible future researches to start.

  • 45.
    Block, Jan
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik. Saab Support and Services, Logistics Analysis and Fleet Monitoring, Lifecycle Logistics Division, Linköping, Sweden.
    Ahmadi, Alireza
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Xun, Xiao
    School of Fundamental Sciences, Massey University, Palmerston North, New Zealand.
    Kumar, Uday
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Spares Provisioning Strategy for Periodically Replaced Units within the Fleet Retirement Period2019Ingår i: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 10, nr 3, s. 299-315Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Within aviation enterprises, the process of dismantling an aircraft at the end of its life is referred to as parting-out. Obviously, the asset value of the units and materials parted out from the retired airframes can be considerable. The benchmarked best practice within the aviation industry is to dismantle the retired aircraft and use the parted-out spares to support the remaining fleet or to offer them on the surplus market. Part-out-based spares provisioning (PBSP) has been a major focus of attention for aviation companies. The PBSP approach is a complex task that requires a multidisciplinary and integrated decision-making process. In order to control the stock level and fulfil the decision criteria within PBSP, it is necessary to make decisions on the termination, at specific times, of both the parting-out process and the maintenance and repair actions performed on the units.

    This paper considers repairable units and introduces a computational model to identify the applicable alternatives for repair termination times that will minimize the number of remaining spares at the end of the retirement period, while fulfilling the availability requirement for spares during the PBSP period, at the lowest possible cost.  The feasible alternatives are compared with regard to their respective costs, and the most cost-effective solution is selected. The cost model uses estimates of future maintenance requirements, the turn-around times, the cost of the various maintenance tasks, the future spares consumption, and the estimated salvage of spares from retired aircraft. The output of the model is a set of applicable alternatives which satisfy the availability requirements for spares for the active fleet. The method is illustrated using a case study performed on the Saab-105 training aircraft. 

    The results show that the proposed PBSP approach and computational model provide added value from a sustainability point of view, since the use of existing resources is maximized during the retirement process, through the process of reclaiming units and the applicable maintenance termination alternatives. The implementation of the proposed computational model in a PBSP programme provides a detailed and situation-based overview of the stock level dynamics, and contributes to the spares provisioning process by providing solutions to issues such as obsolescence, last-time buys and cannibalization.

  • 46.
    Soltanali, Hamzeh
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik. Ferdowsi University of Mashhad, Mashhad, Iran.
    Garmabaki, Amir Soleimani
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Thaduri, Adithya
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Parida, Aditya
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Kumar, Uday
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Rohani, Abbas
    Ferdowsi University of Mashhad, Mashhad, Iran.
    Sustainable production process: An application of reliability, availability, and maintainability methodologies in automotive manufacturing2019Ingår i: Journal of Risk and Reliability, ISSN 1748-006X, E-ISSN 1748-0078, Vol. 233, nr 4, s. 682-697Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Automotive manufacturing industries are required to improve their productivity with higher production rates at the lowest cost, less number of unexpected shutdowns, and reliable operation. In order to achieve the above objectives, the application of reliability, availability, and maintainability methodologies can constitute for resilient operation, identifying the bottlenecks of manufacturing process and optimization of maintenance actions. In this article, we propose a framework for reliability, availability, and maintainability evaluation and maintenance optimization to improve the performance of conveying process of vehicle body in an automotive assembly line. The results of reliability, availability, and maintainability analysis showed that the reliability and maintainability of forklift and loading equipment are the main bottlenecks. To find the optimal maintenance intervals of each unit, a multi-attribute utility theory is applied for multi-criteria decision model considering reliability, availability, and costs. Due to the series configuration of conveying process in automotive assembly line, the optimized time intervals are obtained using opportunistic maintenance strategy. The results could be useful to improve operational performance and sustainability of the production process.

  • 47.
    Saari, Esi
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Lin, Jing
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Zhang, Liangwei
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik. Department of Industrial Engineering, Dongguan University of Technology, Dongguan, China.
    Liu, B.
    Department of Management Science, University of Strathclyde, Glasgow, United Kingdom.
    System availability assessment using a parametric Bayesian approach: a case study of balling drums2019Ingår i: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Assessment of system availability usually uses either an analytical (e.g., Markov/semi-Markov) or a simulation approach (e.g., Monte Carlo simulation-based). However, the former cannot handle complicated state changes and the latter is computationally expensive. Traditional Bayesian approaches may solve these problems; however, because of their computational difficulties, they are not widely applied. The recent proliferation of Markov Chain Monte Carlo (MCMC) approaches have led to the use of the Bayesian inference in a wide variety of fields. This study proposes a new approach to system availability assessment: a parametric Bayesian approach using MCMC, an approach that takes advantages of the analytical and simulation methods. By using this approach, mean time to failure (MTTF) and mean time to repair (MTTR) are treated as distributions instead of being “averaged”, which better reflects reality and compensates for the limitations of simulation data sample size. To demonstrate the approach, the paper considers a case study of a balling drum system in a mining company. In this system, MTTF and MTTR are determined in a Bayesian Weibull model and a Bayesian lognormal model respectively. The results show that the proposed approach can integrate the analytical and simulation methods to assess system availability and could be applied to other technical problems in asset management (e.g., other industries, other systems)

  • 48.
    Kyriakidis, Miltos
    et al.
    ETH Zurich, Future Resilient Systems, Singapore - ETH Centre, Singapore.
    Simanjuntak, Samuel
    Centre for Transport Studies, Imperial College London, United Kingdom.
    Singh, Sarbjeet
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Majumdar, Arnab
    Centre for Transport Studies, Imperial College London, United Kingdom.
    The indirect costs assessment of railway incidents and their relationship to human error: The case of Signals Passed at Danger2019Ingår i: Journal of Rail Transport Planning & Management, ISSN 2210-9706, E-ISSN 2210-9714, Vol. 9, s. 34-45Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The majority of railway incidents result neither in passenger nor operators harm, nor they lead to any severe damage on the rolling stock or the infrastructure. Nevertheless, such incidents result in financial loses, broadly known as indirect costs, which are difficult to identify, isolate, evaluate, and quantify. This paper introduces a framework to quantify the indirect costs in railway operations. Furthermore, as degraded human performance remains a major contributor to operational errors and railway incidents, this study explores for associations between the indirect costs and the factors that affect and contribute to degraded human performance. The framework was implemented in the calculation of the Category A1 Signals Passed at Danger (SPADs) indirect costs. Data was obtained from two UK train operators, while the associated human performance was analysed using the Railway-Performance Shaping Factors (R-PSFs) taxonomy. Employing Spearman's rank order correlation and Fisher's exact statistical tests the associations between R-PSFs and indirect costs were reviewed. Results show significant correlations between the R-PSFs and indirect costs, but only if the importance and severity of every individual R-PSFs is considered. We expect our findings to aid the relevant stakeholders on their efforts to make better decisions on improving safety performance of railway operations.

  • 49.
    Stenström, Christer
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Eriksson, Kjell
    Luleå tekniska universitet, Institutionen för teknikvetenskap och matematik, Material- och solidmekanik.
    The J-contour integral in peridynamics via displacements2019Ingår i: International Journal of Fracture, ISSN 0376-9429, E-ISSN 1573-2673, Vol. 216, nr 2, s. 173-183Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Peridynamics is a nonlocal formulation of solid mechanics capable of unguided modelling of crack initiation, propagation and fracture. Peridynamics is based upon integral equations, thereby avoiding spatial derivatives, which are not defined at discontinuities, such as crack surfaces. Rice’s J-contour integral is a firmly established expression in classic continuum solid mechanics, used as a fracture characterizing parameter for both linear and nonlinear elastic materials. A corresponding nonlocal J-integral has previously been derived for peridynamic modelling, which is based on the calculation of a set of displacement derivatives and force interactions associated with the contour of the integral. In this paper, we present an alternative calculation of the classical linear elastic J-integral for use in peridynamics, by writing Rice’s J-integral as a function entirely of displacement derivatives. The accuracy of the proposed J-integral on displacement formulation is investigated by applying it to the exact analytical displacement solution of an infinite specimen with a central crack and comparing the exact analytical expression of its J-integral. Further comparison with a well-known peridynamic crack problem shows very good agreement. The suggested method is computationally efficient and further allows testing of the accuracy of a peridynamic model as such.

  • 50.