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  • 301.
    Galar, Diego
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Peters, Ralph
    Maintenance Excellence Institute.
    Berges, Luis
    Manufacturing Engineering and Advanced Metrology Group, Aragon Institute of Engineering Research (13A), University of Zaragoza.
    Stenström, Christer
    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.
    Composite indicators in asset management2012Konferensbidrag (Refereegranskat)
    Abstract [en]

    Composite indicators are formed when individual indicators are compiled into a single index. A composite indicator should ideally measure multidimensional concepts which cannot be captured by a single index. Since asset management is multidisciplinary, composite indicators would be helpful. The paper describes a method of monitoring a complex entity in a processing plant. In this scenario, a plurality of use indices and weighting values are used to create a composite use index from a combination of lower level use indices and weighting values. Each use index contains status information on one aspect of the lower level entities, and each weighting value corresponds to one lower level entity. The resulting composite indicator can be a decision-making tool for asset managers.Keywords – Indicator, aggregation, KPI, performance, hierarchy, DSS

  • 302.
    Galar, Diego
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Pilar, Lamban
    Manufacturing and Design Engineering Department, University of Zaragoza.
    Luis, Berges
    Manufacturing and Design Engineering Department, University of Zaragoza.
    Application of dynamic benchmarking of rotating machinery for e-maintenance2010Ingår i: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 1, nr 3, s. 246-262Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The vibration analysis and condition monitoring technology is based on comparison of measurements obtained with benchmarks suggested by manufacturers or standards. In this case, the references provided by current rules are static and independent of parameters such as age, operational or environmental conditions in which the machine is analyzed. It creates false alarms and many unnecessary interventions. New communication technologies allow the integration of e-maintenance systems, production and real-time data or the result of vibration routes. The integration of all these data allows data mining and extraction of parameters to be incorporated into decision making typical of CBM, such as repairs, downtime, overhauls, etc. Absolute vibration data and spectral analysis of rotating machinery require the study of several signals by machine, which become hundreds of values and spectra to analyze where there, is a large number of machines. It is therefore necessary to find proper benchmark points to compare with vibration parameters. These parameters and benchmark points have to be adapted to the real status of the plant and vibratory conditions have to be automated to be easily understood by persons not connected with the detailed analysis of spectra. The trend of the measured data and its comparison with benchmarks should assess the success of the implementation of CBM and other decisions about implementation and changes in maintenance programs. This article proposes the use of two new indicators that result from data mining as a reference dynamic, not static as proposed by the standard, manufacturer or the expertise of maintenance technicians. These values show the real condition of the machine in terms of vibration. The application of these references to the decision making process of the maintenance manager and its inclusion in maintenance scorecard avoids unnecessary repairs caused by false alarms and thus prolongs the life of the equipment, resulting in the improvement of parameters such as the MTBF, in a e-maintenance system

  • 303.
    Galar, Diego
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Sandborn, Peter
    University of Maryland.
    Kumar, Uday
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Johansson, Carl-Anders
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    SMART - Integrating human safety risk assessment with asset integrity2013Ingår i: Advances in Condition Monitoring of Machinery in Non-Stationary Operations: Proceedings of the third International Conference on Condition Monitoring of Machinery in Non-Stationary Operations CMMNO 2013 / [ed] Giorgio Dalpiaz; Riccardo Rubini; Gianluca DÉlia; Marco Cocconcelli; Fakher Chaari; Radoslaw Zimroz; Walter Bartelmus; Mohamed Haddar, Encyclopedia of Global Archaeology/Springer Verlag, 2013, s. 37-59Konferensbidrag (Refereegranskat)
    Abstract [en]

    Maintenance activities are commonly organized into scheduled and unsched-uled actions. Scheduled maintenance is undertaken during pre-programmed in-spections. Such maintenance operations try to minimize the risk of deterioration based on a priori knowledge of failure mechanisms and their timing. However, in complex systems it is not always possible to schedule maintenance actions to mit-igate all undesired effects, and SMART systems, which monitor selected parame-ters, propose actions to correct any deviation in normal behavior. Maintenance decisions must be made on the basis of accepted risk. Performed or not performed scheduled tasks as well as deferred corrective actions can have positive or negative consequences for the company, technicians and machines. These three risks should be properly assessed and prioritized as a function of the goals to be achieved. This paper focuses on how best practices in risk assessment for human safety can be successfully transferred to risk assessment for asset integrity.

  • 304.
    Galar, Diego
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Seneviratne, DammikaLuleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Management Systems in Production Engineering: Maintenance Performance Measurement and Management Challenges:  From Sensing to Decision Support2017Samlingsverk (redaktörskap) (Övrigt vetenskapligt)
  • 305.
    Galar, Diego
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Seneviratne, DammikaLuleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    MPMM 2016, Maintenance, Performance, Measurement & Management: conference proceedings2017Proceedings (redaktörskap) (Refereegranskat)
    Abstract [en]

    The maintenance function is inherent to production but its activities are not always understood or quantified. A characteristic of maintenance is that its activity involves more than a group of people or a workshop and goes beyond the limits of a traditional department.

    The scope of maintenance in a manufacturing environment is illustrated by its various definitions. British Standards Institute defines maintenance as a combination of all technical and associated administrative activities required to keep equipment, installations and other physical assets in the desired operating condition or restore them to this condition, some authors indicate that maintenance is about achieving the required asset capabilities within an economic or business context, or consists of the engineering decisions and associated actions necessary and sufficient for the optimization of specified equipment ‘capability’ where capability is the ability to perform a specified function within a range of performance levels that may relate to capacity, rate, quality, safety and responsiveness. However, they all agree that the objective of maintenance is to achieve the agreed-upon output level and operating pattern at minimum resource cost within the constraints of system condition and safety.

    We can summarize the maintenance objectives under the following categories: ensuring asset functions (availability, reliability, product quality etc.); ensuring design life; ensuring asset and environmental safety; ensuring cost effectiveness in maintenance; ensuring efficient use of resources (energy and raw materials). For production equipment, ensuring the system functions as it should is the prime maintenance objective. Maintenance must provide the required reliability, availability, efficiency and capability of production systems. Ensuring system life refers to keeping the equipment in good condition to achieve or prolong its designed life. In this case, cost has to be optimized to achieve the desired plant condition. Asset safety is very important, as failures can have catastrophic consequences. The cost of maintenance has to be minimized while keeping the risks within strict limits and meeting the statutory requirements.

    For a long time, maintenance was carried out by the workers themselves, in a more loosely organized style of maintenance with no haste for the machinery or tools to be operational again. However, things have changed.

    •        First, there is a need for higher asset availability. With scale economies dominating the global map, the demand for products is increasing. However, companies suffer financially from the costs of expansion, purchase of industrial buildings, production equipment, acquisitions of companies in the same sector, and so on. Productive capacities must be kept at a maximum, and organizations are beginning to worry about keeping track of the parameters that may affect the availability of their plants and machinery.

    •        The second concern follows from the first. When organizations begin to optimize their production costs and create cost models attributable to the finished product, they start to question maintenance cost. This function has grown to include assets, personnel etc., consuming a significant percentage of the overall organization budget. Therefore, when companies are establishing policies to streamline costs, the question of the maintenance budget arises, followed by questions about the success of this budget. They start to consider availability and quality parameters.

    A question that has haunted maintenance throughout history now appears: how do we maximize availability at the lowest cost? To answer this question, various methodologies, technologies and batteries of indicators are being developed to observe the impacts of improvements.

  • 306.
    Galar, Diego
    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.
    Parida, Aditya
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Kumar, Rupesh
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Berges, Luis
    University of Zaragoza.
    Human factor in maintenance performance measurement2011Ingår i: IEEE International Conference on Industrial Engineering and Engineering Management (IEEM), Piscataway, NJ: IEEE Communications Society, 2011, s. 1569-1576Konferensbidrag (Refereegranskat)
    Abstract [en]

    The maintenance performance measurement is often faced with a lack in knowledge about the real function of the maintenance department within organizations, and consequently the absence of appropriate targets emanating from the global mission and vision. These facts bring about metrics not adapted to the real needs, which has a strong load of human factor and without a roadmap of the amount of data to be collected, their processing and use in decision making. This article proposes a model where qualitative and quantitative methods are combined in order to complement advantages and disadvantages of them both.

  • 307.
    Galar, Diego
    et al.
    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.
    Catelani, Marcantonio
    Department of Information Engineering, University of Florence.
    Ciani, Lorenzo
    Department of Information Engineering, University of Florence.
    Context awareness for maintenance decision making: A diagnosis and prognosis approach2015Ingår i: Measurement, ISSN 0263-2241, E-ISSN 1873-412X, Vol. 67, s. 137-150Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    All assets necessarily suffer wear and tear during operation. Prognostics can assess the current health of a system and predict its remaining life based on features capturing the gradual degradation of its operational capabilities. Prognostics are critical to improve safety, plan successful work, schedule maintenance, and reduce maintenance costs and down time. Prognosis is a relatively new area but has become an important part of Condition-based Maintenance (CBM) of systems. Broadly stated, prognostic methods are either data-driven, rule based, or model-based. Each approach has advantages and disadvantages; consequently, they are often combined in hybrid applications. A hybrid model can combine some or all model types; thus, more complete information can be gathered, leading to more accurate recognition of the fault state. In this context, it is important to evaluate the consistency and reliability of the measurement data obtained during laboratory testing and the prognostic/diagnostic monitoring of the system under examination.This approach is especially relevant in systems where the maintainer and operator know some of the failure mechanisms with a sufficient amount of data, but the sheer complexity of the assets precludes the development of a complete model-based approach. This paper addresses the process of data aggregation into a contextual awareness hybrid model to get Residual Useful Life (RUL) values within logical confidence intervals so that the life cycle of assets can be managed and optimised.

  • 308.
    Galar, Diego
    et al.
    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.
    Kumar, Uday
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Pascual, Rodrigo
    Pontificia Universidad Católica de Chile.
    SMART maintenance and prescriptive asset management for mining2016Konferensbidrag (Refereegranskat)
    Abstract [en]

    Operation and maintenance (O&M) activities are commonly organized into scheduled and unscheduled actions. Scheduled maintenance is undertaken during pre-programmed inspections. Such maintenance operations try to minimize the risk of deterioration based on a priori knowledge of failure mechanisms and their timing. However, in complex systems it is not always possible to schedule maintenance actions to mitigate all undesired effects, and SMART systems, which monitor selected parameters, propose actions to correct any deviation in normal behaviour. Indeed, SMARTness is one step beyond the prediction of failure time but also a proposition of operation and maintenance profiles in order to fulfill the company goals. Therefore prognosis and RUL estimation become a part of the process in order to achieve prescriptive actions and control the degradation and operational aspects of the asset as per expected demand and customer request. These O&M decisions must be made on the basis of accepted risk. Performed or unperformed scheduled tasks as well as deferred corrective actions can have positive or negative consequences for the company, technicians, and machines. These three risks should be properly assessed and prioritized as a function of the goals to be achieved. This paper focuses on the SMARTness of assets in order to go one step forwards and propose prescriptive O&M decisions based on a self-risk assessment as a trade-off for asset integrity and company goals.

  • 309.
    Galar, Diego
    et al.
    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.
    Simon, Victor
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Catelani, Marcantonio
    Department of Information Engineering, University of Florence.
    Ciani, Lorenzo
    Department of Information Engineering, University of Florence.
    Prognostic Hybrid Modelling from Data Fusion on Machine Tools2016Ingår i: Measurement, ISSN 1536-6367, E-ISSN 1536-6359Artikel i tidskrift (Övrig (populärvetenskap, debatt, mm))
    Abstract [en]

    This paper proposes an enhancement of remaining useful life (RUL) prediction method based on degradation trajectory tracking under the scope of machine tools. The operational condition data of the machine over time provides the potential degradation state at the next estimation iteration step, based on data-driven techniques. The model-based approach is considered as long-term prognostics method assuming that a physical model describing the degradation behaviour is available. Fusing the aforementioned techniques outputs a hybrid model for RUL estimation.

  • 310.
    Galar, Diego
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Villarejo, Roberto
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Johansson, Carl-Anders
    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.
    Berges, Luis
    Zaragoza University (Higher Polytechnic Centre), Division of Design and Production Engineering.
    Hybrid models for PHM deployment techniques in railway2013Ingår i: 10th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies 2013, CM 2013 and MFPT 2013, 2013, Vol. 2, s. 1047-1056Konferensbidrag (Refereegranskat)
    Abstract [en]

    Many railway assets exhibit increasing wear and tear of equipment during operation. Prognostics are viewed as an add-on capability to diagnosis; they assess the current health of a system and predict its remaining life based on features that capture the gradual degradation in the operational capabilities of a system. Prognostics are critical to improve safety, plan successful missions, schedule maintenance, reduce maintenance cost and down time. Unlike fault diagnosis, prognosis is a relatively new area and became an important part of Condition-based Maintenance (CBM) of systems. Currently, there are many prognostic techniques; their usage must be tuned for each application. The prognostic methods can be classified as being associated with one or more of the following two approaches: data-driven and model-based. Each of these approaches has its own advantages and disadvantages, and consequently, they are often used in combination in many applications called hybrid. A hybrid model could combine some or all of model types (data-driven, and phenomenological), so that more complete information allows for more accurate recognition of the fault state. This approach is especially relevant in railway where the maintainer and operator know some of the failure mechanisms, but the complexity of the infrastructure and rolling stock is huge so no way to develop a complete model based approach that is why development of hybrid models becomes necessary to estimate RUL of railway systems in a more accurate way. The paper address this process of data aggregation into the hybrid model in order to get RUL values within logical confidence intervals so railway assets life cycle can be managed and optimized.

  • 311.
    Galar, Diego
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Wandt, Karina
    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.
    Berges, Luis
    Department of Design Engineering and Manufacturing, University of Zaragoza.
    The evolution from e(lectronic)Maintenance to i(ntelligent)Maintenance2012Ingår i: The Ninth International Conference on Condition Monitoring and Machinery Failure Prevention Technologies, 2012, Vol. 1, s. 203-216Konferensbidrag (Refereegranskat)
    Abstract [en]

    iMaintenance stands for integrated, intelligent and immediate maintenance. It integrates various maintenance functions and connects these to all devices, using advanced communication technologies. The main challenge is to integrate the disparate systems and capabilities developed under current eMaintenance models and to make them immediately accessible through intelligent computing technologies. iMaintenance systems are computer-based, able to evolve with the system that they monitor and control, and they can be embedded in the system’s components, providing the ability to integrate new functionality with no downtime. This article will show how iMaintenance systems can provide decision-making support, thereby going beyond merely connecting various maintenance systems.

  • 312.
    Galar, Diego
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Wandt, Karina
    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.
    Berges, Luis
    Department of Design Engineering and Manufacturing, University of Zaragoza.
    The evolution from e(lectronic)Maintenance to i(ntelligent)Maintenance2012Ingår i: Insight (Northampton), ISSN 1354-2575, E-ISSN 1754-4904, Vol. 54, nr 8, s. 446-450Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    iMaintenance stands for integrated, intelligent and immediate maintenance. It integrates various maintenance functions and connects these to all devices using advanced communication technologies. The main challenge is to integrate the disparate systems and capabilities developed under current eMaintenance models and to make them immediately accessible through intelligent computing technologies. iMaintenance systems are computer-based, able to evolve with the system that they monitor and control and they can be embedded in the system's components, providing the ability to integrate new functionality with no downtime. This article will show how iMaintenance systems can provide decision-making support, thereby going beyond merely connecting various maintenance systems.

  • 313.
    Gandhi, Kanika
    et al.
    Bharatiya Vidya Bhavan’s Usha & Lakshmi Mittal Institute of Mangement, Copernicus Lane, K. G. Marg, New Delhi.
    Jha, P.C
    Department of Operational Research, Faculty of Mathematical Sciences, University of Delhi.
    Govindan, Kannan
    Department of Business and Economics, University of Southern Denmark, Odense.
    Galar, Diego
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Three Echelon Supply Chain Design with Supplier Evaluation2014Ingår i: Proceedings of the Third International Conference on Soft Computing for Problem Solving: SocProS 2013 / [ed] Millie Pant; Kusum Deep; Atulya Nagar; Jagdish Chand Bansal, Berlin: Springer-Verlag GmbH , 2014, Vol. 2, s. 867-881Konferensbidrag (Refereegranskat)
    Abstract [en]

    Effective supply chain management (SCM), which facilitates companies to react to changing demand by swiftly communicating those needs to their supplier, is at the root of successful manufacturing. Optimizing a supply chain (SC) performance is a key factor for success in long term SC relationships. Much information like price, delivery time percentage and acceptance percentage are discussed in the process. A factor as imprecise demand is added in the same process that fuzzifies coordination between buyer and supplier. The paper considers nondeterministic conditions in the environment of business, coordination in procurement and distribution in a supplier selection problem that was proposed and a fuzzy model with two objectives was defined. The proposed model is a “fuzzy bi-objective mixed integer nonlinear” problem. A “fuzzy solution and fuzzy goal programming method” is used to convert the model into crisp form and solved using differential evolution

  • 314.
    Gao, Xueli
    et al.
    University of Stavanger.
    Markeset, Tore
    University of Stavanger.
    Kumar, Uday
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    A review of production assurance in the Norwegian petroleum industry2007Ingår i: Proceedings of the 7th International Conference on Reliability, Maintainability and Safety: Beijing, China, August 22 -26, 2007 / [ed] Changhong Gu; Liming Ren; Guowei He, Beijing: China Astronautic Publishing House , 2007, s. 235-240Konferensbidrag (Refereegranskat)
  • 315.
    Garmabaki, Amir
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Project: Design of Fuzzy Programming Software2013Övrigt (Övrig (populärvetenskap, debatt, mm))
  • 316.
    Garmabaki, Amir
    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.
    Ahmadi, Mahdieh
    Department of Industrial Engineering, Mazandaran University of Science and Technology, Babol.
    Maintenance Optimization Using Multi-Attribute Utility Theory2016Ingår i: Current Trends in Reliability, Availability, Maintainability and Safety: An Industry Perspective / [ed] Uday Kumar; Alireza Ahmadi; Ajit Kumar Verma; Prabhakar Varde, Encyclopedia of Global Archaeology/Springer Verlag, 2016, s. 13-25Konferensbidrag (Refereegranskat)
    Abstract [en]

    Several factors such as reliability, availability, and cost may consider in the maintenance modeling. In order to develop an optimal inspection program, it is necessary to consider the simultaneous effect of above factor in the model structure. In addition, for finding the optimal maintenance interval it is necessary to make trade-offs between several factors, which may conflicting each other as well. The study comprises of mathematical formulating an optimal interval problem based on Multi-Attribute Utility Theory (MAUT). The aim of the proposed research is to develop a methodology with supporting tools for determination of optimal inspection in a maintenance planning to assure and preserve a desired level of performance measure such as reliability, availability, risk, etc. For verification and validation purposes, the proposed methodology (analysis approach) and tools (models) will be applied in a real case which given by the literature.

  • 317.
    Garmabaki, Amir
    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.
    Block, Jan
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Pham, Hoang
    Department of Industrial & Systems Engineering, Rutgers University, Piscataway, NJ.
    Kumar, Uday
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    A Reliability Decision Framework for Multiple Repairable Units2016Ingår i: Reliability Engineering & System Safety, ISSN 0951-8320, E-ISSN 1879-0836, Vol. 150, s. 78-88Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    In practice, the analyst is often dealing with multiple repairable units, installed in different positions or functioning under different operating conditions, and maintained by different disciplines. This paper presents a decision framework to identify an appropriate reliability model for massive multiple repairable units. It splits non-homogeneous failure data into homogeneous groups and classifies them based on their failure trends using statistical tests. The framework discusses different scenarios for analysing multiple repairable units, according to trend, intensity, and dependency of the units’ failure data. The proposed framework has been verified in a fleet of aircraft and in two simulated data sets. The results show a reliability model of multiple repairable units may contain a mixture of different stochastic models. Considering single reliability models for such populations may cause erroneous calculation of the time to failure of a particular unit, which can, in turn, lead to faulty conclusions and decisions. When dealing with massive and non-homogeneous multiple repairable units, the application of the proposed framework can facilitate the selection of an appropriate reliability model.

  • 318.
    Garmabaki, Amir
    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.
    Mahdavi, Iraj
    Mazandaran University of Science and Technology, Babol.
    Ahmadi, Mahdieh
    Mazandaran University of Science and Technology, Babol.
    Reliability modeling of open source software based on adoption behavior under stochastic environment2015Ingår i: Safety and reliability of complex engineered systems: proceedings of the 25th European Safety and Reliability Conference, ESREL 2015, Zürich, Switzerland, 7-10 September 2015 / [ed] Luca Podofilini; Bruno Sudret; Božidar Stojadinović; Enrico Zio; Wolfgang Kröger, Boca Raton: CRC Press, 2015, s. 3995-3999Konferensbidrag (Refereegranskat)
    Abstract [en]

    In the current digitalized world, Open Source Software (OSS) methodology provides greater value to users and leads to increased revenue for the OSS companies. This paper investigates reliability modeling for OSS. Most of software reliability models proposed in literature for OSS projects are based on closed-form methodology and do not consider the properties of OSS in the model structure. This paper models the rate of adoption of volunteers to OSS using diffusion theory and considered as fault detection rate. However, the fault detection rate may vary in such a testing environment; a modified SRGM based on Itô type Stochastic Differential Equation (SDE) is proposed to describe realistic situations. The proposed model have been verified on real data sets from open source projects, as the Apache project, which has been released in the market with new features. Results show the proposed model can describe the failure process for open source software accurately.

  • 319.
    Garmabaki, Amir
    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.
    Mahmood, Yasser Ahmed
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Barabadi, Abbas
    Tromsø University.
    Reliability Modelling of Multiple Repairable Units2016Ingår i: Quality and Reliability Engineering International, ISSN 0748-8017, E-ISSN 1099-1638, Vol. 32, nr 7, s. 2329-2343Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    This paper proposes a model selection framework for analysing the failure data of multiple repairable units when they are working in different operational and environmental conditions. The paper provides an approach for splitting the non-homogeneous failure data set into homogeneous groups, based on their failure patterns and statistical trend tests. In addition, when the population includes units with an inadequate amount of failure data, the analysts tend to exclude those units from the analysis. A procedure is presented for modelling the reliability of a multiple repairable units under the influence of such a group to prevent parameter estimation error. We illustrate the implementation of the proposed model by applying it on 12 frequency converters in the Swedish railway system. The results of the case study show that the reliability model of multiple repairable units within a large fleet may consist of a mixture of different stochastic models, i.e. the HPP/RP, TRP, NHPP and BPP. Therefore, relying only on a single model to represent the behaviour of the whole fleet may not be valid and may lead to wrong parameter estimation.

  • 320.
    Garmabaki, Amir
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Barabadi, Abbas
    Tromsø University.
    Fuqing, Yuan
    Tromsø University.
    Lu, J.
    University of Tromsø - The Arctic University of Norway.
    Ayele, Y.Z.
    University of Tromsø - The Arctic University of Norway.
    Reliability modeling of successive release of software using NHPP2015Ingår i: 2015 IEEE International Conference Industrial Engineering and Engineering Management (IEEM): Singapore, 6-9 Dec. 2015, Piscataway, NJ: IEEE Communications Society, 2015, s. 761-766, artikel-id 7385750Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper presents an effective reliability model for multi-release open source software (OSS), which derived based on software lifecycle development process (SDLC) proposed by Jørgensen [1]. Most of OSS reliability models do not consider the unique characteristic of OSS in the model. This model, combine bugs removed from pre-commit test and parallel debugging test phases. Furthermore, the proposed model is based on the assumptions that the total number of fault removal of the new release depends on the reported faults from the previous release and on the faults generated due to adding some new adds-on to the existing software system. The parameters of model have been estimated using three releases of the Apache project. In addition, three models in the literature are selected to compare with the proposed model. Comparison indicates that the proposed model is a suitable reliability model that fits the data across all the releases of the Apache project.

  • 321.
    Garmabaki, Amir
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Birk, Wolfgang
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Lindström, John
    Luleå tekniska universitet, Institutionen för system- och rymdteknik, Signaler och system.
    Software Fault Detection in Control Systems2017Ingår i: Risk, Reliability and Safety: Innovating Theory and Practice - Proceedings of the 26th European Safety and Reliability Conference, ESREL 2016 / [ed] Walls L.,Revie M.,Bedford T, CRC Press, 2017, s. 2006-2012Konferensbidrag (Refereegranskat)
    Abstract [en]

    Fault detection in the software of control systems is a difficult task. In largely interconnected systems, not only the individual performance of one channel, but also its interaction with other components, must be considered. In this conceptual paper, we outline a new maintenance concept for the detection of software faults in control systems. The concept includes two approaches, morning gymnastics test and envelope analysis. The morning gymnastics test generates data for a baseline of the current operational abilities in contrast to the specified abilities and should be applied when feasible in continuous production systems. The test integrates historical and new sets of data to track degradation trends. Envelope analysis can be performed to detect operational anomalies and is based on subsequent deep analysis to distinguish software and hardware faults from each other. By using the envelope analysis it is possible to identify failures and disturbances affecting the control system. Thus, the proposed maintenance concept may facilitate detection and identification of potential failures in critical automated system.

  • 322.
    Garmabaki, Amir
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Seneviratne, Dammika
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Ahmadi, Mahdieh
    Barabadi, Abbas
    Tromsø University.
    Kumar, Uday
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Data driven RUL estimation of rolling stock using intelligent functional test2017Ingår i: Risk, Reliability and Safety: Innovating Theory and Practice - Proceedings of the 26th European Safety and Reliability Conference, ESREL 2016 / [ed] Walls L.,Revie M.,Bedford T, London: CRC Press, 2017, s. 1994-1999Konferensbidrag (Refereegranskat)
    Abstract [en]

    The rolling stock health condition is important for both passenger and freight trains in terms of safety, availability, punctuality and efficiency. Various inspection and maintenance methodologies are per-formed on rolling stock equipment to fulfill the above performance measures. This paper suggests a new approach, namely, intelligent functional test (IFTest) to estimate the remaining useful life (RUL) of the equipment, sub-systems and systems of rolling stock dynamically by data driven methods. IFTest generates a baseline of the current operational abilities in contrast to the required abilities. The test integrates the historical and new set of data to track the trend of degradation of equipment. With this approach, the operation and maintenance personnel have ample time to make decisions for the maintenance and failure consequences. In addition, it is supposed that by using such data we are achieving a more accurate result for the estimation of reliability and RUL of critical rolling stock equipment.

  • 323.
    Garmabaki, Amir Soleimani
    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.
    Block, Jan
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Fleet-level reliability estimation of repairable units2015Ingår i: Safety and Reliability: Methodology and Applications / [ed] Tomasz Nowakowski; Marek Mlynczak; Anna Jodejko-Pietruczuk; Sylwia Werbinska-Wojciechowska, London: CRC Press, 2015, s. 1977-1982Konferensbidrag (Refereegranskat)
    Abstract [en]

    This paper investigates reliability analysis of a repairable unit at fleet level. In fleet, multiple similar systems are running in different operating environments. In fact, due to the highly censored data as well as high variations in failure rate within the fleet, merging the datasets becomes a challenge. The non-parametric analysis is used to capture the failure trend of repairable units at fleet level. Consequently, fleet data have been aggregated and the actual number of failure has been compared with the expected total number of failures. In addition, parametric models are used to model the reliability trend obtained through a non-parametric approach to identify the reliability parameters at fleet level. Real data are used to demonstrate the applicability and validity of the proposed method. Results shows the accuracy of log-linear process is reasonably acceptable.

  • 324.
    Garmabaki, Amir Soleimani
    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.
    Kapur, P.K
    Amity University.
    Kumar, Uday
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Predicting software reliability in a fuzzy field environment2013Ingår i: International Journal of Reliability, Quality and Safety Engineering (IJRQSE), ISSN 0218-5393, Vol. 20, nr 3Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The testing-development phase has been carried out in a given control environment. However, the product will be used in different operating environment by different end-users, which is unknown to the developer. The operating environment may range from a very clean one up to a harsh environment. These uncertain operating environments will impact to the reliability and performance of the software which may differ from the testing phase reliability. We consider that the effect of environment on reliability has a fuzzy nature. The fuzzy effects of the field environments can be captured by a unit-free environmental factor. To overcome this problem, the fuzzy probabilistic theory may be used in the processing of stochastic parameters, taking into account their fuzzy nature. The proposed model is based on Weibull distribution. The aim of this paper is to introduce a fuzzy field environment (FFE) reliability model that covers both the testing and operating phases in the development cycle. Illustration examples of the proposed model have been validated on data collected from two industries. © 2013 World Scientific Publishing Company.

  • 325.
    Garmabaki, Amir Soleimani
    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.
    Kapur, P.K
    Amity University.
    Kumar, Uday
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Predicting software reliability in a fuzzy-random field environment2012Konferensbidrag (Refereegranskat)
    Abstract [en]

    The development of a new complex software or industrial system produces a series of prototypes that may contain faults during the processes, including development, design, and production. Therefore, during the early stages of prototyping complex systems, reliability often faces a major challenge in meeting the desired requirements level. For these reasons, a typical reliability improvement process is carried out in order to achieve a specific software/system reliability level. Incorrect estimation of reliability could lead to an inappropriate system design and implementation of incorrect maintenance policies.Many software reliability models have been proposed to help software developers and managers to assess the level of the reliability and estimation of the development cost. Among these software reliability models, Non-Homogenous Poisson Process (NHPP) based models have been successfully applied to model the software failure processes, and predict the number of software failures. NHPP has been used also to determine “time to stop testing” and release the software.Usually, the testing-development phase has been carried out in a given control environment. However, the product will be used in different operating environment by different end-users, which is unknown to the developer. The operating environment may range from a very clean one up to a harsh environment. These uncertain operating environments will impact to the reliability and performance of the software which may differ from the testing phase reliability. Hence the effect of environmental factors on reliability should be considered for estimation of the operational phase reliability. In fact the effect of environment on reliability has a fuzzy nature and quiet random. On the other hand, it is well known that the probability distribution and its parameters cannot be univocally defined. To overcome this problem, the fuzzy probabilistic theory may be used in the processing of stochastic parameters, taking into account their fuzzy nature. In fact, the fuzzy random effects of the field environments can be captured by a unit-free environmental factor. Based on the fuzzy probability distribution and its properties, we can define a fuzzy reliability function. The aim of this paper is to introduce a Fuzzy random field environment (FRFE) reliability model that covers both the testing and operating phases in the development cycle. The proposed model is based on Weibull distribution. It should be noted that the testing costs is one the major concern in software/system development. Several researcher investigated software/System release policies to minimize development cost while satisfying a reliability objective. Although the length of testing phase directly relates to the number of errors removed, but leads to a significant financial loss by increasing testing cost and delay in delivery. Further, releasing software in the market before reaching its desired level of reliability (which is fixed by the manager) may increase the maintenance cost during operational phase as well as create risk to lose future market.For a critical software system, the penalty costs resulting from the software failures are much more significant than the software development costs themselves. Therefore, the total software/ system cost should consist of not only the development costs, but also the penalty costs resulting from the software failure in operational phase. For software developers and managers, the following questions need to be answered (1) How to allocate the resources to ensure the on-time delivery of a software product? (2) When to stop testing and release the software from current software testing activities? (3) Is the software product really reliable in field? To answer the above mentioned questions, the paper proposes a cost function using proposed FRFE reliability model, to determine the optimal release policies.

  • 326.
    Garmabaki, Amir Soleimani
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Kapur, P.K
    Aggarwal, Anu. G
    Yadavali, V.S.S
    The Impact of Bugs Reported from Operational Phase on Successive Software Releases2014Ingår i: International Journal of Productivity and Quality Management, ISSN 1746-6474, E-ISSN 1746-6482, Vol. 14, nr 4, s. 423-440Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Software testing is a necessary part of software development life cycle (SDLC) to achieve a high reliable software system. In today’s software environment of global competition where each company is trying to prove itself better than its competitors, software companies have to continually do up-gradation or add-ons in their software to survive in the market. Each succeeding up-gradation offers some innovative performance or new functionality, distinguishing itself from the past release. We consider the combined effect of bugs encountered during testing of present release and user reported bug from operational phase. The model developed in the paper takes into consideration the testing and the operational phase where fault removal phenomenon follows Kapur-Garg model and Weibull-model respectively. The model developed is validated on real datasets for software which has been released in the market with new features

  • 327.
    Garmabaki, Amir
    et al.
    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.
    Seneviratne, Dammika
    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.
    Opportunistic inspection planning for Railway eMaintenance2016Ingår i: IFAC-PapersOnLine, ISSN 2405-8963, Vol. 49, nr 28, s. 197-202Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Railway infrastructure is a complex system that comprises of several subsystems which interacts in hierarchical, multi-distributive and multi-user environment. It is a difficult task to perform inspections for all the assets at an instant because the train management system decides when to conduct different types of inspection techniques on several assets in a particular track section. There are two main wastes of resources for inspection planning occurred in maintenance; under usage due to inaccurate prediction of failure and over usage because the necessary information already has been acquired from other sources. These irregularities lead to wastage of resources, for instance, human, machine and time that has tremendous implications on cost, availability and manpower. This paper proposes a methodology by using intelligent functional test outcome to assess the performability of an asset and integrating the data to the eMaintenance cloud platform of Swedish railway infrastructure. By implementing this methodology, we can achieve better planning of resources for optimal performance of assets. A case study is performed on Switches and Crossings of Swedish railway infrastructure for the applicability of the proposed methodology.

  • 328.
    Gerdes, Mike
    et al.
    Department of Automotive and Aeronautical Engineering, HAW Hamburg.
    Galar, Diego
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Fuzzy condition monitoring of recirculation fans and filters2016Ingår i: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 7, nr 4, s. 469-479Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    A reliable condition monitoring is needed to be able to predict faults. Pattern recognition technologies are often used for finding patterns in complex systems. Condition monitoring can also benefit from pattern recognition. Many pattern recognition technologies however only output the classification of the data sample but do not output any information about classes that are also very similar to the input vector. This paper presents a concept for pattern recognition that outputs similarity values for decision trees. Experiments confirmed that the method works and showed good classification results. Different fuzzy functions were evaluated to show how the method can be adapted to different problems. The concept can be used on top of any normal decision tree algorithms and is independent of the learning algorithm. The goal is to have the probabilities of a sample belonging to each class. Performed experiments showed that the concept is reliable and it also works with decision tree forests (which is shown during this paper) to increase the classification accuracy. Overall the presented concept has the same classification accuracy than a normal decision tree but it offers the user more information about how certain the classification is.

  • 329.
    Gerdes, Mike
    et al.
    Department of Automotive and Aeronautical Engineering, HAW Hamburg.
    Galar, Diego
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Scholz, Dieter
    Hamburg University of Applied Sciences, Aero - Aircraft Design and Systems Group.
    Automated parameter optimization for feature extraction for condition monitoring2016Ingår i: 14th IMEKO TC10 Workshop on Technical Diagnostics 2016: New Perspectives in Measurements, Tools and Techniques for Systems Reliability, Maintainability and Safety, Milan, Italy, 27-28 June 2016, 2016, s. 452-457Konferensbidrag (Refereegranskat)
    Abstract [en]

    Pattern recognition and signal analysis can be used to support and simplify the monitoring of complex aircraft systems. For this purpose, information must be extracted from the gathered data in a proper way. The parameters of the signal analysis need to be chosen specifically for the monitored system to get the best pattern recognition accuracy. An optimization process to find a good parameter set for the signal analysis has been developed by the means of global heuristic search and optimization. The computed parameters deliver slightly (one to three percent) better results than the ones found by hand. In addition it is shown that not a full set of data samples is needed. It is also concluded that genetic optimization shows the best performance

  • 330.
    Gerdes, Mike
    et al.
    Department of Automotive and Aeronautical Engineering, HAW Hamburg.
    Galar, Diego
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Scholz, Dieter
    Hamburg University of Applied Sciences, Aero - Aircraft Design and Systems Group.
    Decision trees and the effects of feature extraction parameters for robust sensor network design2017Ingår i: Eksploatacja i Niezawodnosc - Maintenance and Reliability, ISSN 1507-2711, Vol. 19, nr 1, s. 31-42Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Reliable sensors and information are required for reliable condition monitoring. Complex systems are commonly monitored by many sensors for health assessment and operation purposes. When one of the sensors fails, the current state of the system cannot be calculated in same reliable way or the information about the current state will not be complete. Condition monitoring can still be used with an incomplete state, but the results may not represent the true condition of the system. This is especially true if the failed sensor monitors an important system parameter. There are two possibilities to handle sensor failure. One is to make the monitoring more complex by enabling it to work better with incomplete data; the other is to introduce hard or software redundancy. Sensor reliability is a critical part of a system. Not all sensors can be made redundant because of space, cost or environmental constraints. Sensors delivering significant information about the system state need to be redundant, but an error of less important sensors is acceptable. This paper shows how to calculate the significance of the information that a sensor gives about a system by using signal processing and decision trees. It also shows how signal processing parameters influence the classification rate of a decision tree and, thus, the information. Decision trees are used to calculate and order the features based on the information gain of each feature. During the method validation, they are used for failure classification to show the influence of different features on the classification performance. The paper concludes by analysing the results of experiments showing how the method can classify different errors with a 75% probability and how different feature extraction options influence the information gain

  • 331.
    Gerdes, Mike
    et al.
    Department of Automotive and Aeronautical Engineering, HAW Hamburg.
    Galar, Diego
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Scholz, Dieter
    Hamburg University of Applied Sciences, Aero - Aircraft Design and Systems Group.
    Genetic algorithms and decision trees for condition monitoring and prognosis of A320 aircraft air conditioning2017Ingår i: Insight (Northampton), ISSN 1354-2575, E-ISSN 1754-4904, Vol. 59, nr 8, s. 424-433Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Unscheduled maintenance is a large cost driver for airlines, but condition monitoring and prognosis can reduce the number of unscheduled maintenance actions. This paper discusses how condition monitoring can be introduced into most systems by adopting a data-driven approach and using existing data sources. The goal is to forecast the remaining useful life (RUL) of a system based on various sensor inputs. Decision trees are used to learn the characteristics of a system. The data for the decision tree training and classification are processed by a generic parametric signal analysis. To obtain the best classification results for the decision tree, the parameters are optimised by a genetic algorithm. A forest of three different decision trees with different signal analysis parameters is used as a classifier. The proposed method is validated with data from an A320 aircraft from Etihad Airways. Validation shows that condition monitoring can classify the sample data into ten predetermined categories, representing the total useful life (TUL) in 10% steps. This is used to predict the RUL. There are 350 false classifications out of 850 samples. Noise reduction reduces the outliers to nearly zero, making it possible to correctly predict condition. It is also possible to use the classification output to detect a maintenance action in the validation data.

  • 332.
    Gerdes, Mike
    et al.
    Department of Automotive and Aeronautical Engineering, HAW Hamburg.
    Scholz, Dieter
    Department of Automotive and Aeronautical Engineering, HAW Hamburg.
    Galar, Diego
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Effects of condition-based maintenance on costs caused by unscheduled maintenance of aircraft2016Ingår i: Journal of Quality in Maintenance Engineering, ISSN 1355-2511, E-ISSN 1758-7832, Vol. 22, nr 4, s. 394-417Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    PurposeThis paper analyses the effects of condition-based maintenance based on unscheduled maintenance delays that were caused by ATA chapter 21 (air conditioning). The goal is to show the introduction of condition monitoring in aircraft systemsDesign/methodology/approachThe research was done using the Airbus In-Service database to analyse the delay causes, delay length and to check if they are easy to detect via condition monitoring or not. These results were then combined with delay costs.FindingsAnalysis shows that about 80% of the maintenance actions that cause departure delays can be prevented when additional sensors are introduced. With already existing sensors it is possible to avoid about 20% of the delay causing maintenance actions.Research limitations/implicationsThe research is limited on the data of the Airbus In-Service Database and on ATA chapter 21 (air conditioning).Practical implicationsThe research shows that delays can be prevented by using existing sensors in the air-conditioning system for condition monitoring. More delays can be prevented by installing new sensors.Originality/valueThe research focuses on the effect of the air-conditioning system of an aircraft on the delay effects and the impact of condition monitoring on delays

  • 333.
    Ghodrati, Behzad
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Efficient product support: optimum and realistic spare parts forecasting2011Ingår i: Replacement Models with Minimal Repair, London: Encyclopedia of Global Archaeology/Springer Verlag, 2011, s. 225-269Kapitel i bok, del av antologi (Refereegranskat)
  • 334.
    Ghodrati, Behzad
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Enhancement of mining machineries availability through supportability2008Ingår i: MassMin 2008: Proceedings of the 5th International Conference and Exhibition on Mass Mining, Lulea, Sweden 9-11 June 2008 / [ed] Håkan Schunnesson; Erling Nordlund, Luleå: Luleå tekniska universitet, 2008, s. 617-626Konferensbidrag (Refereegranskat)
  • 335.
    Ghodrati, Behzad
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Product support and spare parts considering system reliability and operating environment2003Licentiatavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    The required spare parts planning for a system/machine is an integral part of the product support strategy. The number of required spare parts can be effectively estimated on the basis of the product reliability characteristics. The reliability characteristics of an existing machine/system are influenced not only by the operating time, but also by factors such as the environmental parameters (e.g. dust, humidity, temperature, moisture, etc.), which can degrade or improve the reliability. In the product life cycle, for determining the accurate spare parts needs and for minimizing the machine life cycle cost, consideration of these factors is useful. Identification of the effects of operating environment factors (as covariates) on the reliability may help in the prediction and calculation of the required spare parts for a system under given operating conditions, which constitutes the research problem studied in this thesis. The Proportional Hazard Model (PHM) method is used for estimation of the hazard (failure) rate of components under the effect of covariates. In this research an approach has been developed to forecast and estimate accurately the spare parts requirements and to create rational part ordering strategies. Subsequently, a model considering environmental factors is developed to forecast and estimate the required number of spare parts within a specific period of the product life cycle. This thesis only discusses non- repairable components (changeable/service parts), which must be replaced after failure. In addition, the existing method for calculating the number of spare parts on the basis of the reliability characteristics, without consideration of covariates, is modified to arrive at the optimum spare parts requirement. To test the model, case studies concerning spare parts planning based on the reliability characteristics of parts and with/without considering the operating environment have been carried out. The results show clearly the differences between the consumption patterns for spare parts with and without taking into account the effects of covariates in the estimation. The final discussion treats spare parts logistics and inventory management. In this work an attempt is made to minimize the inventory cost and consequently the product life cycle cost. Two models for ordering, purchasing and storing spare parts are discussed in connection with the inventory management.

  • 336.
    Ghodrati, Behzad
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Product support optimization through monitoring of system operating condition2007Ingår i: Proceedings of Condition Monitoring and Fault Diagnosis / [ed] Mehdi Behzad, Sharif University of Technology , 2007Konferensbidrag (Refereegranskat)
    Abstract [en]

    Product support, which is also referred to after sale service to the product is important for customer because it increases the availability of the product and it assures the expected function of the product in its operational phase. It gets influence by many factors such as - reliability and maintainability characteristics, operating environment of the product. By highlighting these influencing factors in design and manufacturing phases, the product life cycle cost (LCC) can be minimized. One of the important steps in product design is the decision making for design out maintenance (DOM) or designs for maintenance (DFM). The DOM alternative leads to produce high reliable, and vice versa, whereas the DFM assure the similar performance with lower reliability beside support. The forecasting of required product support and spare parts based on both reliability-maintainability characteristics and working condition is one approach for the product LCC minimization. This article describes a method to forecast the spare part requirements based on reliability estimation of the existing product under the influence of the product-operating environment.

  • 337.
    Ghodrati, Behzad
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Reliability and operating environment based spare parts planning2005Doktorsavhandling, sammanläggning (Övrigt vetenskapligt)
    Abstract [en]

    The required spare parts planning for a system/machine is an integral part of the product support strategy. The number of required spare parts can be effectively estimated on the basis of the product reliability characteristics. The reliability characteristics of an existing machine/system are influenced not only by the operating time, but also by factors such as the environmental parameters (e.g. dust, humidity, temperature, moisture, etc.), which can degrade or improve the reliability. In the product life cycle, for determining the accurate spare parts needs and for minimizing the machine life cycle cost, consideration of these factors is useful. Identification of the effects of operating environment factors (as covariates) on the reliability may facilitate more accurate prediction and calculation of the required spare parts for a system under given operating conditions. The Proportional Hazard Model (PHM) method is used for estimation of the hazard (failure) rate of components under the effect of covariates. The existing method for calculating the number of spare parts on the basis of the reliability characteristics, without consideration of covariates, is modified and improved to arrive at the optimum spare parts requirement. In this research an approach has been developed to forecast and estimate accurately the spare parts requirements considering operating environment and to create rational part ordering strategies. Subsequently, two models (exponential and Weibull reliability based) considering environmental factors are developed to forecast and estimate the required number of spare parts within a specific period of the product life cycle. This study only discusses non-repairable components (changeable/service parts), which must be replaced upon failure. To test the models, the data collection and classification was carried out from two mining company in Iran and Sweden and then the case studies concerning spare parts planning based on the reliability characteristics of parts, with/without considering the operating environment were done. The results show clearly the differences between the consumption patterns for spare parts with and without taking into account the effects of covariates (operating environment) in the estimation. The final discussion treats a risk analysis of not considering the system’s working conditions through a non-standard (new) event tree approach in which the organizational states and decisions were included and taken into consideration in the risk analysis. In other words, we used the undesired states instead of barriers in combination with events and consequent changes as a safety function in event tree analysis. The results of this analysis confirm the conclusion of this research that the system’s operating environment should be considered when estimating the required spare parts.

  • 338.
    Ghodrati, Behzad
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Spare parts planning and risk assessment associated with non-considering system operating environment2007Ingår i: 6th IMA International Conference on Modelling in industrial maintenance and reliability: IMAR 2007. Proceedings / [ed] Matthew Carr; Philiph Scarf; Wenbin Wang, Institute of Mathematics and its Applications , 2007, s. 80-90Konferensbidrag (Refereegranskat)
    Abstract [en]

    Spare parts needs - as an issue in the field of product support - are dependent on the technical characteristics of the product, e.g. its reliability and maintainability, and the operating environment in which the product is going to be used (e.g. the temperature, humidity, and the user/operator's skills and capabilities), which constitute covariates. The covariates have a significant influence on the system reliability characteristics and consequently on the system failure and number of required spare parts. Ignoring this factor might cause irretrievable losses in terms of production and ultimately in terms of economy. This was proved by the event tree risk analysis method used in a new and non-standard form in the present paper. It has been found that the percentage of risk associated with not considering the system operating environment in spare parts estimation is relatively high.

  • 339.
    Ghodrati, Behzad
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Weilbull and exponential renewal models in spare parts estimation: a comparison2006Ingår i: International Journal of Pedagogy, Innovation and New Technologies, ISSN 0973-1318, E-ISSN 2392-0092, Vol. 2, nr 2, s. 135-147Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Providing the required spare parts is an important issue of product support, which is important for system/machine utility improvement. Required spare parts estimation can be performed through different approaches, one of the realistic and well-founded spare parts estimation method is based on the system's reliability characteristics and taking into consideration the system operating environment. In this paper we study and compare two renewal models namely exponential and Weibull models (constant versus non-constant failure rate assumptions) used in estimation of spare parts for non-repairable components. We also estimate the differences between the two models and calculate the percentage of error. Furthermore a case study is conducted on the hydraulic system of LHD machines in Kiruna Mine in Sweden to find out which factor has a significant impact on the estimation of the number of required spare parts

  • 340.
    Ghodrati, Behzad
    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.
    Product Support Logistics Based on System Reliability Characteristics and Operating Environment2014Ingår i: IEEE International Conference on Industrial Engineering and Engineering Management: IEEM 2013, Bangkok, Thailand; 10 - 13 December 2013, Piscataway, NJ: IEEE Communications Society, 2014, s. 457-461, artikel-id 6962453Konferensbidrag (Refereegranskat)
    Abstract [en]

    The environmental conditions in which the equipment is to be operated, such as temperature, humidity, dust, operators’ skill, etc, often have considerable influence directly on the product reliability and indirectly on the product supportability characteristics. This paper, after discussing the factors influencing product reliability, describes a method to estimate spare part requirements based on estimation of the actual reliability of a product under the influence of the product-operating environment using a proportional hazard model. In this research only non-repairable components/parts in repairable systems are studied. Results express a considerable difference between considering and ignoring the operating environmental factor on system performance. So, this factor should be seriously considered while dimensioning product support and service delivery performance strategies, since it will have an impact on operation, maintenance and service quality.

  • 341.
    Ghodrati, Behzad
    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.
    Galar, Diego
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Reliability analysis of switches and crossings: a case study in Swedish railway2013Konferensbidrag (Refereegranskat)
    Abstract [en]

    It is reported that switches and crossings (S&C) are one of the subsystems that cause the most delays on Swedish Railways while accounting for at least 13% of maintenance costs [6]. It is the main reason why we chose to base our study on this subsystem.Intelligent data processing allows understanding the real reliability characteristics of the assets to be maintained. The first objective of this research is to determine the S&C reliability characteristics based on field data collection. Because field failure data are typically strongly censored, an especial statistics software package was developed to process field failure data, as commercial packages have not been found satisfactory in that respect. The resulting software, named RDAT® (Reliability Data Analysis Tool) has been relied upon for this study: it is especially adapted to statistical failure data analysis.In the next step the availability of studied switches and crossings is estimated based on the reliability characteristics founded in the first step.

  • 342.
    Ghodrati, Behzad
    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.
    Galar, Diego
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Reliability Analysis of Switches and Crossings: A Case Study in Swedish Railway2017Ingår i: International Journal of Railway Research, ISSN 2361-5376, Vol. 4, nr 1, s. 1-12Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    It is reported that switches and crossings (S&C) are one of the subsystems that cause the most delays on Swedish Railways while accounting for at least 13% of maintenance costs [6]. It is the main reason why we chose to base our study on this subsystem.

    Intelligent data processing allows understanding the real reliability characteristics of the assets to be maintained. The first objective of this research is to determine the S&C reliability characteristics based on field data collection. Because field failure data are typically strongly censored, an especial statistics software package was developed to process field failure data, as commercial packages have not been found satisfactory in that respect. The resulting software, named RDAT® (Reliability Data Analysis Tool) has been relied upon for this study: it is especially adapted to statistical failure data analysis.

    In the next step the availability of studied switches and crossings is estimated based on the reliability characteristics founded in the first step.

  • 343.
    Ghodrati, Behzad
    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.
    Galar, Diego
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Spare parts estimation for machine availability improvement addressing its reliability and operating environment: case study2013Ingår i: International Journal of Reliability, Quality and Safety Engineering (IJRQSE), ISSN 0218-5393, Vol. 20, nr 3Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Industrial operation cost analysis shows that, in general, maintenance represents a significant proportion of the overall operating costs. Therefore, the improvement of maintenance follows the final goal of any company, namely, to maximize profit. This paper studies spare parts availability, an issue of the maintenance process, which is an important way to improve production through increased availability of functional machinery and subsequent minimization of the total production cost. Spare parts estimation based on machine reliability characteristics and operating environment is performed. The study uses an improved statistical-reliability (S-R) approach which incorporates the system/machine operating environment information in systems reliability analysis. For this purpose, two methods of Poisson process and renewal process are introduced and discussed. The renewal process model uses a multiple regression type of analysis based on Cox’s proportional hazards modeling (PHM). The parametric approaches with baseline Weibull hazard functions and time independent covariates are considered, and the influence of operating environment factors on this model is analyzed. The outputs represent a significant difference in the required spare parts estimation when considering or ignoring the influence of the relevant system operating environment. The difference is significant in the sense of spare parts forecasting and inventory management which can enhance the parts and consequently machine availability, leading to economical operation and savings.

  • 344.
    Ghodrati, Behzad
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Akersten, Per-Anders
    Kumar, Uday
    Spare parts estimation and risk assessment conducted at Choghart iron ore mine: a case study2007Ingår i: Journal of Quality in Maintenance Engineering, ISSN 1355-2511, E-ISSN 1758-7832, Vol. 13, nr 4, s. 353-363Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Purpose - Spare parts needs are dependent on the characteristics of the product in question, e.g. its reliability and maintainability, and the characteristics of the environment in which the product is going to be used (e.g. the temperature, humidity, and the user/operator's skills and capabilities), which constitute covariates. The covariates have a significant influence on the system reliability characteristics and consequently on the number of required spare parts. The main objective of this research study is to evaluate the associated risks (i.e. risk of shortage of spare parts) in estimation of the required number of spare parts due to not considering the characteristics of system operating environment. Design/methodology/approach - An event tree is a graphical logic model that identifies and quantifies possible outcomes following an initiating event (non-considering system operating environment in this case) in spare parts planning. In the present research a risk analysis is performed through a new and non-standard event tree analysis. It used an event tree analysis in which the states of organization and managerial decisions took place in risk analysis. Findings - In the present study a modified form of event tree analysis was introduced and implemented. In the new version the undesired states were used instead of barriers in combination with events and consequents changes as a safety function in event tree analysis. The output of the event tree analysis shows that there is a considerable operational risk due to losses (production and economical) associated with the non-consideration of the machine working environment. Practical implications - In the estimation of the accurate amount of support and spare parts needed for any industrial system/machine, it is strongly recommended to take the product operating environment into account. This can be proved by the event tree risk analysis method used in a modified and non-standard form in the present research. The results of risk analysis can help managers in making accurate decisions for product support and spare part needs in the future. Originality/value - Modified event tree analysis is a new approach suggested for visualizing the risk associated with non-considering of system operating environment in required support/spare parts estimation. Visualization of risk in graphics can facilitate correct decision making in spare parts planning.

  • 345.
    Ghodrati, Behzad
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Banjevic, Dragan
    C-MORE Lab, University of Toronto.
    Jardine, Andrew K. S.
    C-MORE Lab, University of Toronto.
    Developing Effective Spare Parts Estimations Results in Improved System Availability2010Ingår i: 2010 proceedings: Annual Reliability and Maintainability Symposium : San Jose, California, USA, 25 - 28 January 2010, Piscataway, NJ: IEEE Communications Society, 2010Konferensbidrag (Refereegranskat)
    Abstract [en]

    Production and manufacturing firms are under great pressure to continuously reduce their production costs in order to stay competitive. Industrial operation cost analysis shows that, in general, maintenance represents a significant proportion of the overall operating cost. For instance, the cost of maintenance in the highly mechanized Kiruna underground iron ore mine in Sweden is 30-50% of the total operating cost. Spare parts availability, an issue of the maintenance process, is studied in this paper. Simply stated, production can be enhanced by the increased availability of functional machinery and the subsequent minimization of the total production cost. Spare parts estimation based on machine reliability characteristics and operating environment is a pragmatic method to improve supportability; it can guarantee non-delay in spare parts logistics which can ultimately improve production output. This study uses an improved statistical-reliability (S-R) approach which incorporates system/machine operating environment information in systems reliability analysis. It selects a multiple regression type of analysis based on Cox’s proportional hazards modeling (PHM). It considers a parametric approach with a baseline Weibull hazard function and time independent covariates and analyzes the influence of operating environment factors on this model. Based on the results of analyses, a mathematical model for spare parts prediction in component level for non-repairable parts is developed and the findings are validated through a case study in the Swedish mining industry. The study finds that the outputs represent a significant difference in the required spare parts estimation when considering the influence of the system operating environment. The difference is significant in the sense of spare parts forecasting and inventory management; this can enhance the availability of parts and consequently of machines resulting in economical operation and cost savings.

  • 346.
    Ghodrati, Behzad
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Banjevic, Dragan
    University of Toronto.
    Jardine, Andrew K.S.
    University of Toronto.
    Optimizing product support (spare parts procurement) strategy by considering system operating environment: A case study2009Ingår i: 13th IFAC Symposium on Information Control Problems in Manufacturing 2009: Moscow, Russia, 3 - 5 June 2009, Red Hook: Curran Associates, Inc., 2009Konferensbidrag (Refereegranskat)
    Abstract [en]

    Existing industrial system / machinery availability depends highly on the form and the level of product support. Product support, which is also referred to as after sale service to the product, is important for the customer as well, because it assures the expected function of the product in its operational phase. Product support is affected by different factors, such as reliability and maintainability characteristics and the operating environment of the product. The forecasting of required product support and spare parts based on these factors is one approach for product life cycle cost optimization along with system availability maximization. This paper describes a method to estimate the spare part requirements based on an estimation of reliability of the existing product under the influence of the product-operating environment. Subsequently, in a case study, the management of the spare parts inventory based on the geographical location and required performance of the product will be addressed.

  • 347.
    Ghodrati, Behzad
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Banjevic, Dragan
    C-MORE Lab, University of Toronto.
    Jardine, Andrew K.S.
    C-MORE Lab, University of Toronto.
    Product support improvement by considering system operating environment: a case study on spare parts procurement2012Ingår i: International Journal of Quality & Reliability Management, ISSN 0265-671X, E-ISSN 1758-6682, Vol. 29, nr 4, s. 436-450Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    The ongoing availability of existing industrial systems/machines depends to a great extent on the form and level of product support. Product support, or the after sale service of a product, is important because it assures the expected function of the product in its operational phase. Product support is affected by a number of factors, including system reliability and maintainability characteristics and the operating environment. The purpose of this paper is to analyze the influence of time independent external factors of industrial systems on product support requirements and spare parts need.

  • 348.
    Ghodrati, Behzad
    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.
    Hoseinie, Hadi
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Railway switches and crossings reliability analysis2016Ingår i: 2016 IEEE International Conference on Industrial Engineering and Engineering Management, 2016, Vol. 2016-December, s. 1412-1416, artikel-id 7798110Konferensbidrag (Refereegranskat)
    Abstract [en]

    Switches and crossings (S&Cs) connect the rail network, guiding trains from one track to another and supporting path crossing. They are critical systems given the frequency of their functional failure and the consequences on the operation, cost and safety of railway transportation. Reliability studies are required to support the transport objective of providing dependable, sustainable and cost effective transportation. The main objective of this study is to assess the reliability characteristics of S&Cs based on field data collection. As field failure data have censored nature, commercial packages have not been satisfactory for processing them; therefore, the study uses a special statistical software package RDAT® (Reliability Data Analysis Tool). The availability of the studied switches and crossings is estimated based on the estimated reliability characteristics. The results show the availability of the S&Cs varies between x and y. This is useful information, as it helps the contractor plan and schedule maintenance. It also helps the asset owner to identify units whose performance is below the desired target and to make replacement decisions.

  • 349.
    Ghodrati, Behzad
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Hamodi, Hussan
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Hoseinie, Hadi
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Environmental friendly manufacturing and support: Issues and challenges2015Konferensbidrag (Refereegranskat)
    Abstract [en]

    Environmentally Conscious Manufacturing and Product Support (ECMPS) is animportant issue driven by concern for the escalating deterioration of the environment.ECMPS involves integrating environmental thinking into the design of a product, theselection of materials, manufacturing processes, delivery and support to consumers, andend-of-life management of the product after its useful life has ended. Both academia andindustry are interested in finding solutions in this newly emerging research area. Relatedresearch is on pollution prevention, remanufacturing, disassembly, life cycle of products,after sale support and material recovery. The aim of this study is emphasizing the productdesign, operation, maintenance and disassembly effects on environment, and how theseissues can be considered in manufacturing phase to minimize the negative environmentalimpact.

  • 350.
    Ghodrati, Behzad
    et al.
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Hoseinie, Hadi
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Garmabaki, Amir
    Luleå tekniska universitet, Institutionen för samhällsbyggnad och naturresurser, Drift, underhåll och akustik.
    Reliability considerations in automated mining systems2015Ingår i: International Journal of Mining, Reclamation and Environment, ISSN 1748-0930, E-ISSN 1748-0949, Vol. 29, nr 5, s. 404-418Artikel i tidskrift (Refereegranskat)
    Abstract [en]

    Automation is the operation of machinery or processes by devices, such as robots and machines, able to make and execute decisions without human intervention. Automation is one of the most attractive research and development areas in mining, as it aims to solve many technical, production and safety problems in current and future mining. This paper studies the structure of automated mining systems from a reliability and failure occurrence perspective. It reviews the main subsystems and related failure modes. Based on field investigation and a literature review, it highlights some critical issues and technical difficulties. Finally, it presents some challenges for future automated mines and offers some related solutions

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