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Soltanali, H., Rohani, A., Tabasizadeh, M., Hossein Abbaspour-Fard, M. & Parida, A. (2019). Operational reliability evaluation-based maintenance planning for automotive production line. Quality Technology & Quantitative Management
Open this publication in new window or tab >>Operational reliability evaluation-based maintenance planning for automotive production line
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2019 (English)In: Quality Technology & Quantitative Management, ISSN 1684-3703, E-ISSN 1811-4857Article in journal (Refereed) Epub ahead of print
Abstract [en]

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

Place, publisher, year, edition, pages
Taylor & Francis, 2019
Keywords
Automotive industry, reliability, maintenance interval, Monte Carlo simulation, statistical structure
National Category
Reliability and Maintenance Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-72679 (URN)10.1080/16843703.2019.1567664 (DOI)
Available from: 2019-01-25 Created: 2019-01-25 Last updated: 2019-01-30
Soltanali, H., Garmabaki, A. S., Thaduri, A., Parida, A., Kumar, U. & Rohani, A. (2019). Sustainable production process: An application of reliability, availability, and maintainability methodologies in automotive manufacturing. Journal of Risk and Reliability, 233(4), 682-697
Open this publication in new window or tab >>Sustainable production process: An application of reliability, availability, and maintainability methodologies in automotive manufacturing
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2019 (English)In: Journal of Risk and Reliability, ISSN 1748-006X, E-ISSN 1748-0078, Vol. 233, no 4, p. 682-697Article in journal (Refereed) Published
Abstract [en]

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

Place, publisher, year, edition, pages
Sage Publications, 2019
Keywords
Automotive manufacturing, conveying process, opportunistic maintenance, reliability, availability, and maintainability methodologies, multi-attribute utility theory
National Category
Reliability and Maintenance Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-72427 (URN)10.1177/1748006X18818266 (DOI)000478598600015 ()2-s2.0-85059945405 (Scopus ID)
Note

Validerad;2019;Nivå 2;2019-08-28 (johcin)

Available from: 2019-01-02 Created: 2019-01-02 Last updated: 2019-08-28Bibliographically approved
Parida, A. & Tretten, P. (2017). Condition Monitoring and Diagnosis of Modern Dynamic Complex Systems using Criticality aspect of Key Performance Indicators. International Journal of COMADEM, 20(1), 35-39
Open this publication in new window or tab >>Condition Monitoring and Diagnosis of Modern Dynamic Complex Systems using Criticality aspect of Key Performance Indicators
2017 (English)In: International Journal of COMADEM, ISSN 1363-7681, Vol. 20, no 1, p. 35-39Article in journal (Refereed) Published
Abstract [en]

Proactive condition monitoring, diagnosis and prognosis of modern complex engineering systems are becoming an increasingly challenging issue. This is mainly attributed to the dynamic global scenario and the ever increasing stakeholders conflicting interests. One of the most important missing links that is often given a low priority while assessing the health of a complex dynamic system is the key criticality of the system in question. This paper discusses some of the challenging issues facing the Asset Management personnel and highlights the importance of incorporating criticality aspect of the key performance indicator in the diagnosis and prognosis of all modern complex systems.

Place, publisher, year, edition, pages
Birmingham, UK: COMADEM International, 2017
Keywords
Asset Management, Condition Monitoring, Key Performance Indicators, diagnosis, prognosis
National Category
Reliability and Maintenance Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-67466 (URN)2-s2.0-85048751238 (Scopus ID)
Available from: 2018-02-02 Created: 2018-02-02 Last updated: 2019-09-13Bibliographically approved
Parida, A., Karim, R. & Thaduri, A. (2017). Guest Editorial. Journal of Quality in Maintenance Engineering, 23(3), 258-259
Open this publication in new window or tab >>Guest Editorial
2017 (English)In: Journal of Quality in Maintenance Engineering, ISSN 1355-2511, E-ISSN 1758-7832, Vol. 23, no 3, p. 258-259Article in journal, Editorial material (Other academic) Published
Place, publisher, year, edition, pages
Emerald Group Publishing Limited, 2017
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-65111 (URN)10.1108/JQME-05-2017-0039 (DOI)2-s2.0-85027990510 (Scopus ID)
Available from: 2017-08-15 Created: 2017-08-15 Last updated: 2017-11-24Bibliographically approved
Gupta, S., Gupta, P. & Parida, A. (2017). Modeling lean maintenance metric using incidence matrix approach. International Journal of Systems Assurance Engineering and Management, 8(4), 799-816
Open this publication in new window or tab >>Modeling lean maintenance metric using incidence matrix approach
2017 (English)In: International Journal of Systems Assurance Engineering and Management, ISSN 0975-6809, E-ISSN 0976-4348, Vol. 8, no 4, p. 799-816Article in journal (Refereed) Published
Abstract [en]

Lean Maintenance (LM) enhances organizational profitability by identifying and eliminating maintenance related wastes. There exists no singular metric that measures maintenance related wastes. The paper identifies the LM features and models them using incidence-matrix. LM features are represented by diagonal elements, while its off-diagonal elements represent mutual influences among the LM features. The maintenance system leanness is quantified using the permanent of the matrix. The metric of leanness is proposed to be defined as Lean maintenance index (LMI) and is a ratio of the actual to the ideal values of permanent of actual and ideal maintenance system matrices. A high value of LMI indicates that the maintenance system is operating in a reduced waste scenario with respect to its resources. Among all the LM features, LMI was found to be most sensitive to management support including organizational processes. The results of the methodology are a good guide for managers. The shortcoming of the methodology is that, it relies on values and weights of the inter-relations among the features, which may not be necessarily true and may need further scientific rigor. The proposed methodology of using LMI as a singular metric to judge maintenance efficacy is expected to aid the operation managers in quantifying the maintenance leanness and may help them focus their efforts appropriately. There is no evidence to indicate existence of comprehensive list of LM features that culminate into a singular metric of maintenance productivity. This paper attempts to fill this gap.

Place, publisher, year, edition, pages
Springer, 2017
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-66365 (URN)10.1007/s13198-017-0671-z (DOI)000414521800011 ()2-s2.0-85032805201 (Scopus ID)
Note

Validerad;2017;Nivå 2;2017-11-07 (rokbeg)

Available from: 2017-11-02 Created: 2017-11-02 Last updated: 2018-11-23Bibliographically approved
Stenström, C., Xin, T. & Parida, A. (2016). A rapid method for estimating the prevented train delays as an effect of rail infrastructure inspections. In: F. Chen, X.P. Cai, L.J. Wang and L. Gao (Ed.), The Infrastructure Construction and Maintenance of High-speed Railway and Urban Rail Transit in Complex Environment: . Paper presented at 4th International Conference on Railway Engineering, ICRE2016, Beijing, China (pp. 51-55). China Railway Publishing House
Open this publication in new window or tab >>A rapid method for estimating the prevented train delays as an effect of rail infrastructure inspections
2016 (English)In: The Infrastructure Construction and Maintenance of High-speed Railway and Urban Rail Transit in Complex Environment / [ed] F. Chen, X.P. Cai, L.J. Wang and L. Gao, China Railway Publishing House , 2016, p. 51-55Conference paper, Published paper (Other academic)
Abstract [en]

In this study, a formula is described for calculating the relationship between preventive maintenance inspections and train delays for rail infrastructure. The reduction in train delays due to preventive maintenance has been calculated as follows: When an inspection is performed, the probability to find a potential failure is between 0 and 100 %. The potential failure is registered as an inspection remark. The risk that the potential failure will degrade to a functional failure within a certain time is also between 0 and 100 %. Strictly speaking, this time is equal to the specified maximum time to restoration in the inspection remark registration, e.g. within one week, but in practice longer. As an example, one can assume 100 inspections, with 10 % probability to find a potential failure, 75 % risk for functional failure if an action is not taken within a near future and 25 % risk for train delays. This gives 100 · 0.1 · 0.75 · 0.25 = 1.875 prevented train-delaying functional failures, and therefore 1.875 times the average number of train delay minutes in reduced minutes of train delays.

 

A case study was carried out to verify the proposed method. The prevented train-delay minutes per maintenance inspection for various rail infrastructure systems were found to be between 0-40 minutes per inspection. However, the result depends to a large extent on the definition of inspection within the maintenance database. The result also depends on the type of inspection, e.g. safety or maintenance inspections. Moreover, the result depends greatly on the criteria that are being used for specifying the risk that a potential failure will degrade to a functional failure within a certain time period. These factors need to be clear before actions are taken upon the results.

Place, publisher, year, edition, pages
China Railway Publishing House, 2016
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-62115 (URN)978-7-113-22023-5 (ISBN)
Conference
4th International Conference on Railway Engineering, ICRE2016, Beijing, China
Available from: 2017-02-22 Created: 2017-02-22 Last updated: 2017-11-24Bibliographically approved
Parida, A. & Stenström, C. (2016). Asset performance evaluation: A recipe for success or failure. In: Proceedings for the COMADEM 2016: . Paper presented at 29th International Congress on Condition Monitoring and Diagnostic Engineering Management, Xi'an, China, 20-22 August 2016.
Open this publication in new window or tab >>Asset performance evaluation: A recipe for success or failure
2016 (English)In: Proceedings for the COMADEM 2016, 2016Conference paper, Published paper (Refereed)
Abstract [en]

Abstract.The prevailing economicdownturn, looming global recession, vola-tile energy and asset prices with emerging technology for prescriptive analytics and increasing budgetary cuts have compelled the companies to manage its en-gineering assets competitively for survival and growth. As per international standard ISO 55001:2014, performance evaluation is fundamental to asset man-agement system (AMS). Asset maintenance performance measurement and management (AMPM) is a recognized process and best practice for supporting sustainability and return on investment.It is hard for an organization to improve the present level of performance of the engineering assets without measurement. Therefore, all functions including units and processes of the organization need to be built and developed as per as-set management principles, such as; ISO 55000 series standard. The challenges in AMPM are to prepare a strategic road map from top management level to the operational level through a link and effect model for identifying and developing key performance indicators (KPI). These KPIs are broken down to measures which are used for monitoring and controlling the unplanned downtime with in-creased reliability, availability, maintainability and safety. Other challenges are to define and develop methods for right data collection through condition moni-toring and big data analytics, beside management for knowledge management. eMaintenance is required for remote data collection, storage, analysis and deci-sion making. The KPIs and indicators will be used for developingcomposite indicators (CI) for bench marking the performance with the best in the industry, besides verifying the return on investment.The author has discussed the various compulsions and challenges associated with asset performance evaluation (APE) for AMPM for the organization. Once the AMPM fundamentals and recipe is known, its success or failure will depend on finding solutions for the challenges while defining, structuring, developing, and implementing AMPM system.

National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-62051 (URN)
Conference
29th International Congress on Condition Monitoring and Diagnostic Engineering Management, Xi'an, China, 20-22 August 2016
Available from: 2017-02-16 Created: 2017-02-16 Last updated: 2017-11-24Bibliographically approved
Norrbin, P., Lin, J. & Parida, A. (2016). Energy efficiency optimization for railway switches & crossings: a case study in Sweden (ed.). Paper presented at World Congress of Railway Research : 29/05/2016 - 02/06/2016. Paper presented at World Congress of Railway Research : 29/05/2016 - 02/06/2016.
Open this publication in new window or tab >>Energy efficiency optimization for railway switches & crossings: a case study in Sweden
2016 (English)Conference paper, Oral presentation only (Refereed)
National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-37249 (URN)b3987a25-04e1-4ebd-bb24-869f79896376 (Local ID)b3987a25-04e1-4ebd-bb24-869f79896376 (Archive number)b3987a25-04e1-4ebd-bb24-869f79896376 (OAI)
Conference
World Congress of Railway Research : 29/05/2016 - 02/06/2016
Note
Godkänd; 2016; 20160523 (pernor)Available from: 2016-10-03 Created: 2016-10-03 Last updated: 2017-11-25Bibliographically approved
Norrbin, P., Lin, J. & Parida, A. (2016). Infrastructure robustness for railway systems (ed.). International Journal of Performability Engineering, 12(3), 249-264, Article ID 5.
Open this publication in new window or tab >>Infrastructure robustness for railway systems
2016 (English)In: International Journal of Performability Engineering, ISSN 0973-1318, Vol. 12, no 3, p. 249-264, article id 5Article in journal (Refereed) Published
Abstract [en]

In the railway industry, most maintenance approaches are based on certain “specified conditions”, e.g., RAMS (Reliability, Availability, Maintainability and Safety) and Risk. But the reality is more complex. Instead of the assumed conditions, “unfavorable conditions” may occur from either natural or operational causes, where robustness can be an effective approach. To adequately consider “unfavorable conditions” and to reduce “uncertainties” in railway maintenance, this study conducts a holistic examination of railway infrastructure robustness. It gives an overview of robustness and discusses some relevant studies. It then develops a new road map for railway infrastructure robustness, including a novel definition and a new framework of robustness management, based on continuous improvement. It explores the opportunities of applying the road map to the infrastructure of railway systems and outlines some practical concerns and remaining challenges for future research. The results provide guidelines for other research into robust infrastructure in railway maintenance.

National Category
Other Civil Engineering
Research subject
Operation and Maintenance; Sustainable transportation (AERI)
Identifiers
urn:nbn:se:ltu:diva-9983 (URN)2-s2.0-84991508605 (Scopus ID)8b91769d-0e85-47cb-9bc1-f8984a825597 (Local ID)8b91769d-0e85-47cb-9bc1-f8984a825597 (Archive number)8b91769d-0e85-47cb-9bc1-f8984a825597 (OAI)
Note

Validerad; 2016; Nivå 1; 20160523 (pernor)

Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-10-02Bibliographically approved
Stenström, C., Parida, A. & Kumar, U. (2016). Measuring and Monitoring Operational Availability of Rail Infrastructure (ed.). Paper presented at . Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit, 230(5), 1457-1468
Open this publication in new window or tab >>Measuring and Monitoring Operational Availability of Rail Infrastructure
2016 (English)In: Proceedings of the Institution of mechanical engineers. Part F, journal of rail and rapid transit, ISSN 0954-4097, E-ISSN 2041-3017, Vol. 230, no 5, p. 1457-1468Article in journal (Refereed) Published
Abstract [en]

In reliability and maintenance engineering, availability can be described as the ability of an item to be in a state to perform a required function at a given time. Availability is commonly given as a measure between zero and one, where one means the probability of an item to be available for use at a given time is 100%. Availability is measured in many areas, such as electronics, information technologies, military equipment, electrical grids and the industry. Various indicators related to availability of railways have been examined by academia and industry. However, there is some ambiguity about how to define and measure the availability of rail infrastructure, given railways' semi-continuous operation, besides data quality issues. This article considers the application of common definitions of availability to rail infrastructure. It includes a case study comparing various approaches for measuring availability. The case study ends with a section on how availability as a function of train frequency and maintenance time can be simulated. The results show rail infrastructure availability correlates well with train delay, but this depends on how infrastructure failure data and outliers are treated.Keywords: availability, reliability, dependability, maintenance engineering, railways, linear assets, condition monitoring

National Category
Other Civil Engineering
Research subject
Operation and Maintenance
Identifiers
urn:nbn:se:ltu:diva-5795 (URN)10.1177/0954409715592189 (DOI)000378687300006 ()2-s2.0-84973661587 (Scopus ID)3fb59d24-7b2e-4b4e-9a45-f54f4905e11b (Local ID)3fb59d24-7b2e-4b4e-9a45-f54f4905e11b (Archive number)3fb59d24-7b2e-4b4e-9a45-f54f4905e11b (OAI)
Projects
Link and effect model application through life cycle cost and return of investment analysis
Note
Validerad; 2016; Nivå 2; 20160512 (chrste)Available from: 2016-09-29 Created: 2016-09-29 Last updated: 2018-07-10Bibliographically approved
Organisations
Identifiers
ORCID iD: ORCID iD iconorcid.org/0000-0002-7474-2723

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