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Multi-criteria Decision Model for Spare Parts Stocking for Manufacturing Industries

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Original date: 
Friday, April 22, 2022
Abstract: 

Reliability and Maintenance (R&M) teams at manufacturing facilities employ different maintenance strategies on their physical assets to achieve the desired reliability and maximize the availability of the assets. Most of the production downtime in manufacturing facilities is because of unexpected (or) random failures of equipment and the associated reactive maintenance work. One of the factors that affects the total time to fix failed equipment is spare parts availability. The increasing complexity to minimize production downtime with aging assets demands problem-specific decision models. In this study, a multi-criteria decision model is proposed to assist the R&M stakeholders at manufacturing facilities in making decisions on stocking the right parts. The proposed model will help facilities to stock the spare parts required to maintain the system with-in acceptable and manageable risk. Two case studies from a pulp mill will be presented to demonstrate the use of the proposed decision model. The first case study deals with “Pulp Machine Process Area” with historical data on equipment failures and spare parts usage while the second one focuses on a newly commissioned plant without failure information. The proposed decision model helped to identify the right parts to stock and minimized the risk and inventory costs in both cases.

BoK Content Source: 
MainTrain 2022
BoK Content Type: 
Presentation Slides
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Presentation Paper
Asset Management Framework Subject: 
03 Lifecycle Delivery, 3.05 Maintenance Delivery, 4.00 Asset Information General, 4.02 Asset Information Standards, 4.03 Asset Information Systems
Maintenance Management Framework Subject: 
05 Maintenance & Reliability Engineering, 5.4 Critical Spares & Redundancy Analysis, 08 Material Resource Mgmt, 8.1 Materials Management, 8.2 Inventory Management, 9.0 Information Management General, 9.3 Master Data Management
Author Title: 
Reliability Specialist
Author Employer: 
Hinton Pulp a division of West Fraser Mills Ltd.
Author Bio: 

Sathishkumar is a young, diligent, and industrious team player who always loves to work in a challenging work environment, with positive attitude. Sathishkumar is currently working as a Reliability Specialist at Hinton Pulp, A Division of West Fraser Mills Ltd. He is currently leading the Machine Task Force team at Hinton Pulp with an objective to improve the reliability of the Pulp Machine by establishing an optimal and comprehensive reliability and maintenance program. Sathishkumar obtained a Bachelor of Engineering degree in Mechanical Engineering in India and a Master of Science degree in Engineering Management at the University of Alberta, Canada. Sathishkumar worked as a "Research Assistant" at the Reliability Research Lab of University of Alberta, under the supervision of Prof. Dr. Ming Zuo, who is a global leader in Physical Asset Management, Reliability and Maintenance research. Sathishkumar developed prime knowledge in physical asset management, reliability, and maintenance through his time at the Reliability Research Lab, University of Alberta. Sathishkumar worked with Dr. Ming Zuo and has published his research work in reliability and maintenance areas in highly reputed journals and conferences. Sathishkumar gained expertise in ISO 55000, asset management strategy, methods, models, through his Asset Management summer school in Zhejiang University, China. Sathishkumar worked with the Asset Management department of EPCOR Utilities Inc. on multiple reliability and asset management roles and then joined Hinton Pulp, West Fraser Timber Co.Ltd. as a Reliability Specialist. Sathishkumar holds multiple professional credentials namely "Certified Maintenance and Reliability Professional" (CMRP), PMI Certified Associate in Project Management (CAPM) and “IAM Certification in Asset Management”.