Lz-Transform Method and Markov Reward Approach for Flexible Manufacturing System Performance Evaluation
Source abstract
Abstract
This article presents a performance evaluation of a flexible manufacturing system (FMS), in which the system and its components can have different performance levels ranging from perfect functioning to total failure. An original multistate transition process for the FMS’s main component, Computerized Numerical Control (CNC) machine tools, proposed in the current article and treated as an aging process because of its increasing failure rate is investigated. The Markov reward approach is utilized to analyze the availability of CNC machine tools and sensitivity analysis of each non-operational state to the machine’s downtime. To overcome the “state explosion problem” in the subsequent FMS performance evaluation process, an application of the Lz-transform method is proposed to determine the performance evaluation and availability of such aging multistate FMS. An illustrated case is presented to demonstrate the performance evaluation process. The results show that the suggested methods can be implemented in engineering decision making and construction of various aging multistate FMS related to demands, availability, and output performance.
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Research context
OpenAlex topics: Reliability and Maintenance Optimization · Flexible and Reconfigurable Manufacturing Systems · Product Development and Customization
SciVX discovery tags are terminology-based. OpenAlex topics are source-provided classifications.
Affiliations
Key Laboratory of CNC Equipment Reliability, Ministry of Education, School of Mechanical and Aerospace Engineering, Jilin University, Changchun 130022, China
Center for Reliability and Risk Management, Shamoon College of Engineering, Beer Sheva 84100, Israel
Institute of Energy Conversion Technology, Technical University of Munich (TUM), 80333 Munich, Germany
The Israel Electric Corporation Ltd., Haifa 31000, Israel
Funding
Jilin Provincial Department of Science and Technology Development Project
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