Composite performance metric for product flow configuration selection of reconfigurable manufacturing system (RMS)

Singh, Prabhjot; Madan, Jatinder; Singh, Harwinder

doi:10.1080/00207543.2020.1756511

Cited by 22 publications

(2 citation statements)

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“…Thus, these problematic products and production system units can be removed to ensure the optimal performance of a manufacturing system. In [4], the authors proposed nine industrially relevant factors to assess the product flow in RMS. A metric was defined, based on these factors, in the form of a composite performance metric.…”

Section: B Diagnostic Of Rmsmentioning

confidence: 99%

“…Few authors have considered the economic aspects of configuration design while ignoring other beneficial aspects such as the diagnostics of configuration design. There is a need to consider several other factors to assess the performance of a reconfigurable manufacturing system [4]. The RMS is still an emerging manufacturing paradigm; hence, it offers much room for improvement and investigation.…”

Section: Introductionmentioning

confidence: 99%

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Problem-Specific Heuristics for Diagnosability and Inventory Analysis in a Reconfigurable Manufacturing System

Khan

2022

IEEE Access

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Reconfigurable manufacturing systems are complex systems that are prone to malfunctions and performance decay. Thus, such systems need to be safeguarded against quality issues and decline in production efficiency to ensure the optimal health of machines. The product quality and health of a reconfigurable manufacturing system can be analyzed by using the diagnosability characteristic. This study examines the diagnosability characteristic in a multi-stage reconfigurable manufacturing system. The aim is to understand the impact of time-based diagnostics on the functionality performance of a reconfigurable manufacturing system and the level of inventory used during production. The diagnosability is analyzed regarding product variation and system diagnosability. A mathematical model is proposed, and it is subsequently applied in deterministic and stochastic settings. The deterministic setting is examined through a set of two problem-specific heuristics. The stochastic setting, subject to the gamma process, is examined by using a simulation-based optimization approach. The results suggest that the use of line replacement units can restore a reconfigurable system to optimal functionality, reduce the level of inventory, and complete production in minimum time at the expense of additional cost. Finally, a conclusion and future research avenues are provided.

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Section: B Diagnostic Of Rmsmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%