The purpose of this paper is to develop the methodology which can facilitate the concept of reconfiguration in the manufacturing system.
Design methodology includes the calculation of similarity matrix, formation of part family, and selection of part family. ALC algorithm has been used for part family formation and three criteria have been considered for the selection of part family. These criteria are reconfiguration effort, under-utilization cost, and floor space cost. AHP has been used to calculate the weights of criteria and reference ideal method has been used for the selection of alternatives.
In the manufacturing system, machines should be grouped on the basis of reconfiguration cost. When the time period is less, light machines and Group 1 machines are added and removed. In the case study, the concept of reconfiguration is useful for families (A, B, C, D). Machines can be reused by adding/removing some modules of machines. The concept of reconfiguration becomes more useful when it is implemented with lean manufacturing. Lean manufacturing techniques Jidoka and Poka-yoke are used to increase the diagnosability of the system.
Industrial case study has been considered.
Market competition is increasing rapidly and it increases the demand and variety of products, due to which manufacturing enterprises are forced to adapt a manufacturing system which can adjust its capacity and functionality quickly at low cost. To reconfigure manufacturing system from one product/product family to another product/product family, changes can be done in hardware and/or software components in response to sudden changes in the market or in regulatory requirements.
An integrated approach for reconfiguration has been proposed considering the industrial application. It includes weighted Jaccard function, ALCA, AHP, RIM. The methodology for calculation of reconfiguration effort, under-utilization cost, and floor space cost has been presented for industrial case.
Prasad, D. and Jayswal, S. (2019), "Assessment of a reconfigurable manufacturing system", Benchmarking: An International Journal, Vol. ahead-of-print No. ahead-of-print. https://doi.org/10.1108/BIJ-06-2018-0147Download as .RIS
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