System parameter selection with information axiom for the new product introduction to the hybrid manufacturing systems under dual-resource constraint

Abstract

New part introduction is an important topic because customer expectations expanded and a large variety of parts must be produced by the production systems. Therefore, effect of new parts to the system performance at the operational level should be analysed in order to verify that the new parts can be processed within the cells using the current capacity of machines and workers or to identify if there will be any inter-cell flow due to new parts. In the current study, a methodology that incorporates both simulation methodology and Information Axiom of Axiomatic Design (AD) to identify the best system parameter levels is developed. The structural properties of a manufacturing system will be investigated with simulation technique to observe system performance metrics. Then based on observations, information content of each scenario is calculated and the best scenario with the most suitable parameter levels is selected. To indicate applicability of the methodology, a real hybrid manufacturing system where new parts are introduced is modelled for different levels of system parameters including different setup levels, numbers of workers and lot size, using the simulation technique and different scenarios are populated. The performance of the system for each scenario is observed using the simulation models. Then, based on the Information Axiom of Axiomatic Design total information content is calculated for each scenario, the best scenario that represents the most suitable system parameters is determined. Integration of simulation and Information Axiom of AD makes a distinction from other new product introduction studies.

Keywords:

• new part introduction
• hybrid manufacturing system
• cellular manufacturing system
• simulation modelling
• Information Axiom
• Axiomatic Design (AD)