A bi-objective robust inspection planning model in a multi-stage serial production system. Issue 4 (16th February 2018)

• Record Type: Journal Article
• Authors: Mohammadi, M.; Dantan, J.-Y.; Siadat, A.; Tavakkoli-Moghaddam, R.
• Is Part Of: International journal of production research. Volume 56:Issue 4(2018)
• Page Start: 1432
• Page End: 1457
• Publication Date: 2018-02-16
• Subjects: multi-stage production system -- conformity inspection -- monitoring inspection -- multi-objective optimisation -- robust optimisation -- differential evolution; Factory management -- Periodicals; 658.57
• DOI: 10.1080/00207543.2017.1363425
• Languages: English
• ISSNs: 0020-7543

Abstract

Abstract : In this paper, we present a bi-objective mixed-integer linear programming (BOMILP) model for planning an inspection process used to detect nonconforming products and malfunctioning processors in a multi-stage serial production system. The model involves two inter-related decisions: (1) which quality characteristics need what kind of inspections (i.e. which - what decision) and (2) when the inspection of these characteristics should be performed (i.e. when decision). These decisions require a trade-off between the cost of manufacturing (i.e. production, inspection and scrap costs) and the customer satisfaction. Due to inevitable variations in manufacturing systems, a global robust BOMILP (RBOMILP) is developed to tackle the inherent uncertainty of the concerned parameters (i.e. production and inspection times, errors type I and II, misadjustment and dispersion of the process). In order to optimally solve the presented RBOMILP model, a meta-heuristic algorithm, namely differential evolution (DE) algorithm, is combined with the Taguchi and Monte Carlo methods. The proposed model and solution algorithm are validated through a real industrial case from a leading automotive industry in France.