Optimisation design of attribute control charts for multi-station manufacturing system subjected to quality shifts

Abstract

The qualities of products are a major concern in any production system; thus implementing efficient inspection policies is of great importance to reduce quality-related costs. This article addresses the problem of finding optimal inspection policies for the multi-station manufacturing system (MMS) subjected to quality shifts to minimise total quality-related cost. Each station of the MMS may stay at either in-control condition or out-of-control condition, which may lead to different nonconforming product rates. Markov chain method is used to calculate the steady-state probability distribution (SSPD). Based on the SSPD, the cost structure of this MMS is analysed. The economical optimisation model of attribute control charts (ACCs) is then established, in which the decision variables are the control chart parameters: sampling interval, sample size and control limit. The ACCs optimisation model is resolved by the proposed integrated algorithm combining heuristic rule and tabu search. This approach is verified through an application case taken from a mobile phone shell production company. The results of comparative analysis show that the proposed model is much more economical than both the current outgoing inspection strategy and the regular np control chart. The sensitivity analysis of four input parameters is also conducted.

Keywords:

• multi-station manufacturing system
• attribute control chart
• inspection policy
• Markov chain method
• tabu search

Disclosure statement

No potential conflict of interest was reported by the authors.

Additional information

Funding

This work the supported by the National Natural Science Foundation of China (NSFC) [grant number 51275191]; Fundamental Research Funds for the Central Universities of HUST [grant number 2014TS033].