A Hierarchical Analytic Process Framework for Manufacturing System Improvement

Abstract

This paper proposes a hierarchical analytic process framework to facilitate practitioners to determine improvement directions for a manufacturing system efficiently and systematically.  The proposed framework analyzes current state performances of a manufacturing system by applying the knowledge of science of manufacturing systems which describe relationship control factors, performance measures, and improvement objectives. Then, concrete directions for improvements are suggested. The analysis process embeds the concept of diagnostic tree which makes it an easy-to-handle framework. Under the diagnostic tree concept, it decomposes the high-level business goal into successively low-level activities to give more comprehensive areas of improvement.  The proposed framework comprises of three key elements:  Operation Performance Measures (OPMs), Diagnostic tree (D-Tree), and Action guidelines. The OPMs are used in the D-Tree to determine improvement objectives.  Then the Action guidelines suggest how to adjust control factors in a manufacturing system according to each improvement objective.  The proposed diagnostic framework is demonstrated by Promodel simulation of a case study.   The simulation model includes physical resources, flow lines, WIP, and replenishment signals of the case. By following the analytic process in the framework, the performance measures have shown improvements according to action guidelines and the result of improvements meets the requirement of a factory in the case study.