An integrated multidimensional process improvement methodology for manufacturing systems

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Abstract

In this paper, an integrated multidimensional process improvement methodology (IMPIM) is formulated to address the yield management, process control and cost management problems of a manufacturing system. Simulation is used as a platform to implement the integrated multidimensional process methodology by incorporating the productivity, quality and cost dimension in a unified, systematic and holistic manner. Total Quality Management (TQM) addresses the quality parameters and Activity-Based Costing is used to manage the cost dimension of the system. Discrete event simulation is then used as a platform to perform process reengineering (Business Process Reengineering) and process improvement (TQM). The general implementation framework of the IMPIM is given with a step-by-step explanation. A conceptual discussion is also provided for the integrated methodology. The generic IMPIM is then formulated and the detailed implementation procedures for two case studies are compared with the generic methodology.

Section snippets

Overview

The explosive production power of the Pacific Rim has led to worldwide over-resourcing and a competitive global marketplace. With the inclusion of China and India, the pressure is on for businesses in the West to improve management processes in order to secure a trading place in the 21st century (Hutchins, 1998). However, global competition and the recent recession have exposed a serious weakness in Asian organisations; namely many organisations had become over-staffed, cumbersome, slow and

Physical layout of the system

The objective of the manufacturing company is to optimise productivity, to minimize cost and to maximise quality. Both case studies presented in this paper were conducted on the assembly system of opto-electronic products in one of the electronic manufacturing companies in Singapore. The existing assembly line layout and the process flow of the assembly operation are shown in Fig. 5.

It is a closed system because the number of the pallets circulated in the system is fixed. Only a p chart

Implementation of IMPIM on case study one

IMPIM can be used to design an optimal control chart configuration with higher, productivity, better process control and lower cost (Spedding & Chan, 2001). The general methodology is proposed in Section 2. A step by step approach with suggestions of specific techniques is given in this section to solve the control chart design problem in a systematic and holistic manner. This step by step approach can be used to determine ‘Where to put a control chart’ and ‘Which type of control chart to use’

Implementation of IMPIM on case study two

IMPIM gives a general approach for obtaining non-disruptive, on-line quality information so that a manufacturing system may be configured to provide optimal performance in terms of quality and productivity at the lowest cost. The technique applies a neural network to ‘learn’ the process control configuration necessary to obtain the optimal quality improvement possible from a system. An important implication here is that the suggested methodology will allow the engineer to determine how much a

Conclusion

Global competition, changing customers' needs, increasing product complexity, volatile economic conditions and higher customer expectation are the changing set of business requirements that causes the need for optimising productivity, improving quality and reducing cost. However, there is no scientific and methodical approach to address the productivity, quality and cost problems in an integrated and a unified manner.

In this paper, an IMPIM is developed to solve the yield management, process

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