Title: Quality improvement of multistage and multi-response grinding processes: an insight into two different methodologies for parameter optimisation
Authors: Indrajit Mukherjee, Pradip Kumar Ray
Addresses: Sailesh J. Mehta School of Management, Indian Institute of Technology, Bombay, Mumbai 400076, India. ' Department of Industrial Engineering and Management, Indian Institute of Technology Kharagpur, Kharagpur 721 302, West Bengal, India
Abstract: Process quality improvement using appropriate optimisation methodology has been a continual research endeavour. However, search for optimal path conditions for multi-stage and multi-response grinding in mass-scale manufacturing still remains a critical and difficult task for researchers. In this context, two different methodologies may be adopted to determine optimal process setting conditions. The first methodology (Methodology-1) is to assume each stage as independent, and thereby determine optimal setting conditions for the individual stages. Based on individual stage optimal process conditions, overall optimal path conditions are selected. Another possible methodology (Methodology-2) for optimisation is to consider all the stages as a single system, with their interdependency, and thereby determine the overall optimal path conditions. In this paper, an attempt has been made to compare and contrast the solution quality, as determined by genetic algorithm, and tabu search for both the methodology. The computational results show the relative superiority of tabu search.
Keywords: multi-stage grinding; multi-response grinding; genetic algorithm; GA; tabu search; quality improvement; parameter optimisation.
International Journal of Productivity and Quality Management, 2009 Vol.4 No.5/6, pp.613 - 643
Published online: 16 May 2009 *Full-text access for editors Full-text access for subscribers Purchase this article Comment on this article