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International Journal of Business Performance Management
International Journal of Business Performance Management


Special Issue on: "Solving Multi Response Problems in the Taguchi Method for Product And Process Performance Improvement"

Guest Editors:
M. Rajmohan, P. Shahabudeen, K. Krishnaiah, Anna University, India
R. Jeyapaul, National Institute of Technology, India

Manufacturing companies around the world are affected by globalisation and are forced to be more competitive day by day to sustain their profitability. The implementation of total quality principles is being considered as one of the strongest indicators of competitiveness of the company. Robust design, which is widely acknowledged as most significant contribution of Taguchi, is an offline quality assurance technique which ensures quality of design of process and products that greatly improves engineering productivity. The Taguchi method of experimental design is a widely accepted approach for robust experimental design that seeks to obtain a best combination set of factors/levels with the lowest societal cost solution to achieve customer requirements.

It is observed that most of the published Taguchi applications have been primarily concerned with the optimisation of a single response. However, in practice, multiple responses are common in complex processes and, in most cases; we generally rely on experience and engineering knowledge of the product/process for optimisation which often increases the degree of uncertainty during the decision-making process.

This special issue aims to provide academia and practitioners with a collection of innovative research and most recent developments in to handling the multi response problems in the Taguchi method for product and process performance improvement.

Subject Coverage
Contributors are encouraged to submit original manuscripts that are conceptual, case studies, or metaheuristic-based, and to focus on the following or other areas related to multi response problem:
  • Engineering judgement
  • Assignment of weight
  • Regression analysis
  • Mathematical programming
  • Response surface methodology
  • Principal component analysis
  • DEAR approach
  • Grey relational analysis
  • Fuzzy logic
  • Fuzzy multiple attribute decision making
  • Neural networks
  • Application of metaheuristics
  • Case studies

Notes for Prospective Authors

Submitted papers should not have been previously published nor be currently under consideration for publication elsewhere

All papers are refereed through a peer review process. A guide for authors, sample copies and other relevant information for submitting papers are available on the Author Guidelines page

Important Dates

Manuscript submission: 31 October 2008

Notification of initial decision: 31 December 2008

Notification of final acceptance: 31 January 2009