An application of Taguchi method of experimental design for new product design and development process

Jiju Antony, Daniel Perry, Chengbo Wang, Maneesh Kumar

Research output: Contribution to specialist publicationArticle

59 Scopus citations

Abstract

Purpose - This paper aims to illustrate an application of Taguchi method of experimental design (TMED) for the development of a new ignition coil for an automotive vehicle. Design/methodology/approach - The application of TMED for optimisation of manufacturing processes has been widely published in the existing literature. However, the applications of TMED in the design and development of new products are not yet widely reported. This case study presents the results of a designed experiment which utilises a 16-trial experiment to study 14 design parameters and one interaction. The case study strictly follows a systematic and disciplined methodology outlined in the paper. Findings - The optimal settings of the critical design parameters are determined. The optimal settings have resulted in increased customer satisfaction, improved market share and low defect rate in the hands of customers. Research limitations/implications - Although the optimal levels are determined from one large experiment, it was unable to determine the true optimal values of each design parameter. Practical implications - Manufacturers may use TMED to optimise processes (either design or manufacturing) without expensive and timeconsuming experimentation. This case study demonstrates the true power of a well planned and designed experiment over the traditional varying one-factor-at-a-time approach to experimentation which is rather unreliable, not cost-effective and may lead to false optimal conditions. Originality/value - The paper provides an excellent resource for those people who are involved in the design optimisation of a new product.

Original languageBritish English
Pages18-24
Number of pages7
Volume26
No1
Specialist publicationAssembly Automation
DOIs
StatePublished - 2006

Keywords

  • Analysis of variance
  • Case studies
  • Design management
  • Experimental design
  • Taguchi methods

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