Implementation of total productive maintenance: A case study

Tung Sun Chan, H. C.W. Lau, R. W.L. Ip, H. K. Chan, S. Kong

Research output: Journal article publicationJournal articleAcademic researchpeer-review

222 Citations (Scopus)

Abstract

The semiconductor industry has gone through significant changes in the last decade. Competition has increased dramatically. Customers focus on product quality, product delivery time and cost of product. Because of these, a company should introduce a quality system to improve and increase both quality and productivity continuously. Total productive maintenance (TPM) is a methodology that aims to increase the availability of existing equipment hence reducing the need for further capital investment. Investment in human resources can further result in better hardware utilisation, higher product quality and reduced labour costs. The aim of the paper is to study the effectiveness and implementation of the TPM programme for an electronics manufacturing company. Through a case study of implementing TPM in an electronics manufacturing company, the practical aspects within and beyond basic TPM theory, difficulties in the adoption of TPM and the problems encountered during the implementation are discussed and analysed. Moreover, the critical success factors for achieving TPM are also included based on the practical results gained from the study. After the implementation of TPM model machine, both tangible and intangible benefits are shown to be obtained for equipment and employees respectively. The productivity of the model machine increased by 83%.
Original languageEnglish
Pages (from-to)71-94
Number of pages24
JournalInternational Journal of Production Economics
Volume95
Issue number1
DOIs
Publication statusPublished - 28 Jan 2005

Keywords

  • Autonomous maintenance
  • Continuous improvement
  • Kaizen
  • Performance measurement
  • Total productive maintenance

ASJC Scopus subject areas

  • Business, Management and Accounting(all)
  • Economics and Econometrics
  • Management Science and Operations Research
  • Industrial and Manufacturing Engineering

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