The Use of TPM Principles to Measure System Performance

M. Molefe, A. Pradhan

Research output: Chapter in Book/Report/Conference proceedingConference contributionpeer-review

Abstract

Numerous organizations strive to grow and survive due to increasing competition. Managers are constantly developing strategies that assist organizations to become productive while sustaining organizational growth and goal achievement. Organizational goals are accomplished through performing proper maintenance on plant equipment. Total Productive Maintenance (TPM) is a maintenance program which involves concepts for maintaining plants and equipment effectiveness. This study aims to analyze the root cause of breakdowns within a production line and further use of TPM to prevent system breakdowns. Relevant data were collected using questionnaires, observations, interviews, and company records. The study then adopted and implemented a competitive strategy which is a TPM model. Overall Equipment Effectiveness (OEE) is used as a measure of performance. The results obtained highlight that if TPM is appropriately implemented, OEE can increase, providing the organization a competitive advantage.

Original languageEnglish
Title of host publication2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021
PublisherInstitute of Electrical and Electronics Engineers Inc.
Pages1508-1512
Number of pages5
ISBN (Electronic)9781665437714
DOIs
Publication statusPublished - 2021
Event2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021 - Virtual, Online, Singapore
Duration: 13 Dec 202116 Dec 2021

Publication series

Name2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021

Conference

Conference2021 IEEE International Conference on Industrial Engineering and Engineering Management, IEEM 2021
Country/TerritorySingapore
CityVirtual, Online
Period13/12/2116/12/21

Keywords

  • OEE
  • System Performance
  • TPM

ASJC Scopus subject areas

  • Strategy and Management
  • Artificial Intelligence
  • Computer Science Applications
  • Information Systems and Management
  • Industrial and Manufacturing Engineering
  • Control and Optimization

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