Autonomous maintenance preparation system design with axioms


Muftuoglu S., Çevikcan E., Durmusoglu B.

JOURNAL OF QUALITY IN MAINTENANCE ENGINEERING, 2022 (ESCI) identifier identifier

  • Publication Type: Article / Article
  • Publication Date: 2022
  • Doi Number: 10.1108/jqme-01-2021-0007
  • Journal Name: JOURNAL OF QUALITY IN MAINTENANCE ENGINEERING
  • Journal Indexes: Emerging Sources Citation Index (ESCI), Scopus, Academic Search Premier, ABI/INFORM, Aerospace Database, Communication Abstracts, Compendex, INSPEC, Metadex, Civil Engineering Abstracts
  • Keywords: Total productive maintenance, TPM implementation initiatives, System design, Training, Lean manufacturing, TOTAL PRODUCTIVE MAINTENANCE, TPM, IMPROVEMENT, MANAGEMENT
  • Istanbul Technical University Affiliated: Yes

Abstract

Purpose The purpose of this paper is to support total productive maintenance implementers by providing a roadmap for autonomous maintenance (AM) preparation phase. Design/methodology/approach The authors use the axiomatic design (AD) methodology with lean philosophy as a paradigm. Findings This is an exploratory research to find the most important factors in AM preparation phase. A decoupled AD design ensures an effective usage of training within industry (TWI) and the introduction of standardized work (SW). TWI provides value in importance it assigns to leaders, with its "train the trainers" approach and in preparing a training program. Besides being an effective training method, TWI job instruction (TWI JI) provides needed information infrastructure to front load operators SW and equipment trainings. Research limitations/implications Although AD, TWI and lean artifacts are generally field proven, the research is limited due to the lack of an industrial application. Practical implications In many real-life projects, companies do not know where to start and how to proceed, which leads to costly iterations. The proposed roadmap minimizes iterations and increases the chance of project success. Originality/value The authors apply AD for the first time to AM preparation phase despite it is used in the analysis of lean manufacturing. AD permits to structure holistically the most relevant lean manufacturing solutions to obtain a risk free roadmap. TWI has emerged as a training infrastructure; TWI JI-based operator SW training and the adaptation of JI structure to equipment training are original additions.