Integration of Industry 4.0 technologies into Lean Six Sigma DMAIC: a systematic review

Tanawadee Pongboonchai-Empl, Jiju Antony, Jose Arturo Garza-Reyes, Tim Komkowski, Guilherme Luz Tortorella

    Research output: Contribution to journalArticlepeer-review

    25 Scopus citations

    Abstract

    This review examines which Industry 4.0 (I4.0) technologies are suitable for improving Lean Six Sigma (LSS) tasks and the benefits of integrating these technologies into improvement projects. Also, it explores existing integration frameworks and discusses their relevance. A quantitative analysis of 692 papers and an in-depth analysis of 41 papers revealed that ‘Analyze’ is by far the best-supported DMAICs phase through techniques, such as Data Mining, Machine Learning, Big Data Analytics, Internet of Things, and Process Mining. This paper also proposes a DMAIC 4.0 framework based on multiple technologies. The mapping of I4.0 related techniques to DMAIC phases and tools is a novelty compared to previous studies regarding the diversity of digital technologies applied. LSS practitioners facing the challenges of increasing complexity and data volumes can benefit from understanding how I4.0 technology can support their DMAIC projects and which of the suggested approaches they can adopt for their context.

    Original languageBritish English
    JournalProduction Planning and Control
    DOIs
    StateAccepted/In press - 2023

    Keywords

    • Big Data Analytics
    • data science
    • DMAIC 4.0
    • Industry 4.0
    • Lean Six Sigma

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