A Lean Six Sigma framework for the reduction of ship loading commercial time in the iron ore pelletising industry

Jose Arturo Garza-Reyes, Mustafa Al-Balushi, Jiju Antony, Vikas Kumar

    Research output: Contribution to journalArticle

    29 Citations (Scopus)

    Abstract

    Evidence suggests that specifically designed frameworks to implement Lean Six Sigma (LSS) projects to tackle particular problems are more effective than ‘generic’ versions. This paper proposes an implementation framework to effectively deploy LSS to improve a key operation and performance indicator, i.e. ship loading commercial time, of one of the largest world producer of iron ore. This article therefore contributes with a refined framework to effectively implement LSS, and documents its successful application and effectiveness within the context of the case organisation. The LSS framework and project contributed in helping the studied organisation to improve both the capability of its ship loading process and commercial time by more than 30%, resulting in operational savings in the range of $300,000 USD per year. The systematic nature of the framework proposed also helped the organisation to establish a standardised routine to improve its operations. Managerial implications exposing the challenges faced during the implementation of LSS are also discussed to serve as lessons learnt to be considered in other LSS projects. Managers and engineers incharge of improving operations and processes can benefit from this paper as it can be used as a guide to direct the conduction of LSS projects and the empirical application of its principles and tools.

    Original languageEnglish
    Pages (from-to)1092-1111
    Number of pages20
    JournalProduction Planning and Control
    Volume27
    Issue number13
    Early online date15 May 2016
    DOIs
    Publication statusPublished - 2016

    Keywords

    • DMAIC
    • iron ore industry
    • lean
    • Lean Six Sigma
    • operations improvement
    • Six Sigma

    ASJC Scopus subject areas

    • Industrial and Manufacturing Engineering
    • Computer Science Applications
    • Strategy and Management
    • Management Science and Operations Research

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