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Objective <p>The paper aims to identify the key barriers to lean automation and analyse their interrelationships. Fifteen lean automation barriers of the small-sized pharmaceutical industry have been identified and refined based on a thorough literature review and twenty expert inputs.</p> Method <p>Interpretive Structural Modelling (ISM) and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) analysis was used for the framework and categorisation of barriers into four quadrants. The method for order preference by similarity to the ideal solution (TOPSIS) was then used to prioritise the barriers.</p> Result <p>The results show that high maintenance cost (A2) with performance score (P<sub>i</sub>) = 1, noise and pollution (A5) with performance score (P<sub>i</sub>) = 2 and energy consumption (A4) with performance score (P<sub>i</sub>) = 3 are top-ranked factors that needs more focus from practitioners.</p> Conclusion <p>These findings provide practitioners, managers, and policymakers with a clear understanding to focus more on lean automation barriers and their priorities for selecting the best alternative to ensure the successful implementation of lean automation in the pharmaceutical industry in India.</p>

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Structural Modelling of Lean Automation Barriers: A Hybrid ISM-MICMAC and TOPSIS-Based Approach

  • 期刊论文

  • 发表日期：

    2026年5月27日

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  • Amit Surya,
  • Rakesh Kumar,
  • Rajeev Trehan

摘要

Objective

The paper aims to identify the key barriers to lean automation and analyse their interrelationships. Fifteen lean automation barriers of the small-sized pharmaceutical industry have been identified and refined based on a thorough literature review and twenty expert inputs.

Method

Interpretive Structural Modelling (ISM) and Cross-Impact Matrix Multiplication Applied to Classification (MICMAC) analysis was used for the framework and categorisation of barriers into four quadrants. The method for order preference by similarity to the ideal solution (TOPSIS) was then used to prioritise the barriers.

Result

The results show that high maintenance cost (A2) with performance score (Pi) = 1, noise and pollution (A5) with performance score (Pi) = 2 and energy consumption (A4) with performance score (Pi) = 3 are top-ranked factors that needs more focus from practitioners.

Conclusion

These findings provide practitioners, managers, and policymakers with a clear understanding to focus more on lean automation barriers and their priorities for selecting the best alternative to ensure the successful implementation of lean automation in the pharmaceutical industry in India.