A number of current manufacturing sectors are striving hard to introduce innovative long-term strategies into their operations. As a result, many scholarly studies have found it fruitful to investigate advanced manufacturing strategies such as agile, computer-integrated, and cellular manufacturing. Through the example of downstream cases, manufacturing sectors have learned that financial benefits garnered through automated technologies cannot be counted on as a sole measure to ensure their success in today's competitive and fluctuating marketplaces. The objective of this study is to integrate those advanced techniques with sustainable operations, to promote advanced sustainable manufacturing so those manufacturing sectors can thrive even in uncertain markets. To establish this connection, this study analyzes the drivers of advanced sustainable manufacturing through a proposed framework validated through a case study in India. Common drivers are collected from the literature, calibrated with opinions from experts, and analyzed through an analytical hierarchy process (AHP), which is a multi-criteria decision making (MCDM) approach. This study reveals that quality is the primary driver that pressures manufacturing sectors to adopt advanced sustainable manufacturing. Manufacturers can easily note the top ranked driver and adopt it to soundly implement advanced sustainable manufacturing. In addition, some key future scopes are explored along with possible recommendations for effective implementation of advanced sustainable manufacturing systems.


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    Title :

    Analyzing the Drivers of Advanced Sustainable Manufacturing System Using AHP Approach


    Contributors:

    Publication date :

    2016-01-01


    Remarks:

    Shankar , M , Kumar , P U & Kannan , D 2016 , ' Analyzing the Drivers of Advanced Sustainable Manufacturing System Using AHP Approach ' , Sustainability , vol. 8 , no. 8 , 824 . https://doi.org/10.3390/su8080824



    Type of media :

    Article (Journal)


    Type of material :

    Electronic Resource


    Language :

    English



    Classification :

    DDC:    629



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