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    Lean assessment in manufacturing industry

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    Abstract,Acknowledgement.pdf (230.6Kb)
    Introduction.pdf (337.4Kb)
    Literature Review.pdf (602.9Kb)
    Methodology.pdf (553.2Kb)
    Results and Discussion.pdf (355.7Kb)
    Conclusion and Recommendation.pdf (240.4Kb)
    Refference and Appendics.pdf (1.712Mb)
    Date
    2016-05
    Author
    Moustapha Mahamat Moussa Adam
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    Abstract
    Manufacturing organizations are under pressure to improve productivity and reduce costs through the realization of lean culture. This paper approaches lean culture and aims to identify and measure the closely related parameters of lean culture and also examines the weight of their contribution to overall lean culture. The methodology approach is a questionnaire survey study was performed in Advanced Composites Manufacturing industries to collect data. The reliability of the survey instrument was pre-tested and an acceptable value of Cronbach’s alpha (a reliability coefficient) was found. The relative weight of various parameters using analytical hierarchy process (AHP). Pearson’s coefficient of correlation analysis was used to measure the strength of the relationships between various parameters of lean culture. The study findings are ‘‘engagement’’ to be the most important parameter of lean culture, followed by ‘‘process centric’’. The survey shows that most of the respondents are having weak knowledge towards the realization of lean culture. Research limitations are; sample size (n = 29). Practical implications of the present study provides guidelines to assess the status of lean culture in the manufacturing industries. According to conclusions, weak areas in the manufacturing system can be identified and a suitable course of action might be planned for the improvement. In this work, the theoretical perspective was used not only to update the original instrument, but also to study the subject from a perspective beyond that usually associated with lean culture.
    URI
    http://dspace.unimap.edu.my:80/xmlui/handle/123456789/69805
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    • School of Manufacturing Engineering (FYP) [338]

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