An integrated decision support framework for the adoption of lean, agile and green practices in product life cycle stages.
PhD Thesis
Authors | Udokporo, C. |
---|---|
Type | PhD Thesis |
Abstract | In order to stay competitive in today’s overly competitive market place, businesses must be engineered to match product characteristics and customer requirements. This increased emphasis on achieving highly adaptive manufacturing with reduction in manufacturing costs, better utilization of manufacturing resources and sound environmental management practices force organisations to adopt efficient management practices in their manufacturing operations. Some of the established practices in this context belong to the Lean, Agility and Green (LAG) paradigms. Adopting these practices in order to address customer requirements may require some level of expertise and understanding of the contribution (or lack of it) of the practices in meeting those requirements. Primarily, the wide choice of LAG practices available to address customer requirements can be confusing and/or challenging for those with limited knowledge of LAG practices and their efficacy. There is currently no systematic methodology available for selecting appropriate LAG practices considering of the product life cycle (PLC). Therefore, this research provides a novel framework for selecting appropriate LAG practices based on PLC stages for reducing costs, lead time and generated waste. The methodology describes the application of analytic hierarchy process (AHP), statistical inference and regression analysis as decision support tools, ensuring a systematic approach to the analysis with appropriate performance measures. The data collected were analysed with the aid of SPSS and Excel using a variety of statistical methods. The framework was verified through a Delphi study and validated using a case study. The key findings of the research include the various contributions of lean, agile and green practices towards improving performance measures, the importance of green in improving performance measures and the importance of selecting appropriate practices based on product life cycle stages. This research makes a clear contribution to existing body of knowledge by providing a methodological framework which could serve as a guide for companies in the FMCG industry to systematically integrate and adopt lean, agile and green to better manage their processes and meet customer requirements in their organisations. However, the framework developed in this research has not been tested in other areas. |
Keywords | Analytic hierarchy process.; Agile manufacturing; Product life cycle; Lean manufacturing; Green manufacturing |
Year | 2017 |
Publisher | University of Derby |
Digital Object Identifier (DOI) | https://doi.org/10.48773/939qw |
Web address (URL) | hdl:10545/622017 |
File | License File Access Level Open |
File | File Access Level Open |
Output status | Unpublished |
Publication process dates | |
Deposited | 18 Dec 2017, 16:20 |
Publication dates | 15 Nov 2017 |
Contributors | University of Derby |
https://repository.derby.ac.uk/item/939qw/an-integrated-decision-support-framework-for-the-adoption-of-lean-agile-and-green-practices-in-product-life-cycle-stages
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