Development of sustainable manufacturing decision making models for small and medium enterprises / Sujit Singh
Sustainable manufacturing aims to manage the operations in an environmentally and socially responsible manner. Several organizations have already incorporated the concept of sustainable manufacturing. However, many Small and Medium Enterprises (SMEs) that account for approximately 90% of all ente...
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| Format: | Thesis |
| Published: |
2016
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| Subjects: | |
| Online Access: | http://studentsrepo.um.edu.my/6575/4/sujit.pdf http://studentsrepo.um.edu.my/6575/ |
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| Summary: | Sustainable manufacturing aims to manage the operations in an environmentally and
socially responsible manner. Several organizations have already incorporated the
concept of sustainable manufacturing. However, many Small and Medium Enterprises
(SMEs) that account for approximately 90% of all enterprises are not yet embraced this
opportunity. Therefore, it is important to develop the sustainable manufacturing
decision making models that suited to the characteristics of manufacturing SMEs. In
order to achieve that, this study aims to identify key sustainable manufacturing
performance measures & metrics and develop the sustainability evaluation and strategy
selection models.
This study includes an empirical study to identify the key performance measures for
sustainability assessment of manufacturing SMEs in an effective and comprehensive
manner using the Triple Bottom-Line framework. In order to investigate the importance
and applicability of the proposed measures and metrics, a survey was conducted among
the practitioners. The result of Mann-Whitney U-test confirms that there is no
significant difference between the importance and applicability of the proposed
measures. Considering the human reasoning based decision-making in manufacturing
SMEs,the development of decision-making models are based on the fuzzy set theory.
This study also develops two sustainability performance evaluation models and one
strategy selection model. For performance evaluation, the list of sustainability
performance measures and metrics that is identified during the empirical study is
applied. Consequently, a sensitivity analysis of the proposed method reveals the most
important basic indicators affecting overall sustainability, identifying areas which
decision makers should place special attention. For strategy selection model, the study
develops a hierarchal multi-criteria decision making (MCDM) method by combining
iv
Analytical Hierarchal Process (AHP) and VlseKriterijuska Optimizacija I
Komoromisno Resenje (VIKOR) methods under interval-valued fuzzy environment.
The linguistic variables were expressed in the triangular interval-valued fuzzy sets.
Using a case study of manufacturing SME, the final ranking of the strategies was
elicited in accordance with this procedure. Subsequently, a sensitivity analysis was
performed to validate the stability of the proposed final ranking. Apart from above
mentioned studies, this study also includes the development of a fuzzy rule based expert
system to provide an easy to access, time-saving and cost-effective way for
sustainability evaluation and strategy selection. The expert system has two components:
(1) sustainability evaluation and (2) strategy selection. The measures that are found
important during sustainability evaluation process are considered as selection criteria for
strategy selection. The applicability of the models and expert system were validated by
implementation in manufacturing SMEs.
This study contributes in several ways to the research field of sustainable
manufacturing decision making. It provides a list of key performance measures and
metrics for sustainability evaluation of manufacturing SMEs. In conjunction with the
sustainability evaluation models and strategy selection model, this study assists the
decision maker for improving their sustainability performances. An easy to access
expert system provides a time saving, cost effective way for sustainable manufacturing
decision making. The list of key performance measures & metrics, various modelling
approaches and an expert system should also enrich the literature. |
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