Int. J. Simul. Multidisci. Des. Optim.
Volume 13, 2022
Advances in Modeling and Optimization of Manufacturing Processes
|Number of page(s)||9|
|Published online||15 March 2022|
Selection of raw material supplier for cold-rolled mild steel manufacturing industry
School of Mechanical and Civil Engineering, MIT Academy of Engineering, Alandi, Pune 412105, India
* e-mail: email@example.com
Accepted: 11 February 2022
Appropriate supplier selection is important in success of every manufacturing industry. Improper supplier selection causes an adverse impact on functioning and development of any organization. Evaluating available suppliers and selecting most suitable supplier is very important task of procurement management. Theses selection problems can be solve using decision making methods. These methods are used to find most preferred alternative from given set of alternatives based on different attributes. The aim of the present work is to select raw material supplier for cold-rolled mild steel manufacturing industry using selected three decision making methods such as complex proportional assessment, operational competiveness rating analysis and preference selection index, etc. The selection is made among five suppliers based on five attributes viz: performance rating, productivity, yield, cost and lead time. The analytical hhierarchy process is used for determining weight of the attributes based on relative importance of each attribute which can have a great impact on the final solution. It is found from the ranks obtained using selected three methods that supplier S1 is best and supplier S5 is worst among the others alternatives. It is also observed that the rankings of suppliers has some deviations in the rankings due to different mathematical approaches used in these three selected methods. The proposed methods help to evaluate and rank different raw material suppliers for manufacturing industries.
Key words: Decision making methods / complex proportional assessment / operational competiveness rating analysis / preference selection index
© A.G. Kamble et al., Published by EDP Sciences, 2022
This is an Open Access article distributed under the terms of the Creative Commons Attribution License (https://creativecommons.org/licenses/by/4.0), which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited.
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