Supplier selection process at a South African clothing company
- Chiromo, F., Nel, A., Binda, N.D.
- Authors: Chiromo, F. , Nel, A. , Binda, N.D.
- Date: 2015-06-08
- Subjects: Supplier selection , Clothing trade - South Africa
- Type: Article
- Identifier: uj:5110 , ISBN 978-1-77592-111-0 , http://hdl.handle.net/10210/13936
- Description: This is a case study that investigates a supplier selection process at a South African clothing manufacturing company, hereafter referred to as Brand Solutions. Brand Solutions is a supplier of a wide range of custom-made corporate clothing, headwear, promotional clothing, bags and luggage. The company has in-house knitting mill that makes fabric using mercerised, bamboo, polyester and 100% cotton yarn that is sourced locally and abroad. Brand Solutions also does branding through digital transfer printing, embroidery, digital ultra violet light printing, silkscreen printing and laser engraving. Data for this study was collected by a University of Johannesburg Industrial Engineering Student. The student had interviews with the procurement, production and quality assurance managers. She verified the answers given by the interviewees by taking informative tours of the production floor, warehouse and management offices of the plant. A review of company documents and relevant literature from journals was also done. The research revealed that on new suppliers, Brand Solutions selects them based on the quality, material shrinkage, colour fastness, grammage, cost, delivery lead time, and product mix flexibility. Once the suppliers pass this test, their performance is not reviewed again. These findings have implications on the performance and competitiveness of Brand Solutions. Moreover the findings have a bearing on Brand Solutions’ growth in employment, market share and revenue. Lastly, the study contributes by suggesting the supplier selection model that a clothing manufacturing entity should adopt in relation to the environment that it operates in.
- Full Text: false
- Authors: Chiromo, F. , Nel, A. , Binda, N.D.
- Date: 2015-06-08
- Subjects: Supplier selection , Clothing trade - South Africa
- Type: Article
- Identifier: uj:5110 , ISBN 978-1-77592-111-0 , http://hdl.handle.net/10210/13936
- Description: This is a case study that investigates a supplier selection process at a South African clothing manufacturing company, hereafter referred to as Brand Solutions. Brand Solutions is a supplier of a wide range of custom-made corporate clothing, headwear, promotional clothing, bags and luggage. The company has in-house knitting mill that makes fabric using mercerised, bamboo, polyester and 100% cotton yarn that is sourced locally and abroad. Brand Solutions also does branding through digital transfer printing, embroidery, digital ultra violet light printing, silkscreen printing and laser engraving. Data for this study was collected by a University of Johannesburg Industrial Engineering Student. The student had interviews with the procurement, production and quality assurance managers. She verified the answers given by the interviewees by taking informative tours of the production floor, warehouse and management offices of the plant. A review of company documents and relevant literature from journals was also done. The research revealed that on new suppliers, Brand Solutions selects them based on the quality, material shrinkage, colour fastness, grammage, cost, delivery lead time, and product mix flexibility. Once the suppliers pass this test, their performance is not reviewed again. These findings have implications on the performance and competitiveness of Brand Solutions. Moreover the findings have a bearing on Brand Solutions’ growth in employment, market share and revenue. Lastly, the study contributes by suggesting the supplier selection model that a clothing manufacturing entity should adopt in relation to the environment that it operates in.
- Full Text: false
Sustainable supplier selection in a paint manufacturing company using hybrid meta-heuristic algorithm
- Machesa, M. G. K., Tartibu, L. K., Okwu, M. O.
- Authors: Machesa, M. G. K. , Tartibu, L. K. , Okwu, M. O.
- Date: 2020
- Subjects: Supplier selection , Hybrid Algorithm , ANFIS
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/460016 , uj:40919 , Citation: Machesa, M.G.K., Tartibu, L.K. & Okwu, M.O. 2020. Sustainable supplier selection in a paint manufacturing company using hybrid meta-heuristic algorithm.
- Description: Abstract: Supplier selection in a manufacturing system is highly complex due to the stochastic nature and structure of organizations, thereby necessitating a paradigm shift from the rule of thumb and classical methods of supplier selection to a reliable technique, using the hybrid algorithm to provide higher accuracy in the selection process. Hence, this study proposes the use of hybrid computational intelligence technique, Adaptive Neuro-Fuzzy Inference Systems (ANFIS) for effective prediction and sustainable selection of suppliers (SSS). This hybrid modelling configuration was applied in a paint manufacturing company to select the best possible supplier. Information obtained from the company within the period of investigation was fed into the model. The result obtained shows a faster and reliable prediction of the creative model. Professionals and business managers will benefit greatly from SSS in an in-bound and out-bound supply chain system.
- Full Text:
- Authors: Machesa, M. G. K. , Tartibu, L. K. , Okwu, M. O.
- Date: 2020
- Subjects: Supplier selection , Hybrid Algorithm , ANFIS
- Language: English
- Type: Article
- Identifier: http://hdl.handle.net/10210/460016 , uj:40919 , Citation: Machesa, M.G.K., Tartibu, L.K. & Okwu, M.O. 2020. Sustainable supplier selection in a paint manufacturing company using hybrid meta-heuristic algorithm.
- Description: Abstract: Supplier selection in a manufacturing system is highly complex due to the stochastic nature and structure of organizations, thereby necessitating a paradigm shift from the rule of thumb and classical methods of supplier selection to a reliable technique, using the hybrid algorithm to provide higher accuracy in the selection process. Hence, this study proposes the use of hybrid computational intelligence technique, Adaptive Neuro-Fuzzy Inference Systems (ANFIS) for effective prediction and sustainable selection of suppliers (SSS). This hybrid modelling configuration was applied in a paint manufacturing company to select the best possible supplier. Information obtained from the company within the period of investigation was fed into the model. The result obtained shows a faster and reliable prediction of the creative model. Professionals and business managers will benefit greatly from SSS in an in-bound and out-bound supply chain system.
- Full Text:
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