Design of closed‐loop supply chain and product recovery management for fast‐moving consumer goods

2010 ◽  
Vol 22 (2) ◽  
pp. 232-246 ◽  
Author(s):  
David B. Grant ◽  
Ruth Banomyong
2013 ◽  
Vol 694-697 ◽  
pp. 3484-3487 ◽  
Author(s):  
Shou Wen Ji ◽  
Zhao Zhao Yu ◽  
Zhi Hua Zhang ◽  
Yang Hua Gao

The paper summarizes the characters of fast moving consumer goods supply chain and establishes the double-closed-loop quality model of fast moving consumer goods supply chain which consists of the level of various enterprises and enterprise internal operation. At last, the paper modeling quality house of raw materials procurement, goods production and processing, goods storage and transportation.


Author(s):  
Madhu Bala ◽  
Dinesh Kumar

This research paper identifies the supply chain performance attributes that are relevant to the Fast Moving Consumer Goods (FMCG) industry. The FMCG supply chains are analysed from the perspective of processes, components and typology. The typical issues faced by the FMCG supply chains are also explored. Three supply chain operational models are compared and identify SCOR as the one best suited for the FMCG industry. The survey, conducted with the respondents from four research cases across two product categories, demonstrates the acceptance and the usage of the performance attributes for the FMCG supply chains. The results also include the analysis of the typology of the research cases across two product categories.


2017 ◽  
Vol 10 (6) ◽  
pp. 19
Author(s):  
Anthony Vaz ◽  
Shaheen Mansori

In a bid to maximize corporate profits, many multi-national corporations and even small medium enterprises create many products and place them on shelves at hypermarkets or supermarkets. We can observe an abundance of stock keeping units on shelves as well as observe a variety of such finished goods held by various fast moving consumer goods industries in the home appliance, beverage, canned food, clothes, soft-drinks, cordials and  confectionery product ranges, just to name a few. From supplier, manufacturer, distributor, wholesaler and retailer, it appears that there is a constant flow of new products and stock keeping units held for these fast moving consumer goods. We can say that we humans are a rather wasteful species because a large proportion of products become obsolete or slow moving over time and organizations push products into the marketplace to gain competitive advantage and optimize profits. Hence, there is need to address this issue in the field of Supply Chain Management because resources on this planet are limited and we humans live in a very fragile planet. Yet, as population grows, we humans have become used to this over-abundance even though the resources within this planet are becoming more and more scarce. Consumption levels have increased with population growth and with capitalist thinking, virtually anybody can develop businesses that will create products to meet human needs. In the field of Supply Chain Management, managers set polices on when to order and how much to order and the average inventory that results from these inventory replenishment policies become targets. This paper attempts to compare target days of inventory with actual days of inventory held in warehouses for a single organization with many warehouses/ stock keeping units, in an attempt to understand further approaches that can be used to improve inventory waste within supply chains.


2021 ◽  
Vol 6 (2) ◽  
pp. 121-130
Author(s):  
Shahul Hamid Khan ◽  
Vivek Kumar Chouhan ◽  
Santhosh Srinivasan

Product recovery has become significant business strategies to increase a competitive edge in business and also in the society. Parts from discarded products due to rapid advancement and post-consumer products before & after end-of-life (EOL) are recovered to reduce landfill waste and to have become a part of circular economy. Product recovery is made possible with the help of Closed-loop supply chain (CLSC). This paper concentrates on multi-period, multi-product, and multi-echelon Closed Loop Green Supply Chain (CLGSC) network. A bi-objective (cost and emission) Mixed Integer Linear Programming (MILP) model has been formulated for the network and has been optimized using Goal Programming approach and Genetic Algorithm. Results are discussed for providing some managerial insights of the model.


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