Manufacturing quality improvement and setup cost reduction in a vendor-buyer supply chain model
31 Oct 2017-European Journal of Industrial Engineering (Inderscience Publishers (IEL))-Vol. 11, Iss: 5, pp 588-612
TL;DR: A two-echelon supply chain model with quality improvement of products and setup cost reduction under controllable lead time and the optimal results of decision variables numerically are obtained to minimise the total system cost.
Abstract: Quality improvement and setup cost reduction of any production system are endless procedure. Customer's demand is always intended to have the best quality product and the industries always try to improve the quality of products. This paper develops a two-echelon supply chain model with quality improvement of products and setup cost reduction under controllable lead time. The lead time demand follows a normal distribution and in the second case, it does not consider any specific distribution except a mean and standard deviation. Both models are solved analytically to obtain global solution. Two improved iterative algorithms are developed in order to obtain the optimal results of decision variables numerically to minimise the total system cost. The expected value of additional information is calculated to show the financial effect for collecting the information about lead time demand distribution. Some numerical examples and sensitivity analysis are given to illustrate the model. [Received 8 December 2016; Revised 27 March 2017; Accepted 21 April 2017]
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TL;DR: Numerical study proves that the variable production rate effects a lot on the total cost of supply chain model, which affects the product quality as well as entire supply chain cost under a single-setup multiple-delivery policy.
Abstract: A supply chain with multiple buyers leads to a hike in demand and for satisfying them, a high standard production manufacturing system is required. A predetermined production rate in a supply chain model with economic production lot size is quite inappropriate for this type of situation as production rate can be changed in some cases to fulfill demand of customers. Rate of production has an impact in maintaining process quality. Manufacturing quality deteriorates with an increasing rate of production. In this context, this paper develops a single-vendor multi-buyer supply chain model with variable production rate and imperfect quality of products. The unit production cost is considered as a function of the production rate. Three different production functions are established to relate process quality and production rate. Due to huge demand by multi-buyer, the lead time demand is considered as random variable and it follows a normal distribution. The objective of this study is to analyze how the flexibility of the production rate affects the product quality as well as entire supply chain cost under a single-setup multiple-delivery policy. A classical optimization technique is employed to obtain the global optimum solution. An illustrative algorithm is established to obtain the numerical results. Numerical examples and graphical interpretations, and sensitivity analysis are given to illustrate the model. Numerical study proves that the variable production rate effects a lot on the total cost of supply chain model.
50 citations
TL;DR: A two-echelon supply chain model is formulated to reduce lead time and setup time to obtain their impacts on the expected total cost when lead time demand is stochastic in nature.
Abstract: A two-echelon supply chain model is formulated to reduce lead time and setup time to obtain their impacts on the expected total cost when lead time demand is stochastic in nature. Two different safety factors are utilized to avoid shortages even though the system contains backorder. The lead time is lot size dependent and consists of production time as well as setup time. It does not follow any particular distribution as only mean and standard deviation are known to us. A distribution free approach is used here to handle this situation. Quality improvement and safety factor are related issues to make an impact in the model as they are directly related to the customer satisfaction. The unit production cost is variable and dependent on production rate. An analytical procedure is derived to investigate the effects of reducing lead time, setup time crashing cost, and transportation crashing cost. Some numerical examples are illustrated to test the model. Sensitivity analysis and managerial insights are given to show the applicability of the model.
43 citations
TL;DR: An improved way to calculate imperfect items in an integrated inventory model with distribution free approach for lead time demand to simultaneously optimize lot size, safety factor, number of shipments, and lead time is investigated.
42 citations
TL;DR: This model follows the transportation discount policy for hassle-free delivery of the products with a minimum delivery rate and follows the Kuhn-Tucker optimization technique to avoid the backorder cost.
Abstract: In the current socio-economic situation, the daily demand for essential goods in the business sector is always changing owing to various unavoidable reasons. As a result, choosing the right method for profitable business has become quite tricky. This study introduces different business strategies based on constant and fuzzy demands. There are two types of constraints considered in this model to avoid the backorder cost. However, combining the service-level constraints with the constant and fuzzy demand, this study compares the total costs, and finally, the best strategy is established. Moreover, investing a small amount, this model improves the quality of the products and reduces the vendor’s setup cost. Depending on the number of transported products, this model follows the transportation discount policy for hassle-free delivery of the products with a minimum delivery rate. The Kuhn-Tucker optimization technique is employed, and global optimality is verified numerically, analytically using the Hessian matrix. This model’s robustness is discussed through a comparative study, numerical examples, sensitivity analysis, graphical representation, and managerial insights. Finally, some concluding remarks along with future extensions are discussed.
40 citations
TL;DR: An improved algorithm is designed to obtain the global minimum cost of SCM under the framework of a flexible production system and a numerical study proves that this model obtains the minimum cost with the optimal decision variables.
Abstract: For a complex product production, any flexible manufacturing system with a work-in-process inventory is recommended for a supply chain management (SCM) system. Building a flexible manufacturing sys...
40 citations
Cites background or methods from "Manufacturing quality improvement a..."
...To deflate the probability of moving out-of-control state, the manufacturer manipulates quality improvement as a continuous investment (see Ouyang, Yeh, and Wu 1996; Sarkar and Moon 2014; M. S. Kim and B. Sarkar 2017; Majumder, Guchhait, and Sarkar 2017)....
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...This can be assumed as c1 ≤ c2 ≤ · · · ≤ cn (Ouyang, Chen, and Chang 2002; Sarkar and Moon 2014; Majumder, Guchhait, and Sarkar 2017)....
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...The input data of this numerical experiment is taken from Majumder, Guchhait, and Sarkar (2017) and Glock (2009)....
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...Therefore, this model converges over (Majumder, Guchhait, and Sarkar 2017) in each aspect....
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...Majumder, Guchhait, and Sarkar (2017) incorporated quality improvement and setup cost reduction under a supply chain framework....
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