scholarly journals An Optimizing Integrated Inventory Model with Investment for Quality Improvement and Setup Cost Reduction

Author(s):  
Vijayashree M ◽  
Uthayakumar R
2019 ◽  
Vol 53 (1) ◽  
pp. 39-57 ◽  
Author(s):  
Bikash Koli Dey ◽  
Biswajit Sarkar ◽  
Mitali Sarkar ◽  
Sarla Pareek

This paper develops a sustainable integrated inventory model for maximizing profit with a controllable lead time, discrete setup cost reduction, and consideration of environmental issues. Contrary to the available literature, this paper considers a discrete setup cost for the vendor, thus making the integrated model sustainable. The customer’s demand is assumed to be selling-price dependent to increase the number of sales, and the lead time demand follows a Poisson distribution. The integrated model is used to optimized the total shipment number, volume of shipments, safety factor, investments, selling-price, and probability of moving between the “in-control” to “out-of-control” states. An algorithm is developed to obtain the numerical results. Numerical examples and sensitivity analyses are given to illustrate the model.


Energies ◽  
2019 ◽  
Vol 12 (19) ◽  
pp. 3733 ◽  
Author(s):  
Irfanullah Khan ◽  
Jihed Jemai ◽  
Han Lim ◽  
Biswajit Sarkar

The need for efficient electrical energy consumption has greatly expanded in the process industries. In this paper, efforts are made to recognize the electrical energy consumption in a two-echelon supply chain model with a stochastic lead-time demand and imperfect production, while considering the distribution free approach. The initial investments are made for quality improvement and setup cost reduction, which ultimately reduce electrical energy consumption. The inspection costs are considered in order to ensure the good qualities of the product. Centralized and decentralized strategies are used to analyze the proposed supply chain model. The main objective of this study is to reduce the overall cost through efficient electrical energy consumption in supply chain management by optimizing the lot size, the number of shipments, the setup cost, and the failure rate. A quantity-based transportation discount policy is applied to reduce the expected annual costs, and a service-level constraint is incorporated for the buyer to avoid a stockout situation. The impact of the decision variables on the expected total costs is analyzed, and sensitivity analysis is carried out. The results show a significant reduction in overall cost, with quality improvement and setup cost reduction ultimately reducing electrical energy consumption.


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