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Sort articles by: Volume | Date | Most Rates | Most Views | Reviews | Alphabet
1.

A production inventory model with exponential demand rate and reverse logistic Pages 521-542 Right click to download the paper Download PDF

Authors: Ritu Raj, Naresh Kumar Kaliraman, Shalini Chandra, Harish Chaudhary

DOI: 10.5267/j.ijiec.2014.7.006

Keywords: Imperfect Production, Integrated, Reverse Logistics, Supply Chain

Abstract:
The objective of this paper is to develop an integrated production inventory model for reworkable items with exponential demand rate. This is a three-layer supply chain model with perspectives of supplier, producer and retailer. Supplier delivers raw material to the producer and finished goods to the retailer. We consider perfect and imperfect quality products, product reliability and reworking of imperfect items. After screening, defective items reworked at a cost just after the regular manufacturing schedule. At the beginning, the manufacturing system starts produce perfect items, after some time the manufacturing system can undergo into “out-of-control” situation from “in-control” situation, which is controlled by reverse logistic technique. This paper deliberates the effects of business strategies like optimum order size of raw material, exponential demand rate, production rate is demand dependent, idle times and reverse logistics for an integrated marketing system. Mathematica is used to develop the optimal solution of production rate and raw material order for maximum expected average profit. A numerical example and sensitivity analysis is illustrated to validate the model.
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Journal: IJIEC | Year: 2014 | Volume: 5 | Issue: 4 | Views: 3184 | Reviews: 0

 
2.

A reverse logistic inventory model for imperfect production process with preservation technology investment under learning and inflationary environment Pages 107-122 Right click to download the paper Download PDF

Authors: Preeti Jawla, S. R. Singh

DOI: 10.5267/j.uscm.2015.12.001

Keywords: Exponential demand rate, Exponential holding cost, Imperfect production, Inflation, Learning, Multi-items, Preservation, Reverse logistics

Abstract:
This paper presents a unified multi items general inventory model for integrated production of new items and remanufacturing of returned and defected items for a finite planning horizon. In this paper, a production model that takes into account learning, instantaneous deterioration rate and inflation is proposed. In addition, we also consider that the holding cost is a non-negative, non-decreasing and continuous function of time. In this model, the preservation technology is used to reduce the rate of product deterioration. A theory is developed to find the optimal solution of the proposed model; it is then exemplified with the help of several numerical examples. An efficient solution procedure is also provided to find the optimal strategy. Finally, sensitivity of the optimal solution to changes in the values of different parameters of the system and the convexities of the cost functions are also studied and represented through the graphs.
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Journal: USCM | Year: 2016 | Volume: 4 | Issue: 2 | Views: 2698 | Reviews: 0

 
3.

Fuzzy production planning models for an unreliable production system with fuzzy production rate and stochastic/fuzzy demand rate Pages 179-192 Right click to download the paper Download PDF

Authors: K. A. Halim, B. C. Giri, K. S. Chaudhuri

DOI: 10.5267/j.ijiec.2010.05.001

Keywords: Inventory, production planning, Imperfect production, Fuzzy number, Graded mean integration representation method

Abstract:
In this article, we consider a single-unit unreliable production system which produces a single item. During a production run, the production process may shift from the in-control state to the out-of-control state at any random time when it produces some defective items. The defective item production rate is assumed to be imprecise and is characterized by a trapezoidal fuzzy number. The production rate is proportional to the demand rate where the proportionality constant is taken to be a fuzzy number. Two production planning models are developed on the basis of fuzzy and stochastic demand patterns. The expected cost per unit time in the fuzzy sense is derived in each model and defuzzified by using the graded mean integration representation method. Numerical examples are provided to illustrate the optimal results of the proposed fuzzy models.
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Journal: IJIEC | Year: 2011 | Volume: 2 | Issue: 1 | Views: 2671 | Reviews: 0

 

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