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Abstract
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Article Information:
Solving a Multi-Item Finite Production Rate Model with Scrap and Multi-Shipment Policy without Derivatives
Yuan-Shyi Peter Chiu, Hong-Dar Lin, Singa Wang Chiu and Kuang-Ku Chen
Corresponding Author: Singa Wang Chiu
Submitted: July 27, 2012
Accepted: September 08, 2012
Published: May 25, 2013 |
Abstract:
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In real life manufacturing environments, production managers often make plan to produce m products in turn on a single machine in order to maximize the machine utilization. This study focuses on determining an optimal common production cycle time for a multi-item Finite Production Rate (FPR) model with random scrap rate and multi-shipment plan without using the derivatives. We assume that m products are manufactured in turn based on a common cycle policy on a single machine and during the processes some nonconforming items are generated randomly. These defective items cannot be reworked, thus they are scrapped at additional costs in the end of each production cycle. After the entire lot is quality assured, the delivery of finished items is under a practical multiple shipments plan. The objective is to determine an optimal common cycle time that minimizes the long-run average cost per unit time using an algebraic approach. Conventional method for solving such a problem is by the use of differential calculus on system cost function to derive the optimal policy, whereas the proposed approach is a straightforward method. It helps practitioners, who may not have sufficient knowledge of calculus, to understand and manage the real-life multi-item production systems more effectively.
Key words: Algebraic approach, common cycle time, finite production rate, inventory, multi-item production, multi-shipment, scrap
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Cite this Reference:
Yuan-Shyi Peter Chiu, Hong-Dar Lin, Singa Wang Chiu and Kuang-Ku Chen, . Solving a Multi-Item Finite Production Rate Model with Scrap and Multi-Shipment Policy without Derivatives. Research Journal of Applied Sciences, Engineering and Technology, (06): 2036-2041.
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ISSN (Online): 2040-7467
ISSN (Print): 2040-7459 |
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