Entity

Time filter

Source Type


Wang C.-H.,Institute of Commerce and Business | Tsai W.C.,I - Shou University
International Journal of Systems Science | Year: 2012

This study simultaneously determines the optimal production lot size and an inspection policy for input materials and products, where an unreliable process produces products with a discrete general shift distribution. This work proposes a heuristic inspection policy for materials and products, by first obtaining the inspection range for the input material without considering product inspection, and by further determining the product inspection range based on the obtained range of the input material inspection. The optimal inspection policy shows that common policies of no or full inspection are never optimal. This study includes the optimal production lot size based on the obtained inspection policy. Numerical examples demonstrate the impacts of input quality level, process reliability and unit nonconforming cost on the optimal solution, which adopts a discrete Weibull shift distribution to model the process failure time. Finally, this study addresses the conclusions. © 2012 Taylor & Francis Group, LLC. Source


Tsai W.C.,I - Shou University | Wang C.-H.,Institute of Commerce and Business
Computers and Industrial Engineering | Year: 2011

An economic off-line inspection, disposition, and rework (IDR) model for a batch produced from an unreliable production system was recently proposed by Wang et al. [Economic optimization of off-line inspection with rework consideration, European Journal of Operational Research, 194 (2009) 807-813], where the process is assumed to possess a discrete general shift distribution. Unfortunately, there are some important flaws in the proposed IDR model; in particular, while obtaining optimal IDR policy, they incorrectly assumed that the process shift distribution had the memoryless property. As a result, the purpose of this paper is to reformulate the IDR model, and to develop a solution procedure to find the optimal IDR policy. © 2011 Elsevier Ltd. All rights reserved. Source


Tsai W.C.,I - Shou University | Wang C.-H.,Institute of Commerce and Business
Journal of Manufacturing Systems | Year: 2010

This paper applied a mixed integer programming approach to solve the sourcing and order allocation problem with multiple products and multiple suppliers in a supply chain. The decision process is driven by multiple objectives and a set of constraints. Two schemes of quantity discounts are used to compare the influence upon the buying decisions. An example and an experimental test are presented to demonstrate the effectiveness of the model. The computational solutions are a valuable tool to eliminate much of the subjectivity that impacts decisions under complex situations. A graphical display for the solutions is provided which can assist DMs in making decisions among criteria. © 2010 The Society of Manufacturing Engineers. Published by Elsevier Ltd. All rights reserved. Source


Wang C.-H.,Institute of Commerce and Business | Dohi T.,Hiroshima University | Tsai W.C.,I - Shou University
Computers and Industrial Engineering | Year: 2010

In this study, we investigate integrating the acquisition of input materials, material inspection and production planning, where type I and type II inspection errors are allowed, and the unit acquisition cost is dependent on the average quality level. This study aims to find an optimal purchase lot size (or here, equivalently, the fixed production rate multiplied by the production run time), input quality level and the associated inspection policy that minimize the total cost per item including the order cost, materials purchase cost, setup cost, inventory holding cost, and the quality-related cost. Furthermore, the boundaries, conditions and properties for the optimal production run time are obtained under an optimal inspection policy when the input material quality level is fixed. These findings will facilitate the establishing of an efficient algorithm for an optimal solution. The study demonstrates that a partial inspection approach could dominate over both the commonly used policies of full or no inspection, which is different from a previous report where the optimal inspection policy is either full or no inspection. A numerical example is performed to evaluate the impact of the two types of inspection errors and the process deterioration because of a nonconforming process input on the optimal solution, where a Weibull shift distribution is used to simulate the process failure time. Finally, conclusions are addressed. © 2010 Elsevier Ltd. All rights reserved. Source


Wang C.-H.,Institute of Commerce and Business
Computers and Industrial Engineering | Year: 2010

In the reports in the literature on inventory control, the effects of the random capacity on an order quantity and reorder point inventory control model have been integrated with lead time demand following general distribution. An iterative solution procedure has been proposed for obtaining the optimal solution. However, the resulting solution may not exist or it may not guarantee to give a minimum to the objective cost function, the expected cost per unit time. The aim of this study was to introduce a complete solution of the order quantity/reorder point problem, optimality, properties and bounds on the optimal order quantity and reorder point. The two most appealing distributions of lead time demand, normal and uniform distributions, in conjunction with an exponentially distributed capacity, are used to illustrate our findings in determining the optimal order quantity and reorder point. © 2010 Elsevier Ltd. All rights reserved. Source

Discover hidden collaborations