• Industrial Engineering and Management Systems
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• v.6 no.1
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• pp.1-10
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• 2007

The objective of this study is to develop an optimal joint cost from the perspectives of both the manufacturer and the retailer. The integrated production-inventory model with Weibull distribution deteriorating items is assumed to have a constant demand rate. A limited retailer storage space and multiple delivery per order are considered in this model. A numerical example including the sensitivity analysis is given to validate the results of the production-inventory model.

• Journal of the Korean Operations Research and Management Science Society
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• v.29 no.3
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• pp.9-21
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• 2004

Semiconductor industry is the one whose supply chain network is distributed all over the world. And it has different characteristics with other manufacturing industries as reentrancy, binning, substitution. In this paper, we suggest supply chain models for the semiconductor industry, consisting of production and distribution chains, where manufacturing characteristics are considered. Three policies for the production chain and two policies for the distribution chain are suggested and formulated mathematically. Six combination policies are tested for the evaluation of performances with example. It is shown that the supply chain is operated, if production and distribution are coordinated and managed based on the demand information, without inventory, as efficiently as the chain with inventory.

• Industrial Engineering and Management Systems
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• v.9 no.4
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• pp.303-311
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• 2010

In the last few years growing interest has been dedicated to supply chain management. Modeling complexity is added to supply chain coordination problem by accounting for reverse logistics activities. The objective of this paper is to extend inventory model of manufacturing factory with respect to the production of raw material of forward logistics and recycling material of reverse logistics. The proposed model is applied to a plastic recycling process plant located in Taiwan. The case study improvement scheme shows when the recycling rate of recycling material increases from 15% to 50%, the total inventory cost of manufacturing factory decreases by 12.82%, safety stock volume decreases by 41.19% and the reorder quantity is down by 50.96%. This paper finds whether the results of the model can reach the economic profit through quantitative analysis and encourages companies integrate reverse logistics into the supply chain system.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.10a
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• pp.10-26
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• 2005

In our model, we keep inventory to satisfy uncertain demands which arrives irregularly. In this situation, we have additional two constraints. First, we need to have certain amount of order consolidation (consolidation constraint) for the orders to replenish the inventory because of production or purchase constraint. And also, if we order at a certain date which was set by administrative convenience, we have amount constraint to order the consolidated order demands (capacity constraint). We showed this variant inventory policy is needed in steel industry and note that there will be possible similar case in industry. To deal with this case, we invented a variant replenishment policy and show this policy is superior to other possible polices in the consolidation constraint case by extensive simulation. And we derive a combined solution method for dealing with the capacity constraints in addition to the consolidation constraints. For this, we suggest a combined solution method of integer programming and simulation.

• Journal of the Korean Operations Research and Management Science Society
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• v.31 no.2
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• pp.99-112
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• 2006

In our model, we keep inventory to satisfy uncertain demands which arrives irregularly. In this situation, we have additional two constraints. First, we need to have certain amount of order consolidation (consolidation constraint) for the orders to replenish the inventory because of production or purchase amount constraint. And also, if we order at a certain date which was set by administrative convenience, we have capacity constraint to order the consolidated order demands (capacity constraint). We show this variant inventory policy is needed in steel industry and note that there will be possible similar case in industry. To deal with this case, we invent a variant replenishment policy and show this policy is superior to other possible polices in the consolidation constraint case by extensive simulation. And we derive a combined solution method for dealing with the capacity constraints in addition to the consolidation constraints. For this, we suggest a combined solution method of integer programming and simulation.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 1999.04a
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• pp.426-426
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• 1999

;There are many sources of uncertainty in a typical production and inventory system. There is uncertainty as to how many items customers will demand during the next day, week, month, or year. There is uncertainty about delivery times of the product. Uncertainty exacts a toll from management in a variety of ways. A spurt in a demand or a delay in production may lead to stockouts, with the potential for lost revenue and customer dissatisfaction. Firms typically hold inventory to provide protection against uncertainty. A cushion of inventory on hand allows management to face unexpected demands or delays in delivery with a reduced chance of incurring a stockout. The proposed strategies are used for the design of a probabilistic inventory system. In the traditional approach to the design of an inventory system, the goal is to find the best setting of various inventory control policy parameters such as the re-order level, review period, order quantity, etc. which would minimize the total inventory cost. The goals of the analysis need to be defined, so that robustness becomes an important design criterion. Moreover, one has to conceptualize and identify appropriate noise variables. There are two main goals for the inventory policy design. One is to minimize the average inventory cost and the stockouts. The other is to the variability for the average inventory cost and the stockouts The total average inventory cost is the sum of three components: the ordering cost, the holding cost, and the shortage costs. The shortage costs include the cost of the lost sales, cost of loss of goodwill, cost of customer dissatisfaction, etc. The noise factors for this design problem are identified to be: the mean demand rate and the mean lead time. Both the demand and the lead time are assumed to be normal random variables. Thus robustness for this inventory system is interpreted as insensitivity of the average inventory cost and the stockout to uncontrollable fluctuations in the mean demand rate and mean lead time. To make this inventory system for robustness, the concept of utility theory will be used. Utility theory is an analytical method for making a decision concerning an action to take, given a set of multiple criteria upon which the decision is to be based. Utility theory is appropriate for design having different scale such as demand rate and lead time since utility theory represents different scale across decision making attributes with zero to one ranks, higher preference modeled with a higher rank. Using utility theory, three design strategies, such as distance strategy, response strategy, and priority-based strategy. for the robust inventory system will be developed.loped.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.36
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• pp.193-203
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• 1995

The production management system software which can be applied In the medium and small companies is developed. Since the medium and small companies hesitate to install the computer system for production management owing to the lack of funds and the complexities of operation, the system is made to be used in PC and only requires minimum input data. This system is composed of interrelated modules for receive/order release, inventory management MRP, new product registration, document management and production scheduling. In this paper the architecture of the system, functions of each module, and information processing procedures of each funtion are discussed.

• Korean Management Science Review
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• v.32 no.4
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• pp.19-28
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• 2015

This study presents a mathematical programming model to develop production planning in the manufacturing processes for photovoltaic silicon ingots and wafers. The model is formulated as a linear programming model that maximizes total growth margin, which is composed of production cost, inventory cost, shortage cost, and sales profit while considering the constraints associated with the production environments of photovoltaic materials. In order to demonstrate the utility of the model for production planning, we run operations for a planning horizon of a year for a case study. When the primary results of this mathematical programming are compared with the historical records, the model could have resulted in the considerable increase of the total growth margin by effectively reducing inventory cost if a decision maker had employed the model as a decision support system with perfect information for sales demand.

• Journal of the Korean Operations Research and Management Science Society
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• v.22 no.4
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• pp.93-113
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• 1997

In studying an EOQ-like inventory model for a manufacturing process, a number of findings were made. The system can "go out of control" resulting in a relatively minor problem state or "break-down". When the production system is in the minor problem statei produces a number of defective items. It is assumed that each defective piece requires rework cost and related operations. Once the machine breakdown takes place, the production system produces severely defective items that are completely unusable. Each completely unusuable item is immediately discarded and incurs handling cost, scrapped raw material cost and related operations. Two investment options in improving the production process are introduced : (1) reducing the probability of machine breakdown, breakdowns, and (2) simultaneously reducing the probability of machine breakdowns and setup costs. By assuming specific forms of investment cost function, the optimal investment policies are obtained explicitly. Finally, to better understand the model in this paper, the sensitivity of these solutions to changes in parameter values and numerical examples are provided.amples are provided.

• 제어로봇시스템학회:학술대회논문집
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• 2004.08a
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• pp.722-725
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• 2004

In most manufacturing systems, all customers are expected to take deliveries from inventory. However, in some situations, management may keep inventory only for some customers and not keep inventory for the others. The reason is that they would like to make as much benefit as possible from the first group of customers and this may help sell these customers on further products. This paper attempts to determine the cutoff between the group of customers who are given products immediately when their orders come and other customers who will be served but have to wait for the production of their products. The optimum set of customers to be served immediately and the optimum set of customers who have to wait for the production are found using linear programming to optimize perceived manufacturer benefits measured as the product of the benefit factor and the corresponding profit per customer. The results indicate that it is not necessarily wise to keep inventory for all customers.