• 산업공학
• /
• 제16권1호
• /
• pp.111-116
• /
• 2003

Business integration has been considered as one of the most critical success factors that enable the firms to gain competitive edges. Despite this trend, it has also been found among not a few companies that the activities that should be functionally tied with are performed even independently. In this study, an integrated model of production planning and inventory has been developed. Computerization of the production planning activities is proposed and implemented. We also proposed the reasonable inventory levels of each item using historic data of the items, which are composed of safety stock from the given fill-rate, operating stock from the production patterns, and reserved stock from the production planning. This study has helped the firm to have clearer job definition of the related processes, to tightly control the inventory by setting and tracing the reasonable fill rates for every product, and to quickly respond to the market changes through the computerized production planning process.

• 대한산업공학회지
• /
• 제11권2호
• /
• pp.29-37
• /
• 1985

This paper studies a production-inventory model which unifies the inventory problem of raw materials and the finished product for a single product manufacturing system. The integrated production-inventory model is formulated wth a nonlinear mixed integer programming problem. An algorithm is developed by utilizing the finite explicit enumeration method. The algorithm guarantees to generate an optimal policy for minimizing the total annual variable cost. A mumerical example involving 15 raw materials is given to illustrate the recommended solution procedure.

• 경제분석
• /
• 제24권3호
• /
• pp.1-36
• /
• 2018

재고투자와 경기변동의 관계를 설명하는데 있어 생산평활(production smoothing) 가설과 재고소진 회피(stock-out avoidance) 가설은 서로 상반된 입장을 취하고 있다. 기업의 재고 투자에 관한 의사결정은 두 가지 동기 모두에 의해 영향받을 것으로 생각되지만 경기국면에 따라 각각의 영향력의 상대적 크기 혹은 방향성이 다르게 나타날 수 있다. 이에 본고는 재고투자 동학에서 생산평활 동기와 재고소진 회피동기의 상대적 유의성을 실증적으로 검증하되 경기국면별 비대칭성의 존재와 형태를 규명하는 데 분석의 초점을 둔 점에서 기존 연구와 차별성을 지닌다. 이를 위해 기존의 선형 재고투자 모형을 확장한 비선형 모형을 설정하였으며 이러한 방식이 기존 방식에 비해 우수한 지를 모형의 예측력을 비교 평가하여 확인하였다. 분석 결과, 재고투자 동학의 경기국면별 비대칭적 특성을 확인하였다. 경기 호황기에는 재고소진 회피동기가 나타나지만 생산평활 동기는 유의하지 않았다. 반대로 경기 불황기에는 재고소진 회피동기는 유의하지 않지만 Ramey (1991)에서 제시된 생산비용의 비볼록성에 의하여 재고변화가 경기침체를 심화시키는 경기 의존적 특성을 발견하였다. 경기국면별 비대칭성을 모형에 고려함으로써 그렇지 않은 모형에 비해 예측력을 향상시킬 수 있음을 표본 내 및 표본 외 예측, 다양한 예측력 검정을 통해 확인하였다. 본 연구의 결과는 재고투자의 동학과 경기 불안정화 특성에 대한 이해를 제고하여 경제전망 등에 활용될 수 있을 것으로 기대된다.

• 품질경영학회지
• /
• 제16권1호
• /
• pp.78-87
• /
• 1988

The purpose of this study is to develop the algorithm applicable to the integrated production inventory model under quantity discount. To achieve this purpose, the integrated production inventory model which unifies the inventory problem of raw materials and the finished product for a single product manufacturing system is considered. The product is manufactured in batches and the raw materials are obtained from outside suppliers but some of the raw materials are discounted according to the purchasing quantity. The intergrated production inventory problem considered in this study is formulated by the non-linear mixed integer programming model, and the optimal solution is obtained by using the algorithm developed by Goyal. Then, the algorithm developed by this study is applied to the quantity discount problem, and the optimal solution is revised by this results. The quantity discount algorithm of the integrated production inventory model developed by this study gives a systematic procedure to obtain the optimum policy to minimize the total cost in any case. The numerical example involving 20 raw materials and 5 raw materials among them are discounted according to the purchasing quantity is given to verify the mathematical model and the algorithm developed in this study.

• 대한산업공학회지
• /
• 제34권4호
• /
• pp.425-432
• /
• 2008

While the Vendor-Managed Inventory(VMI) is a convenient inventory replenishment policy for the customer company, the supplier usually bears the burden of higher inventory and urgent shipments to avoid shortage. Recently some manufacturers begin to fix the production schedule for the next few days (such as three days). Utilizing that information can improve the efficiency of the VMI. In this study, we present a myopic optimization model using a mixed inter programming; and a heuristics algorithm. We compare the performance of the two proposed methods with the existing (s, S) reorder policy. We consider the total cost as the sum of transportation cost and inventory cost at the customer's site. Numerical tests indicate that the two proposed methods significantly reduce the total cost over the (s, S) policy.

• 한국경영과학회지
• /
• 제1권1호
• /
• pp.151-170
• /
• 1976

There are many cases of production processes which intermittently produce several different kinds of products for stock through one set of physical facility. In this case, an important question is what size of production run should be prduced once we do set-up for a product in order to minimize the total cost, that is, the sum of the set-up, carrying, and stock-out costs. This problem is used to be called scheduling of multiple products through a single facility in the production management field. Despite the very common occurrence of this type of production process, no one has yet devised a method for determining the optimal production schedule. The purpose of this study is to develop quantitative analytical models which can be used practically and give us rational production schedules. The study is to show improved models with application to a can-manufacturing plant. In this thesis the economic production quantity (EPQ) model was used as a basic model to develop quantitative analytical models for this scheduling problem and two cases, one with stock-out cost, the other without stock-out cost, were taken into consideration. The first analytical model was developed for the scheduling of products through a single facility. In this model we calculate No, the optimal number of production runs per year, minimizing the total annual cost above all. Next we calculate No$_{i}$ is significantly different from No, some manipulation of the schedule can be made by trial and error in order to try to fit the product into the basic (No schedule either more or less frequently as dictated by) No$_{i}$, But this trial and error schedule is thought of inefficient. The second analytical model was developed by reinterpretation by reinterpretation of the calculating process of the economic production quantity model. In this model we obtained two relationships, one of which is the relationship between optimal number of set-ups for the ith item and optimal total number of set-ups, the other is the relationship between optimal average inventory investment for the ith item and optimal total average inventory investment. From these relationships we can determine how much average inventory investment per year would be required if a rational policy based on m No set-ups per year for m products were followed and, alternatively, how many set-ups per year would be required if a rational policy were followed which required an established total average inventory inventory investment. We also learned the relationship between the number of set-ups and the average inventory investment takes the form of a hyperbola. But, there is no reason to say that the first analytical model is superior to the second analytical model. It can be said that the first model is useful for a basic production schedule. On the other hand, the second model is efficient to get an improved production schedule, in a sense of reducing the total cost. Another merit of the second model is that, unlike the first model where we have to know all the inventory costs for each product, we can obtain an improved production schedule with unknown inventory costs. The application of these quantitative analytical models to PoHang can-manufacturing plants shows this point.int.

• 산업경영시스템학회지
• /
• 제38권3호
• /
• pp.117-126
• /
• 2015

This paper is to analyze an integrated production and inventory model in a single-vendor multi-buyer supply chain. The vendor is defined as the manufacturer and the buyers as the retailers. The product that the manufacturer produces is supplied to the retailers with constant periodic time interval. The production rate of the manufacturer is constant for the time. The demand of the retailers is constant for the time. The cycle time of the vendor is defined as the elapsed time from the start of the production to the start of the next production, while the cycle times of the buyer as the elapsed time between the adjacent supply times from the vendor to the buyer. The cycle times of the vendor and the buyers that minimizes the total cost in a supply chain are analyzed. The cost factors are the production setup cost and the inventory holding cost of the manufacturer, the ordering cost and the inventory holding cost of the retailers. The cycle time of the vendor is investigated through the cycle time that satisfies economic production quantity with the production setup cost and the inventory holding cost of the manufacturer. An integrated production and inventory model is formulated, and an algorithm is developed. An numerical example is presented to explain the algorithm. The solution of the algorithm for the numerical examples is compared with that of genetic algorithm. Numerical example shows that the vendor and the buyers can save cost by integrated decision making.

• Management Science and Financial Engineering
• /
• 제15권1호
• /
• pp.33-49
• /
• 2009

We examine the effectiveness of the conventional (Q, r) model in managing production-inventory systems with finite capacity, stochastic demand, and stochastic order processing times. We show that, for systems with finite production capacity, order replenishment lead times are highly sensitive to loading and order quantity. Consequently, the choice of optimal order quantity and optimal reorder point can vary significantly from those obtained under the usual assumption of a load-independent lead time. More importantly, we show that for a given (Q, r) policy the conventional model can grossly under or over-estimate the actual cost of the policy. In cases where a setup time is associated with placing a production order, we show that the optimal (Q, r) policy derived from the conventional model can, in fact, be infeasible.

• 대한산업공학회지
• /
• 제5권2호
• /
• pp.9-14
• /
• 1979

Inventories of finished products exist in each stage of the channel between production and consumption. An inventory has several functions, which make it possible to produce by economic lot size and to elevate services for consumer by shortening delivery time, etc$\cdots$. Finished products may be inventoried in delivery-center as well as at the plant where production takes place. So, finshed products must be dealt with as multistage inventory problem, because an inventory functions differently according to its place. The purpose of this study is to determine how much to carry in stock and what stage to carry Though there may be several channels between production and consumption, this study deals with only one main channel, that is, series of ncomponents and determines the optimal inventory policy by introducing the concept of selling probabilities.

• 한국경영과학회지
• /
• 제37권2호
• /
• pp.45-56
• /
• 2012

This paper considers a supply chain consisting of a component manufacturer and a product manufacturer. The component manufacturer provides components for the product manufacturer based on a vendor-managed inventory type of supply contract, and also faces demands from the market with the option of to accept or reject each incoming demand. Using the Markov decision process model, we examine the structure of the optimal production control and inventory rationing policy. Two types of heuristics are presented. One is the fixed-buffer policy and the other uses two linear functions. We implement a computational study and present managerial insights based on the observations.