• The Journal of the Institute of Internet, Broadcasting and Communication
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• v.18 no.2
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• pp.197-207
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• 2018

SMEs manufacturing Factory, which are small-scale production systems of various types, mass-produce and sell products in order to meet customer needs. This means that the company has an excessive amount of material supply to reduce the loss due to lack of inventory and high inventory maintenance cost. And the products that fail to respond to the demand are piled up in the management warehouse, which is the reality that the storage cost is incurred. To overcome this problem, this paper uses ARIMA model, a time series analysis technique, to predict demand in terms of seasonal factors. In this way, demand forecasting model based on economic order quantity model was developed to prevent stock shortage risk. Simulation is carried out to evaluate the effectiveness of the development model and to demonstrate the effectiveness of the development model as applied to SMEs in the future.

• Journal of Korean Society for Quality Management
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• v.50 no.1
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• pp.153-167
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• 2022

Purpose: The purpose of this study is to guide the operation managers who plan daily production of large mass-processing facility that services multi-customers with multi-product, small-batch item characteristics by providing the practical best production quantity and the inventory allowed to build. Methods: Close observation of a subcontract paint-shop operator captured the daily decision process which was reflected in the subcontractor-unique mathematical model and the system dynamics simulation model. Multiple simulations were run to find the practical best production quantity and the maximum allowable stock level of inventory that did not undermine the profit from practical best daily production. Actual data and a few constant values were obtained from the firm under study. Results: While the inventory holding cost for the customer-owned material harms the total profit of the subcontractor, the running cost of the processing facility hinders production in small batches. This balances the maximum possible productions and results in practical best daily production which can be found through simulation runs with actual data. The maximum level of stocked inventory is deduced from the practical best daily production. Conclusion: To build a large volume that enables economy-of-scale production, operators should deal with multi-product small-batch items from multiple customers. When the planned schedule of the time and amount of material in-flow tend not to be reliable, operators can find it practical to execute level production across the planning horizon instead of adjusting to day-to-day in-flow fluctuations.

• Journal of applied mathematics & informatics
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• v.19 no.1_2
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• pp.397-414
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• 2005

In the existing literature, most of the purchasing models were developed only for retailers problem ignoring the constraint of storage capacity of retailers shop/showroom. In this paper, we have developed a deterministic model of wholesaler-retailers' problem of single product. The storage capacity of wholesaler's warehouse/showroom and retailers' showroom/shop are assumed to be finite. The items are transported from wholesaler's warehouse to retailers' Own Warehouse (OW) in a lot. The customer's demand is assumed to be displayed inventory level dependent. Demands are met from OW and that spaces of OW will immediately be filled by shifting the same amount from the Rented Warehouse (RW) till the RW is empty. The time duration between selling from OW and filling up its space by new ones from RW is negligible. According to relative size of the retailers' existing (own) warehouse capacity and the demand factors, different scenarios are identified. Our objectives are to optimize the cost functions of wholesaler and two retailers separately. To solve this problem, a real coded Genetic Algorithm (GA) with roulette wheel selection/reproduction, whole arithmetic crossover and non-uniform mutation is developed. Finally a numerical example is presented to illustrate the results for different scenarios. To compare the results of GA, Generalised Reduced Gradient Method has been used for the problem. Also, a sensitivity analysis has been performed to study the variations of the optimal average cost with respect to the different parameters.

• Journal of Korea Society of Industrial Information Systems
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• v.27 no.6
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• pp.105-114
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• 2022

We examine berth allocation problems in tidal bulk ports with an objective of minimizing the demurrage and dispatch associated berthing cost. In the proposed optimization model inventory (or stock) level constraints are considered so as to satisfy the service level requirements in bulk terminals. It is shown that the mathematical programming formulation of this research provides improved schedule resolution and solution accuracy. We also show that the conventional big-M method of standard resource allocation models can be exempted in tidal bulk ports, and thus the computational efficiency can be significantly improved.

• Proceedings of the Safety Management and Science Conference
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• 2002.11a
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• pp.227-232
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• 2002

Enormous flocks by the reduced life cycle of products caused by the technological innovation if later 20 century, development of new materials and diversified demands of customers appeared as the pressing element causing the trouble in management of companies, and when considering the logistic costs that are imposed to companies in terms of function, the costs related to the stock topped the list of costs, followed by the transportation ones, and for pallet pool system, inventory of stocks is very difficult by the number of companies. Reducing the logistic cost may be accomplished by numbers of logistic management methods, but the most fundamental and essential one is the accomplishment of the consistent pallet system that is the core of unit load system, and the purpose of consistent pallet system is the treatment of logistic functions such as transportation, storage and unloading with consistent pallet system, and increasing the turnover ratio is required for the improvement of the system. As the turnover ratios is increased, more pallets will be used so, numbers of empty pallets will be increased accordingly by returning the pallet. Therefore, in this study, we will establish the effective stock management system by comparing with the other existing stock management system after looking at the concept and examples of pallet full system in order to resolved this kind of problem.

• Journal of the Korea Safety Management & Science
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• v.5 no.1
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• pp.33-43
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• 2003

Enormous stocks by the reduced life cycle of products caused by the technological innovation in later 20 century, development of new materials and diversified demands of customers appeared as the pressing element causing the trouble in management of companies, and when considering the logistic costs that are imposed to companies in terms of function, the costs related to the stock topped the list of costs, followed by the transportation ones, and for pallet pool system, inventory of stocks is very difficult by the number of companies. Reducing the logistic cost may be accomplished by numbers of logistic management methods, but the most fundamental and essential one is the accomplishment of the consistent pallet system that is the core of unit load system, and the purpose of consistent pallet system is the treatment of logistic functions such as transportation, storage and unloading with consistent pallet system, and increasing the turnover ratio is required for the improvement of the system. As the turnover ratios is increased, more pallets will be used so, numbers of empty pallets will be increased accordingly by returning the pallet. Therefore, in this study, we will establish the effective stock management system by comparing with the other existing stock management system after looking at the concept and examples of pallet full system in order to resolved this kind of problem.

• Journal of the Korean Operations Research and Management Science Society
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• v.26 no.3
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• pp.105-117
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• 2001

This paper models supply uncertainty in the dynamic Newsboy problem context. The system consists of one supplier and one retailer who places an order to the supplier every period to meet stochastic demand. Supply uncertainty is modeled as the uncertainty in quantities delivered by the supplier. That is, the supplier delivers exactly the amount ordered by the retailer with probability of $\beta$ and the amount minus K with probability of (1-$\beta$). We formulate the problem as a dynamic programming problem and prove that retailer’s optimal replenishment policy is a stationary base-stock policy. Through a numerical study, we found that the cost increase due to supply uncertainty is significant and that the costs increase more rapidly as supply uncertainty increases. We also identified the effects of various system parameters. One of the interesting results is that as retailer’s demand uncertainty, the other uncertainty in our model, increases, the cost increase due to supply uncertainty becomes less significant.

• Journal of the Korea Safety Management & Science
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• v.8 no.5
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• pp.139-150
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• 2006

The aim of this study is to establish an efficient distribution planning for a capacitated multi-stage supply chain. We assume that the demand information during planning horizon is given a deterministic form using a certain forecasting method. Under such a condition, we present a cost effective heuristic method for minimizing chain-wide supply chain inventory cost that is the sum of holding and backorder costs by using look-ahead technique. We cope with the capacity restriction constraints through look-ahead technique that considers not only the current demand information but also future demand information. To evaluate performance of the proposed heuristic method, we compared it with the extant research that utilizes echelon stock concept, under various supply chain settings.

• The Journal of the Convergence on Culture Technology
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• v.8 no.6
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• pp.655-660
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• 2022

This paper analyzes the problem of the economic order quantity (lot size) of a retailer in a two-stage supply chain consisting of a supplier, a retailer(distributor), and a customer. In this two-stage supply chain, the supplier permits the retailer to defer payment for a certain fixed period of time for the purchase cost to be paid by the retailer as a price differentiation strategy with his competitor. In addition, in the case of customer goods such as food and grain, it is common to see that end-customer demand is generally depend on the level of inventory displayed by the retailer. From this perspective, this paper analyzes the inventory problem of retailers under the assumption that the supplier may allow a certain period to suspend payments for the purchase of goods and the end customer demand is a function of the retailer's inventory level increasing with size. In this regard, we need to analyze how much the length of the grace period for product purchase costs affect the retailer's lot-sizing policy. Therefore, we formulate the retailer's annual net profit and analyze the effect of the length of credit period on the retailer's inventory policy numerically.

• Korean Journal of Construction Engineering and Management
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• v.25 no.5
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• pp.41-54
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• 2024

In this study, we compare and analyze the performance of three inventory management policies for raw material inventory management in a Precast Concrete production plant: Fixed Order Quantity Policy (FOQP), Fixed Order Interval Policy (FOIP), and (s, S) Ordering Policy (sSOP). In order to make more realistic conclusion, we developed and utilized the ARENA simulation model, a performance evaluation tool that considers the variance of raw material demand and supply for the entire production process in a PC production plant using multiple raw materials. For the three policies, reorder point, order quantity, target level, and order interval parameters were initialized by using Economic Order Quantity (EOQ) model and then optimized through OptQuest. As a result of optimization, inventory management costs were reduced by an average of 97.28% compared to the EOQ model that does not consider the variance of demand and supply. After setting three influencing factors, Project Occurrence Cycle (POC), Raw Material Lead-time (RML), and Unit Stock-out Cost (USC), a performance evaluation was conducted for the three policies. As a result of evaluation, the inventory management costs of FOQP and sSOP, which determine order intervals by considering inventory levels by real-time or daily, were 30.6% and 27.9% lower than FOIP with fixed order intervals respectively. In addition, inventory management costs were affected by RML and USC factors excluding POC, but the differences were 2.17% and 2.09% respectively, which were not large due to the optimization of parameters for responding the variance of raw material demand and supply.