• 한국경영과학회:학술대회논문집
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• 한국경영과학회/대한산업공학회 1999년도 춘계공동학술대회:정보화시대의 지식경영
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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.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 2006년도 추계학술대회
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• pp.391-402
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• 2006

Most previous studies considering inventory models for imperfect quality assumed that defective items could be completely detected by inspection and fixed before delivery to customers. This makes it difficult to adopt their research results to practice. This study reduces the assumption of perfect inspection, and presents an inventory model considering reverse logistics caused by imperfect inspection. System dynamics model is used to describe complex and dynamic problem and to show the effect of imperfect inspection on profit by simulation. Then, this article provides a guideline for the inspection policy which provides the maximum profit.

• 산업경영시스템학회지
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• 제37권4호
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• pp.116-125
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• 2014

In this paper, we investigate an inventory and production system in a three-layer supply chain system involving a single supplier, single manufacturer and multiple retailers. Earlier study in this type of supply chain only consider a single raw material in order to produce single item, but we consider raw materials in order to produce multiple items. It is assumed that the cycle time at each stage is an integer multiple of the adjacent downstream stage. We develop an iterative solution procedure to find the order quantity for the multiple items and raw materials that minimizes the supply chain-wide total cost per unit time of the supplier and manufacturer's raw materials ordering and holding, setup and finished items holding, the retailer's ordering and inventory holding. Numerical examples are presented to show that the proposed heuristic gives good performance.

• 경영과학
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• 제10권2호
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• pp.43-59
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• 1993

A production control information system developed for multi-product, small-lot-sized production is presented. The system is composed of interrelated modules for production planning, shop floor control, and inventory/material management. The architecture of the system, functions of each module, and information processing procedures of each function are discussed.

• 한국정보시스템학회지:정보시스템연구
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• 제30권1호
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• pp.151-177
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• 2021

Purpose This paper aims to improve management performance by effectively responding to production needs and reducing inventory through synchronizing production planning and procurement in the aviation industry. In this study, the differences in production planning and execution were first analyzed in terms of demand, supply, inventory, and process using the big data collected from a domestic aircraft manufacturers. This paper analyzed the problems in procurement and inventory management using legacy big data from ERP system in the company. Based on the analysis, we performed a simulation to derive an efficient procurement and inventory management plan. Through analysis and simulation of operational data, we were able to discover procurement and inventory policies to effectively respond to production needs. Design/methodology/approach This is an empirical study to analyze the cause of decrease in inventory turnover and increase in inventory cost due to dis-synchronize between production requirements and procurement. The actual operation data, a total of 21,306,611 transaction data which are 18 months data from January 2019 to June 2020, were extracted from the ERP system. All them are such as basic information on materials, material consumption and movement history, inventory/receipt/shipment status, and production orders. To perform data analysis, it went through three steps. At first, we identified the current states and problems of production process to grasp the situation of what happened, and secondly, analyzed the data to identify expected problems through cross-link analysis between transactions, and finally, defined what to do. Many analysis techniques such as correlation analysis, moving average analysis, and linear regression analysis were applied to predict the status of inventory. A simulation was performed to analyze the appropriate inventory level according to the control of fluctuations in the production planing. In the simulation, we tested four alternatives how to coordinate the synchronization between the procurement plan and the production plan. All the alternatives give us more plausible results than actual operation in the past. Findings Based on the big data extracted from the ERP system, the relationship between the level of delivery and the distribution of fluctuations was analyzed in terms of demand, supply, inventory, and process. As a result of analyzing the inventory turnover rate, the root cause of the inventory increase were identified. In addition, based on the data on delivery and receipt performance, it was possible to accurately analyze how much gap occurs between supply and demand, and to figure out how much this affects the inventory level. Moreover, we were able to obtain the more predictable and insightful results through simulation that organizational performance such as inventory cost and lead time can be improved by synchronizing the production planning and purchase procurement with supply and demand information. The results of big data analysis and simulation gave us more insights in production planning, procurement, and inventory management for smart manufacturing and performance improvement.

• 산업경영시스템학회지
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• 제39권3호
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• pp.170-179
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• 2016

In this paper we have tackled the outstanding inventory planning problems over new product launching period in a more holistic manner by addressing first the definition of efficient business rules to effectively control and reduce the inventory risks followed by the rigorous explanations on the implementation guide on suggested inventory planning rules. It is not unusual for many companies in the consumer electronics market to make a great effort to reduce the time to launch a new product because the ability to bring out higher performing products in such a short time period greatly increases the probability for them to remain competitive in the high tech market. Among so many newly developed products, those products with new features and technologies appeal to many potential customers while products which fail to win customers by design and prices rapidly disappear in the market. To adapt to this business environment, those companies have been trying to find the answer to minimize the inventory of old products so they can move to next generation products quickly with less obsolete material. In the experimental implementation of our rule-based inventory planning, Company 'S' reduced the inventory cost for the outgoing products as low as 49% of its peak level of its preceding product version in just 5 month after the adoption of rule-based inventory planning process and system. This paper concluded the subject with a suggestion that the best performance of rule-based inventory planning is guaranteed not from one-time campaign of process improvement along with system development but the decision maker's continuing support and attention even without seeing any upcoming business crisis.

• 산업경영시스템학회지
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• 제15권25호
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• pp.63-74
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• 1992

This study proposes D- shortage control system which is a convenient tool for cooperative companies to reduce shortages which frequently break out between the manufacturing companies and the cooperative companies. On the ground of theoretical analysis of MRP and JIT system, D- shortage control system sets up a schedule that secures the delivery date by precedent scheduling( D-) comparing with MRP It also syncronizes business, production and release, and builds the pull system comparing with JIT. The factors causing shotages are the scheduling absurdity and the controlling absurdity. The scheduling absurdity can be settled by the calculating required quantity method of MRP and the controlling absurdity can be settled by daily control of business, production and pruchasing fuctions by the pull system of JIT. And the inventory and the WIP can be reduced by the operating of PULL system and by the settlement of D- shortage control practices. The Application of D- shortage control system, therefore, enables the rationalization of logistics and reduces the inventory And it leads to the reinforced competitiveness and the security of subsistence of manufacturer by the cost ruduction, the reduction of financial difficulty, and the insurance of the delivery date.

• 산업공학
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• 제16권1호
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• pp.111-116
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• 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.

• 한국건축시공학회지
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• 제5권4호
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• pp.153-164
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• 2005

This study aims at establishing JIT production management system to enable manage the resources input into from procurement through construction based on correct identification of the process, an analysis on the amount of input materials and information sharing. This study has focused on the process control and working process of rebar work in domestic apartment house construction where the overall scope of Process from the planning phase to the construction phase has been analyzed in this study. Also construction phase was selected for the application of a sample case. A basic model for JIT production was generated with these processes. Furthermore A questionnaire and the on-site survey with process, checklist and control data were prepared and performed for the application of JIT production management model into rebar work. The governing scopes of JIT production management system include process management, material management, yard loading and moving management and inventory control, and the operation of each control item

• 산업경영시스템학회지
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• 제43권3호
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• pp.61-67
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• 2020

The fourth industrial revolution encourages manufacturing industry to pursue a new paradigm shift to meet customers' diverse demands by managing the production process efficiently. However, it is not easy to manage efficiently a variety of tasks of all the processes including materials management, production management, process control, sales management, and inventory management. Especially, to set up an efficient production schedule and maintain appropriate inventory is crucial for tailored response to customers' needs. This paper deals with the optimized inventory policy in a steel company that produces granule products under supply contracts of three targeted on-time delivery rates. For efficient inventory management, products are classified into three groups A, B and C, and three differentiated production cycles and safety factors are assumed for the targeted on-time delivery rates of the groups. To derive the optimized inventory policy, we experimented eight cases of combined safety stock and data analysis methods in terms of key performance metrics such as mean inventory level and sold-out rate. Through simulation experiments based on real data we find that the proposed optimized inventory policy reduces inventory level by about 9%, and increases surplus production capacity rate, which is usually used for the production of products in Group C, from 43.4% to 46.3%, compared with the existing inventory policy.