• 제어로봇시스템학회논문지
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• 제22권12호
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• pp.1040-1045
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• 2016

An inventory control system was developed for multiproduct batch plants with an arbitrary number of batch processes and storage units. Customer orders are received by the plant at intervals and in quantities that are subject to random fluctuations. The objective of the plant operation is to minimize the total cost while maintaining inventory levels within the storage or warehouse capacity by adjusting the startup times, the quantities of raw material orders, and production batch sizes. An adaptive model-based control algorithm was developed that uses a periodic square wave model to represent the flows of material between the processes and the storage units. The effectiveness of this approach was demonstrated by performing simulations.

• 산업경영시스템학회지
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• 제6권8호
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• pp.49-53
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• 1983

The purpose of this study is to consider models for the production planning of multiproduct. Because these multiproducts use common facilities, labor, and materials, they are able to be considered jointly instead of planned independently. Initially linear programming models will be considered, followed by some examples of modeling and analysis when the cost structure is nonlinear. Basic model components are the following ; (1) inventory balance equations for each product to link successive time periods, and (2) capacity constraints for each period to represent resource limitations.

• 한국경영과학회지
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• 제9권2호
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• pp.15-22
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• 1984

A deterministic multiproduct, facility-in series multiperiod production planning model is analyzed, where each period demand for the product of a facility appear in a fixed proportion of that for the product of the immediately following facility. The model considers concave production and inventory costs, which can depend upon the production in different facilities. No backlogging is allowed. It is shown that the model is represented via a single source network, which facilitates development of efficient dynamic programming algorithms for computing the optimal production schedule.

• 제어로봇시스템학회논문지
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• 제9권9호
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• pp.727-735
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• 2003

The determination of completion time constitutes an important step in developing algorithms for short-term production scheduling. Existing completion time algorithms of multi-product batch processes often assume that intermediate storage tanks are always available when it is needed. In this paper, we consider a serial multi-product batch plants with ZW and NIS policy intermediate storge tank. We limit storage residence time and allocated products in the intermediate storage tank to minimize the quality change of the stored material as well as to reduce the clearing time during product change. A set of recurrence relations is suggested to calculate the completion times for the given batch sequence of products on all processing units. Also analytic solution for the suggested model is solved by a graphical method. The effectiveness of these results is proved by a few illustrative examples.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1998년도 제13차 학술회의논문집
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• pp.455-460
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• 1998

We propose robust MILP model for scheduling and design of multiproduct batch processes in this paper. Recent stochastic modeling approaches considering uncertainty have mainly focused on maximization of expected NPV. Robust model concept is applied to generate solution spectrum in which we can select the best solution based on tradeoff between robustness measure and expected NPV. Robustness measure is represented as penalty term in the objective function, which is Upper Partial Mean of NPV. We can quantify solution robustness by this penalty term and maintain model as MILP form to be computationally efficient. An example illustrates the effectiveness of the proposed model. In many cases sufficient robustness can be guaranteed through a little reduction of expected NPV.

• 제어로봇시스템학회논문지
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• 제21권11호
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• pp.1076-1080
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• 2015

An inventory control system was developed for a distribution system consisting of a single multiproduct warehouse serving a set of customers and purchasing products from multiple vendors. Purchase orders requesting multiple products are delivered to the warehouse in a process. The receipt of customer orders by the warehouse proceeded in order intervals and in order quantities that are subject to random fluctuations. The objective of warehouse operation is to minimize the total cost while maintaining inventory levels within the warehouse capacity by adjusting the purchase order intervals and quantities. An adaptive model predictive control algorithm was developed using a periodic square wave model to represent the material flows. The adaptive concept incorporated a stabilized minimum variance control-type input calculation coupled with input/output stream parameter predictions. The effectiveness of the scheme was demonstrated using simulations.

• 한국정밀공학회:학술대회논문집
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• 한국정밀공학회 2010년도 춘계학술대회 논문집
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• pp.483-484
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• 2010

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1991년도 한국자동제어학술회의논문집(국제학술편); KOEX, Seoul; 22-24 Oct. 1991
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• pp.1718-1723
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• 1991

The determination of a production sequence is an important problem in a batch process operation. In this paper a new algorithm for a near optimal production sequence of N product in an M unit serial multiproduct batch process is proposed. The basic principle is the same as that of Johnson's algorithm for two-unit UIS system. Test results on a number of selected examples exhibit the superiority over previously reported results. In addition, a tabulation technique is presented to calculate the makespan of a given sequence of production for all processing units under UIS mode.

• 제어로봇시스템학회:학술대회논문집
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• 제어로봇시스템학회 1997년도 한국자동제어학술회의논문집; 한국전력공사 서울연수원; 17-18 Oct. 1997
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• pp.844-847
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• 1997

In this paper, scheduling problem is dealt for the minimization of due date penalty for the customer order. Multiproduct batch processes have been dealt with for their suitability for high value added low volume products. Their scheduling problems take minimization of process operation for objective function, which is not enough to meet the customer satisfaction and the process efficiency simultaneously because of increasing requirement of fast adaptation for rapid changing market condition. So new target function has been suggested by other researches to meet two goals. Penalty function minimization is one of them. To present more precisely production scheduling, we develop new scheduling model with penalty function of earliness and tardiness We can find many real cases that penalty parameters are divergent by the difference between the completion time of operation and due date. That is to say, the penalty parameter values for the product change by the customer demand condition. If the order charges different value for due date, we can solve it with the due date period. The period means the time scope where penalty parameter value is 0. If we make use of the due date period, the optimal sequence of our model is not always same with that of fixed due date point. And if every product have due date period, due date of them are overlapped which needs optimization for the maximum profit and minimum penalty. Due date period extension can be enlarged to makespan minimization if every product has the same abundant due date period and same penalty parameter. We solve this new scheduling model by simulated annealing method. We also develop the program, which can calculate the optimal sequence and display the Gantt chart showing the unit progress and time allocation only with processing data.

• 산업공학
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• 제6권1호
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• pp.99-112
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• 1993

This study deals with analysis of material from in Tube manufacturing line. This line is a multi product flow ship type production line, which consists of 5 steps of work station. Some work stations involve in unnecessary moving activities of workers and much work in-process storage due to the non-systematic material flow with respect to the different lot size production of multi-items. To improve productivity for this line, one alternative is considered such as grouping two work stations by using GT and JIT concepts. Also, feasibility analysis for this alternative is performed using and simulation model built by SIMAN IV simulation language.