• 한국정밀공학회지
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• 제12권5호
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• pp.136-148
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• 1995

In this study, a model integration method is pressented as a new method for development of a parametric simulation model. This method enable us to integrate the special simulation models for each production subsystem into a large simulation model. Not only this large simulation model but also each special simulation model for each production subsytem can be used independently. Using this integration method man can reduce the development time and cost for simulation model development. To show the usefulness of this method, a simulation model for a production system with robots is developed by this model integration method. This simulation model is realized by the integration of two special simulation models, one model for a machining subsystem and the other model for a transport subsystem. The modeled production system consists of the robotic cells for machining and a transport subsystem which enable the material flow among the robotic cells. The flow of workpiece in each robotic cell is not fixed. All machines in a robotic cell are only served by robots.

• 한국경영과학회:학술대회논문집
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• 한국경영과학회 1993년도 추계학술대회발표논문집; 서강대학교, 서울; 25 Sep. 1993
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• pp.175-184
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• 1993

Modeling the production process is a necessary and essential aspect of the production planning. This paper introduces a theoretical model of the multi-stage production process. A multi-stage production process is regarded as a network of interrelated production activities which use system exogenous inputs of goods in production and the intermediate products transfers between activities to produce final products. Our model is characterized by (1) a few of the production-related assumptions and (2) two types of elements "goods and activities" that are represented in terms of the network terminology. This model is different from the another multi-stage production models, so-called production network models in relation to the production-theoretical concept. It is not based on the concept of the production correspondence and the activity production functions, but the technology model of Koopmans. Koopmans.

• 한국시뮬레이션학회논문지
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• 제11권4호
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• pp.69-80
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• 2002

This study deals with the productivity improvement on a flow production system with the consideration of line-balancing. In a flow production system, similar product models are produced on a same assembly line, the predefined process order and the limitation of total worker number. The system can be increased the work-in -process(WIP) inventory and the worker's idle time. In this study, the worker assignment model is developed to assign evenly workload of process to each product model in such a manner that each process has the different number of worker. This worker assignment model is the mathematical model that determines worker number in each process such that the idle time of processes is reduced and the utilization of worker is improved. We use a simulation technique to simulate the production line proposed by the mathematical model and apply real production line. With the result of simulation, this study analyzes the propriety of production line and proposes the alternatives of new production line

• 소성∙가공
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• 제26권4호
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• pp.240-245
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• 2017

Mixed-model production technology is a method of producing multiple products with one production process and production line in order to reduce wasted manpower and adjust to market trends. In other words, mixed-model production is a flexible production system that changes production volume by model according to market demand. This study has developed a progressive laminated stamping die technology to enable flexible production of a motor core consisting of attaching and detaching the Cam on the back of the punch so that two kinds of stator and two kinds of rotor could be produced in one progressive die.

• 산업경영시스템학회지
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• 제18권36호
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• pp.93-103
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• 1995

This paper des with an economic production quantity model with partial backorders for the situation in which production lead time is deterministic and demand during lead time follows a continuous distribution. In the model, an objective function is formulated In minimize an average annual inventory cost. And then the procedure of iterative solution method for the model is developed to find both production reorder point and production quantity. Finally, sensitivity analysis for various partial backorder ratios and standard deviations of demand during production lead time are presented.

• Fisheries and Aquatic Sciences
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• 제24권4호
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• pp.139-152
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• 2021

The main purpose of this study is to fit catch-per-unit-effort (CPUE) data about Korea chub mackerel (Scomber japonicus) stock with a state-space production (SSP) model, and to provide stock assessment results. We chose a surplus production model for the chub mackerel data, namely annual yield and CPUE. Then we employed a state-space layer for a production model to consider two sources of variability arising from unmodelled factors (process error) and noise in the data (observation error). We implemented the model via script software ADMB-RE because it reduces the computational cost of high-dimensional integration and provides Markov Chain Monte Carlo sampling, which is required for Bayesian approaches. To stabilize the numerical optimization, we considered prior distributions for model parameters. Applying the SSP model to data collected from commercial fisheries from 1999 to 2017, we estimated model parameters and management references, as well as uncertainties for the estimates. We also applied various production models and showed parameter estimates and goodness of fit statistics to compare the model performance. This study presents two significant findings. First, we concluded that the stock has been overexploited in terms of harvest rate from 1999 to 2017. Second, we suggest a SSP model for the smallest goodness of fit statistics among several production models, especially for fitting CPUE data with fluctuations.

• 한국생산제조학회지
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• 제23권6호
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• pp.602-608
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• 2014

Mixed-model production lines are often used in manufacturing systems. In production lines, different product types are simultaneously manufactured by processing small batches. This paper describes a new welding assembly technology involving the development of experimental models for a mixed-model production line in an automobile company. Due to the extensive number of models, the design of a welding assembly system is complicated. Performance evaluation is an important phase in the design of welding assembly lines in a mixed-model production environment. In this study, a new welding assembly technology for a mixed-model production method was used to weld the package tray and dash panel of a vehicle.

• Ocean and Polar Research
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• 제34권2호
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• pp.185-195
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• 2012

This paper focused on forecasting a short-term production of oysters, which have been farmed in Korea, with distinct periodicity of production by year, and different production level by month. To forecast a short-term oyster production, this paper uses monthly data (260 observations) from January 1990 to August 2011, and also adopts several econometrics methods, such as Multiple Regression Analysis Model (MRAM), Seasonal Autoregressive Integrated Moving Average (SARIMA) Model, and Vector Error Correction Model (VECM). As a result, first, the amount of short-term oyster production forecasted by the multiple regression analysis model was 1,337 ton with prediction error of 246 ton. Secondly, the amount of oyster production of the SARIMA I and II models was forecasted as 12,423 ton and 12,442 ton with prediction error of 11,404 ton and 11,423 ton, respectively. Thirdly, the amount of oyster production based on the VECM was estimated as 10,425 ton with prediction errors of 9,406 ton. In conclusion, based on Theil inequality coefficient criterion, short-term prediction of oyster by the VECM exhibited a better fit than ones by the SARIMA I and II models and Multiple Regression Analysis Model.

• 경영과학
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• 제32권4호
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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.

• 산업공학
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• 제24권3호
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• pp.241-247
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• 2011

This paper develops a mathematical model which searches an optimum lot size of a press line, and applies this model to the scheduling of the press line. This mathematical model is not a widely studied cost model but a model which considers the utilization of the press line under a lean production system. In this paper, the optimum lot size is a minimum lot size which does not exceed the total work time of the press line. A production volume and the priority of the production in the press line are adjusted using this optimum lot size. A mathematical model developed in this paper will allow determining the optimum lot size easily in case of variable production environments such as an introduction of a new product and a fluctuation of production volume of each item. Therefore, our model will make a better scheduling of the press line and will enhance the utilization of it.