• Journal of Korean Society of Industrial and Systems Engineering
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• v.18 no.35
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• pp.95-106
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• 1995

This study is aimed at development a plan to strengthen the competitiveness in technology of small and medium manufacturing enterprises, which can be assumed mainly by small and medium manufacturing companies, to improve the competitiveness of domestic industry. To remove these obstacles and strengthen the technological competitiveness, internally it is required to change the attitude of management about the development and innovation of technology first. Promotion of favorable atmosphere for the technological development and organized activity to acquire technological information are additional requirements. In conclusion, to survive the competition and to secure national industrial competitiveness, each individual company needs to endeavor for technological innovation and improvement in product quality and productivity.

• Journal of Korean Institute of Industrial Engineers
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• v.23 no.3
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• pp.581-595
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• 1997

The procedure of grouping the machines and parts to form cells is called manufacturing cell design. The manufacturing cell design is an important step in the development and implementation of advanced manufacturing systems. For the successful implementation of the manufacturing systems, identification of independent manufacturing cells, i.e., cells where parts are completely processed in the cell and no intercell movements, is necessary in the design phase. In this paper, we developed a mixed integer programming model and genetic algorithm based procedure to solve the independent manufacturing cells design problem considering the alternative process plans and machines duplication. Several manufacturing parameters such as, production volume, machine capacity, processing time, number of cells and cell size, are considered in the process. The model determines the process plan for parts, port families and machine cells simultaneously. The model has been verified with the numerical examples.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.38 no.4
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• pp.149-158
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• 2015

Up-to-date manufacturing companies have faced a market-driven environment of pull production order. There should be a difference in operating manufacturing resources according to the type, quantity, and delivery time of manufactured products, because the process situation in pull production is changed by customer orders. And it should be taken into account from the stage of preparing for production such as process design and the placement and utilization of manufacturing resources. However, the feasibility of production plans is limited because most of small manufacturing businesses make production/supply plan of the parts and products assuming that equipment abilities in scheduling is sufficient without managing process standard information systemically. In this study, a discrete event simulation system based on BOM (bill of material), that is F-OPIS (online productivity innovation system), is introduced and a case study on application of the system leading to improving productivities is presented. F-OPIS deals with a decision-problem on production management and it is specialized for small-and- medium sized manufacturing companies. The target company of this case study is a typical small-and-medium sized manufacturing company in Korea, that produces various machined parts. The target company adopts make-to-stock production management to prevent tardy delivery because of fluctuations in demand. Therefore, it is required to apply an efficient inventory control solution for improving productivities. In this paper, based on the constraints of working capacity of manufacturing resources, the bottleneck process is analyzed as production conditions are changed. Consequently, an improvement plan is proposed, that eventually enhances overall utilization rates of resources in the bottleneck process and reduces overall production lead-time and inventory level.

• Journal of the Korean Society for Precision Engineering
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• v.26 no.1
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• pp.17-23
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• 2009

• Korean Journal of Computational Design and Engineering
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• v.11 no.2
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• pp.148-155
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• 2006

This paper presents a new method for assessing the efficiency of production process plans using tolerance chart to lower production cost. The tolerance chart is used to predict the accuracy of a part that is to be produced following the process plan, and to carry out the quantitative measurement on the efficiency of the process plan. By comparing the values of design tolerances and their corresponding resultant tolerances calculated using the tolerance chart, the process plan that is incapable of satisfying the design requirements and the faulty production operations can be identified. Similarly, the process plan that imposes unnecessarily high accuracy and wasteful production operations can also be identified. For the latter, a quantitative measure on the efficiency of the process plan is introduced. The higher the unnecessary cost of the production, the poor is the efficiency of the process plan. A coefficient is introduced for measuring the process plan efficiency. The coefficient also incorporates two weighting factors to reflect the difficulty of manufacturing operations and number of dimensional tolerances involved. To facilitate the identification of the machining operations and the machined surfaces, which are related to the unnecessarily tight resultant tolerances caused by the process plan, a rooted tree representation of the tolerance chart is introduced, and its use is demonstrated. An example is presented to illustrate the new method. This research introduces a new quantitative process plan evaluation method that may lead to the optimization of process plans.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2005.06a
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• pp.153-156
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• 2005

Real-time monitoring and controlling manufacturing process is important because of the unexpected events. When unexpected event like mechanical trouble occurs, prior plan becomes unacceptable and a new schedule must be generated though manufacturing schedule is already decided for order. Regenerating the whole schedule, however, spends much time and cost. Thus automated system which monitors and controls manufacturing process is required. In this paper, we present a system which uses radio-frequency identification and computer vision system. The system collect real-time information about manufacturing conditions and generates new schedule quickly with those information.

• Korean Management Science Review
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• v.10 no.2
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• pp.121-143
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• 1993

Traditional Manufacturing method is push system by plan made in advance and Japanese manufacturing method represented by JUST-IN-TIME is pull system which respond's to the demand flexibly. Both have their pros and cons. In general, it is well understood that push system is faster than pull system in the sense of manufacturing speed. However, pull system such as JIT excelles dramatically in the sense of work in process. Therefore, this paper is trying to put together to get alternative which has the advantage of both system. The objective of the paper is to enhance the effect of built-in manufacturing system without paying extra cost by way of introducing the alternative of the pull-push manufacturing strategic operational method.

• Journal of the Korean Society for Precision Engineering
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• v.8 no.1
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• pp.105-115
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• 1991

This paper describes an integrated CAD and CAPP system for prismatic parts of injection mold which generates a complete process plan automatically from CAD data of a part without human intervention. This system employs Auto CAD as a CAD model and GS-CAPP as an automatic process planning system for injection mold. The proposed CAD/CAPP system consists of three modules such as CAD data conversion module, manufacturing feature recognition module, and CAD/CAPP interface module. CAD data conversion module transforms design data of AutoCAD into three dimensional part data. Manufacturing feature recognition module extracts specific manufacturing features of a part using feature recognition rule base. Each feature can be recognized by combining geometry, position and size of the feature. CAD/CAPP interface module links manufacturing feature codes and other head data to automatic process planning system. The CAD/CAPP system can improve the efficiency of process planning activities and reduce the time required for process planning. This system can provide a basis for the development of part feature based design by analyzing manufacturing features.

• Design & Manufacturing
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• v.15 no.1
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• pp.48-56
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• 2021

The quality of products produced by injection molding process is greatly influenced by the process variables set on the injection molding machine during manufacturing. It is very difficult to predict the quality of injection molded product considering the stochastic nature of manufacturing process, because the process variables complexly affect the quality of the injection molded product. In the present study we predicted the quality of injection molded product using Artificial Neural Network (ANN) method specifically from Multiple Input Single Output (MISO) and Multiple Input Multiple Output (MIMO) perspectives. In order to train the ANN model a systematic plan was prepared based on a combination of orthogonal sampling and random sampling methods to represent various and robust patterns with small number of experiments. According to the plan the injection molding experiments were conducted to generate data that was separated into training, validation and test data groups to optimize the parameters of the ANN model and evaluate predicting performance of 4 structures (MISO1-2, MIMO1-2). Based on the predicting performance test, it was confirmed that as the number of output variables were decreased, the predicting performance was improved. The results indicated that it is effective to use single output model when we need to predict the quality of injection molded product with high accuracy.

• Journal of the Korea Safety Management & Science
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• v.12 no.1
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• pp.71-81
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• 2010

Today's fierce competition and global economic recession make most of manufacturing companies in the world difficult to gain a profit. In order to survive such a environment and increase competitiveness, manufacturing companies have to continuously eliminate their wasteful factors through an efficient process analysis, improve quality of products, increase the flexibility of manufacturing processes. In this paper, we consider a case study for the Shanghai New Auto which is a subcontractor of MOBIS in China, to improve productivity by using therblig method, one of the motion analysis, to minimize the work-in-process inventories and to shorten the manufacturing cycle times. We also try to relocate the facility layout to increase the efficiency and flexibility of manufacturing processes.