• IE interfaces
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• v.11 no.2
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• pp.159-176
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• 1998

In the motor manufacturing system with the properties of short delivery and order based production, the process plan is performed individually for each order by the expert of process plan after the completion of the detail design process to satisfy the specification to be required by customer. Also it is hard to establish the standard process plan in reality because part routings and operation times are varied for each order. Hence, the production planner has the problem that is hard to establish the production schedule releasing the job to the factory because there occurs the big difference between the real time to be completed the process plan and the time to be required by the production planner. In this paper, we study the decision supporting system for the process plan based on knowledge base concept. First, we represent the knowledge of process planner as a database model through the modified POI-Feature graph. Then we design and implement the decision supporting system imbedded in the heuristic algorithm in the client/server environment using the ORACLE relational database management system.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.8 no.4
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• pp.924-929
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• 2007

This paper introduces a simulation model regarding the process analysis of a LED assembly process. The objective of the simulation model is to evaluate the performance of various design aspects of process alternatives. To develop the simulation model, a time study is performed for each process. Next, by using ARENA, a simulation model is conducted based on the process analysis and the line balancing methodology. We found out several problems for the assembly process, and then suggest several alternatives to improve the system.

• Journal of the Korean Society for Precision Engineering
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• v.12 no.3
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• pp.82-91
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• 1995

The purpose of this research is to develop a new real-time process control system. In this paper, a theoretical method for acquiring the control limit of cutting process(cutting surface) according to the required value(geometric tolerance) based on geometrical relations was propsed. In particular, the three following points are amphasized. Firstly, the process control was based on the cutting process, and the control limit was determined from the analysis of geometrical relations. Secondly, AMGD(Actual Measured Geometrical Deviation) was used as a new substitute value in process analysis. Thirdly, fuzzy reasoning was introduced to get the control limit flexibility according to the variations in the required value and general consideration of each measurememnt items.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.4
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• pp.144-150
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• 2005

Gas-assisted injection molding (GAIM) process is reducing the injection pressure during mold filling required as well as the shrinkage and warpage of the part and cycle time. Despite of these advantages, this process introduces new parameters and makes the application more difficult because the process interacts between gas and melt during injection molding process. Important GAIM factors that involved in this process include gas penetration design, locations of gas injection points, shot size, gas injection delay time as well as common injection molding parameters, gas pressure and gas injection time. In this study, the experiments were conducted to investigate effects of GAIM process variables on the gas penetration for PP and ABS moldings by changing gas injection point. Taguchi method was used fer the design of experiment. When the gas was injected at cavity's center, the most effective factor was shot size. When the gas was injected at cavity's end, the most effective factor was melt temperature. Injection speed was also an effective factor in GAIM process.

• Journal of the Korean Society for Precision Engineering
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• v.22 no.6 s.171
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• pp.222-231
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• 2005

Recently, life cycle and lead-time of products have been shortened with the demand of customers. Therefore, it is important to reduce time and cost at the stage of manufacturing trial molds. In order to realize a three-dimensional shape on CAD, the machining process has been widely used because it offers practical advantages such as precision and versatility. However, the traditional machining process needs a large amount of time in cutting a product and the remained material causes trouble such as inconvenience for clarity. In this work, a new rapid manufacturing process using the hot tool, Rapid Heat Ablation process, has been developed to overcome such limitations. While the hot tool moves the predetermined path, the heat of the tool decomposes the remained material. The radius of heat affect ed zone related to process parameters was investigated through experiments to improve the quality of ablated parts. In order to examine the applicability of the proposed process, three-dimensional shapes such as hemisphere and standard test part, wereablatedutilizingtheapparatus.

• Journal of the Korea Safety Management & Science
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• v.24 no.4
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• pp.149-156
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• 2022

Manufacturing process mining performs various data analyzes of performance on event logs that record production. That is, it analyzes the event log data accumulated in the information system and extracts useful information necessary for business execution. Process data analysis by process mining analyzes actual data extracted from manufacturing execution systems (MES) to enable accurate manufacturing process analysis. In order to continuously manage and improve manufacturing and manufacturing processes, there is a need to structure, monitor and analyze the processes, but there is a lack of suitable technology to use. The purpose of this research is to propose a manufacturing process analysis method using process mining and to establish a manufacturing process mining system by analyzing empirical data. In this research, the manufacturing process was analyzed by process mining technology using transaction data extracted from MES. A relationship model of the manufacturing process and equipment was derived, and various performance analyzes were performed on the derived process model from the viewpoint of work, equipment, and time. The results of this analysis are highly effective in shortening process lead times (bottleneck analysis, time analysis), improving productivity (throughput analysis), and reducing costs (equipment analysis).

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.11 no.4
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• pp.327-333
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• 1998

The influence of slow cooling and annealing time in $O_2$in MPEG process on $J_c$ was investigated. From the measurement of $J_c$,SEM and XRD, it was observed that the critical current density was related with the slow cooling time and annealing time in $O_2$. The value of $J_c$ was the highest at slow cooling time of 40 hour. And also, the value of $J_c$ along the annealing time in $O_2$in the case of the slow cooling time of 40 hours was inclined to increase with annealing time. Consequently, it can be suggested that proper slow cooling time and annealing time after slow cooling in MPMG process be important to improve the critical characteristics.

• IE interfaces
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• v.21 no.4
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• pp.418-434
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• 2008

This paper studied issues in decision making on the production control policy of a cathode plate manufacturing process in zinc refining plant. The present production system has a long lead time from raw materials (aluminum plate) to products (cathode plate) due to many WIP inventories. Because WIP inventories are stocked at each process and moved from one place to another frequently, they are the main cause of inefficiency in the process. In this paper, to solve this problem, several production control policies have been identified and studied. Several simulation models are used to compare the performances of these production control policies. The output lead time and WIP (Work In Process) of real production system are compared with those of simulation models. PUSH, CONWIP, DBR, KANBAN and CONWIP-DBR models have been used to simulate and review the optimized production control policy that achieves the target output quantities with decreased lead time and WIP. The simulation results of each production control policy show that CONWIP and CONWIP-DBR models are the good production control policy under the present production system. Especially in present production system, CONWIP with one parameter is easier control policy than CONWIP-DBR with two parameters. Therefore CONWIP has been selected as the best optimum production control policy. With CONWIP, lead time has been reduced by 97% (from 6,653 to 187 minute) and WIP has been reduced from 1,488 to 53, compared to the present system.

• IE interfaces
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• v.20 no.3
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• pp.288-297
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• 2007

Success of semiconductor/LCD industry depends on its yield and quality of product. For the purpose, FDC (Fault Detection and Classification) system is used to diagnose fault state in main manufacturing processes by monitoring time series data collected by equipment sensors which represent various conditions of the equipment. The data set is segmented at the start and end of each product lot processing by a trigger event module. However, in practice, segmented sensor data usually have the features of data asynchronization such as different start points, end points, and data lengths. Due to the asynchronization problem, false alarm (type I error) and missed alarm (type II error) occur frequently. In this paper, we propose a robust process fault detection system by integrating a process event detection method and a similarity measuring method based on dynamic time warping algorithm. An experiment shows that the proposed system is able to recognize abnormal condition correctly under the asynchronous data situation.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.9 no.3
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• pp.76-82
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• 2010

A laborer always watched a process of production carefully but defective manufactures were inspected after press process. These inspections made a waste of human power and defective manufactures could make a serious damage of press mold. Therefore, AE(Acoustic Emission) system was introduced to prevention of the damage of the press molds, to a real time detection of defective manufactures and to save human power. AE system was introduced to solve this problem which is a detecting defective manufacture on real time and to prevent the damage of the press mold. In this research we get acoustic emission signal in accordance with weight and processing method of press by using AE sensor, Preamplifier, AE board signal board which occurs press processing and it analyzed various signal through using CMD8 software on the time. From the result, we found that the intensity and shape of the signal were changed according to the weight and processing type of the press. By using this special algorithm, it can judge the acoustic signal which occurs from press on real time.