• Proceedings of the Korea Society of Design Studies Conference
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• 2001.10a
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• pp.22.1-22
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• 2001

• Journal of Welding and Joining
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• v.27 no.2
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• pp.57-62
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• 2009

This research was carried out to improve the productivity in the subassembly process of shipbuilding through optimal work planning for the shortest work time. The work time consist of welding time, moving time of gantry, teaching time of robot and robot motion time. The shortest work time is accomplished by even distribution of work and the shortest welding sequence. Even distribution of work was done by appling the simple algorithm. The shortest work sequence was determined by using GA. The optimal work planning decreased the total work time of the subassembly process by 4.1%. The result showed the effectiveness of the suggested simple algorithm for even distribution of work and GA for the shortest welding sequence.

• Journal of the Korean Institute of Electrical and Electronic Material Engineers
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• v.17 no.7
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• pp.701-707
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• 2004

High aspect ratio silicon structure through deep silicon etching process have become indispensable for advanced MEMS applications. In this paper, we present the results of modified Bosch process to obtain anisotropic silicon structure with conventional Inductively Coupled Plasma (ICP) etcher instead of the expensive Bosch process systems. In modified Bosch process, etching step ($SFsub6$) / sidewall passivation ($Csub4Fsub8$) step time is much longer than commercialized Bosch scheme and process transition time is introduced between process steps to improve gas switching and RF power delivery efficiency. To optimize process parameters, etching ($SFsub6$) / sidewall passivation ($Csub4Fsub8$) time and ion energy effects on etching profile was investigated. Etch profile strongly depends on the period of etch / passivation and ion energy. Furthermore, substrate temperature during etching process was found to be an important parameter determining etching profile. Test structures with different pattern size have been etched for the comparison of the aspect ratio dependent etch rate and the formation of silicon grass. At optimized process condition, micropatterns etched with modified Bosch process showed nearly vertical sidewall and no silicon grass formation with etch rate of 1.2 ${\mu}{\textrm}{m}$/ min and the size of scallop of 250 nm.

• Korean Chemical Engineering Research
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• v.50 no.5
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• pp.830-836
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• 2012

Dead times appear often in describing process dynamics and raise some difficulties in simulating process dynamics or analyzing process control systems. To relieve these difficulties, it is needed to approximate the infinite dimensional dead time by the finite dimensional transfer function and, for this, the Pade approximation method is often used. For the accurate approximation of the dead time, high order Pade approximation is needed and the high order Pade approximation is not easy to memorize and is not stable numerically. We propose a method based on the continued fraction expansion that provides the same transfer functions. The method is excellent numerically as well as systematic to be memorized easily. It can be used conveniently for the process control lecture and computations.

• Design & Manufacturing
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• v.14 no.4
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• pp.25-39
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• 2020

In this study, an edge device that monitors the injection molding process by measuring the mold vibration(acceleration) signal and the mold surface temperature was developed and evaluated its performance. During injection molding, signals of the injection start, V/P switchover, and packing end sections were obtained through the measurement of the mold vibration and the injection time and packing time were calculated by using the difference between the times of the sections. Then, the mold closed and mold open signals were obtained using a magnetic hall sensor, and cycle time was calculated by using the time difference between the mold closed time each process. As a result of evaluating the performance by comparing the process data monitored by the edge device with the shot data recorded on the injection molding machine, the cycle time, injection time, and packing time showed very small error of 0.70±0.38%, 1.40±1.17%, and 0.69±0.82%, respectively, and the values close to the actual were monitored and the accuracy and reliability of the edge device were confirmed. In addition, it was confirmed that the mold surface temperature measured by the edge device was similar to the actual mold surface temperature.

• Proceedings of the Korean Institute of Intelligent Systems Conference
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• 2001.12a
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• pp.83-86
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• 2001

In injection molding, short shot is one of the frequent and fatal defects. Experts of injection molding usually adjust process conditions such as injection time, mold temperature, and melt temperature because it is the most economic way in time and cost. However it is a difficult task to find appropriate process conditions for troubleshooting of short shot as injection molding process is a highly nonlinear system and process conditions are coupled. In this paper, a fuzzy neural network(FNN) has been applied to injection molding process to shorten troubleshooting time of short shot. Based on melt temperature and fill time, a reasonable initial mold temperature is recommended by the FNN, and then the mold temperature is inputted to injection molding process. Depending on injection molding result, specifically the insufficient quantity of an injection molded part, an appropriate mold temperature is recommend repeatedly through the FNN.

• Proceedings of the Korean Society of Precision Engineering Conference
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• 2000.11a
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• pp.653-657
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• 2000

The paper describes the contents and results of the national project named "Development of Computer Integrated Product Design for Automation Equipment". It is focussed on the real-time control '||'&'||' monitoring of manufacturing process for automobile rubber parts. Automobile rubber parts industy is one of the typical process that high11 depends upon manufacturing facilities and equipments. So. it requires high cost and engineering technolog) on plant implementation. But most companies of rubber parts industries are small or mid companies that habe weak abilities for plant implementation properly and systematically. Therefore, for upgrading the levelof automation. it is necessar). to dekelope the computer based management and monitoring slsteni that enables to build-up the common base of automation and systemization. 'Through this project. we developed low cost real-time monitoring system for banbun mixing process '||'&'||' mold injection process of rubbcr parts manufacturing, that is composed with DDCU(Distributed Digital Control Unit),signal interfaces to gathering mon~toring terms and speciall\ developed functional sofhare including some algorithm for management '||'&'||' process monitoring

• Journal of Korean Society of Industrial and Systems Engineering
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• v.42 no.4
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• pp.145-152
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• 2019

All machines deteriorate in performance over time. The phenomenon that causes such performance degradation is called deterioration. Due to the deterioration, the process mean of the machine shifts, process variance increases due to the expansion of separate interval, and the failure rate of the machine increases. The maintenance model is a matter of determining the timing of preventive maintenance that minimizes the total cost per wear between the relation to the increasing production cost and the decreasing maintenance cost. The essential requirement of this model is that the preventive maintenance cost is less than the failure maintenance cost. In the process mean shift model, determining the resetting timing due to increasing production costs is the same as the maintenance model. In determining the timing of machine adjustments, there are two differences between the models. First, the process mean shift model excludes failure from the model. This model is limited to the period during the operation of the machine. Second, in the maintenance model, the production cost is set as a general function of the operating time. But in the process mean shift model, the production cost is set as a probability functions associated with the product. In the production system, the maintenance cost of the equipment and the production cost due to the non-confirming items and the quality loss cost are always occurring simultaneously. So it is reasonable that the failure and process mean shift should be dealt with at the same time in determining the maintenance time. This study proposes a model that integrates both of them. In order to reflect the actual production system more accurately, this integrated model includes the items of process variance function and the loss function according to wear level.

• Journal of Intelligence and Information Systems
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• v.6 no.2
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• pp.29-40
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• 2000

Process planning (selection and ordering of processes) and material selection for product manufacturing are two key things determined before taking full-scale manufacturing. Knowledge on product design. material characteristics, processes, time and cost all-together are mutually related and should be considered concurrently. Due to the complexity of problem, human experts have got only one of the feasilbe solutions with their field knowledge and experiences. We propose a hierarchical expert system framework of knowledge representation and reasoning in order to overcome the complexity. Manufacturing processes have inherently hierarchical relationships, from top level processes to bottom level operation processes. Process plan of one level is posted in process blackboard and used for lower level process planning. Process information on blackboard is also used to adjust the process plan in order to resolve the dead-end or inconsistency situation during reasoning. Decision variables for process, material, tool, time and cost are represented as object frames, and their relationships are represented as constraints and rules. Constraints are for relationship among variables such as compatibility, numerical inequality etc. Rules are for causal relationships among variables to reflect human expert\`s knowledge such as process precedence. CRSP(Constraint and Rule Satisfaction Problem) approach is adopted in order to obtain solution to satisfy both constraints and rules. The trade-off procedure gives user chances to see the impact of change of important variables such as material, cost, time and helps to determine the preferred solution. We developed the prototype system using visual C++ MFC, UNIK, and UNlK-CRSP on PC.

• Journal of Industrial Technology
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• v.18
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• pp.139-148
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• 1998

Traditionally, the problems of manufacturing technology and manufacturing management have been treated independently. In this research, we endeavor to integrate the process planning and scheduling activities as an attempt to integrate the two realms. To draw up a plan of process planning and scheduling in real manufacturing environment is not an easy task because available time to plan could be limited and the shop status could change frequently. So we propose an architecture of integrated process planing and scheduling problem within the allowed time even if sheep situations change rather frequently. We argue that we can obtain a better and practical scheduling solution by dynamically changing the processing machines and operations as the shop condition changes. The proposed system takes the initial information for alternative machines and operations represented by an AND/OR graph as its input. Other informational inputs to the system are part order and shop statues. The system then generates new process plan and schedules during permitted time. Experimental results show that the proposed scheme provides a viable solution for real world scheduling problems.