• Journal of the Korean Society of Manufacturing Process Engineers
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• v.21 no.7
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• pp.1-9
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• 2022

Peeling and dimensional deformation that occur during a manufacturing process are accompanied by an increase in the manufacturing cost and production time caused by manufacturing defects. In order to solve this problem, it is essential to predict risk factors at the design stage through computational analysis of the additive manufacturing process and to control shape distortion due to residual stress. In this study, the dimensional characteristics were improved by applying the distortion compensation design through computational analysis to minimize the distortion occurring in the DMLS(Direct Metal Laser Sintering) method of the metal additive manufacturing process.

• Journal of Korea Society of Industrial Information Systems
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• v.8 no.1
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• pp.1-8
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• 2003

There are many statistical evaluation methods, A more technical Perspective is needed in estimating the effect of the Manufacturing Process for improving the Productivity, Process network analysis is a technique which has the potentiality for a wire use to improve the manufacturing process which other techniques can't be used to analyze effectively. The concept of six sigma plan was developed and pursued by Motorola to improve the process control. The goals of six sigma plan are established on the foundation of customer satisfaction such as Quality, Cost Delivery and Service This paper presents how to improve the manufacturing process by statistical process control for the evaluation of six sigma level.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.26 no.1
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• pp.7-16
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• 2003

At present, company has to produce a product that consumer like with a competitive price, a good quality, and a fitting time to supply. Process control and quality control are very important to supply with a product uniformly and inexpensively. Process control is given much weight in the quality control in manufacturing system. Statistical process controls(SPC) that are used in process generally have major impact on manufacturing, product design activities, and process development potentially. Control charts in statistical process control method can be interpreted the data from quality characteristics in production process and discriminated between chance variation and assignable variation in process. In addition, control chart can be used to monitor the process output and detect when changes in the inputs are required to bring the process back to an in-control state. The models that relate the influential inputs to process outputs help determine the nature and magnitude of the adjustments required. In this paper, the characteristic of product quality is monitored by control chart during the machining process and construction of quality control cycle is considered to divide into two types in this case that different assignable causes lead to shifts having different magnitudes. Then we are intended to find a process shift magnitude which has economical quality cost policy and are considered to quality cost functions to find a process shift magnitude. Those costs are categorized into the well-known categories of prevention, appraisal, and internal failure and external failure. This paper ends with numerical examples that demonstrate the usefulness of the model.

• 제어로봇시스템학회:학술대회논문집
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• 1990.10a
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• pp.186-189
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• 1990

The automization of manufacturing lines may be accomplished by replacing the human operator with computer system. This paper describes an idea to fully automize the razor qrinding process. Now, in this system, to control the process, human operator must estimate the qrinded states and control the grinding machine continuously. We propose two methods to automize this process by using CMAC memory. One is about learning expert-rules without direct communication with operator. And the other is complete self-learning method based on CMAC's learning algorithm. These ideas may be applied for another manufacturing processes.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2004.05a
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• pp.467-470
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• 2004

MANPro-based control is a novel control paradigm aimed at intelligent manufacturing systems on the basis of mobile agent-based negotiation process (MANPro). MANPro is a negotiation mechanism based on the agent-based control architecture and, especially, it adapts a mobile agent system called N-agent for the negotiation process. N-agent travels around the network of distributed manufacturing systems to acquire information, and it makes a decision for system control according to the obtained information. MANPro includes communication architecture and information architecture for intelligent shop floor control. MANPro also considers the following issues: (1) negotiation mechanism, (2) single-agent internal strategic policies, and (3) information model. Communication architecture concerns the first issue of the negotiation mechanism. It provides information exchanging mechanism with functional modules. In specific, N-agent is equipped with an intelligent reasoning engine with a built-in knowledge base. This reasoning engine is closely related to the single-agent internal strategic policies of the second issue. Finally, ontology-based information architecture addresses information models and provides a framework for information modeling on negotiation. In this paper, these three issues are addressed in detail and a framework of MANPro-based control is also proposed.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.2
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• pp.115-123
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• 2021

A lot of sensor and control signals is generated by an industrial controller and related internet-of-things in discrete manufacturing system. The acquired signals are such records indicating whether several process operations have been correctly conducted or not in the system, therefore they are usually composed of binary numbers. For example, once a certain sensor turns on, the corresponding value is changed from 0 to 1, and it means the process is finished the previous operation and ready to conduct next operation. If an actuator starts to move, the corresponding value is changed from 0 to 1 and it indicates the corresponding operation is been conducting. Because traditional fault detection approaches are generally conducted with analog sensor signals and the signals show stationary during normal operation states, it is not simple to identify whether the manufacturing process works properly via conventional fault detection methods. However, digital control signals collected from a programmable logic controller continuously vary during normal process operation in order to show inherent sequence information which indicates the conducting operation tasks. Therefore, in this research, it is proposed to a recurrent neural network-based fault detection approach for considering sequential patterns in normal states of the manufacturing process. Using the constructed long short-term memory based fault detection, it is possible to predict the next control signals and detect faulty states by compared the predicted and real control signals in real-time. We validated and verified the proposed fault detection methods using digital control signals which are collected from a laser marking process, and the method provide good detection performance only using binary values.

• Journal of the Korea Academia-Industrial cooperation Society
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• v.12 no.4
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• pp.1812-1816
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• 2011

This research developed chemical flow control system(CFCS) essential for spinner equipment in nano semiconductor manufacturing process under the 100nm to prevent complex process defect due to missing spread after chemical injection. The devices developed in this research, which can be swiftly replaced in case abnormal state element changes or wafer manufacturing defect occurs, are anticipated to improve module yield as well as real-time monitoring on the state element. In addition, as a result of mounting H/W and S/W system to control detailed operation sequence in production line and executing performance check and verification, we can be exactly detected in five abnomal process type.

• 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

• Transactions of the Korean Society of Mechanical Engineers A
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• v.20 no.3
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• pp.765-774
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• 1996

Computer Integrated Manufacturing(CIM) requires models of manufacturing processes to be implemented on the computer. These models are typically used for determining optimal process control parameters or designing adaptive control systems. In spite of the progress made in the mechanistic modeling, however, empirical models derived from experimental data play a maior role in manufacturing process modeling. This paper describes the development of a meural metwork medel for injection molding. This paper describes the development of a nueral network model for injection molding process. The model uses the CAE analysis data based on Taguchi method. The developed model is, then, compared with the traditional polynomial regression model to assess the applicabilit in practice.

• Proceedings of the Korean Operations and Management Science Society Conference
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• 2005.05a
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• pp.215-224
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• 2005

It is a fundamental requirement for the medium-sized manufacturing company with multiple-types of products and mixed process flows to have a real time feedback system for systematic production scheduling and process control to maximize the productivity and delivery achievement. However it is very inferior in actual condition to make infrastructure for a systematic production scheduling and process control in middle-sized manufacturing company, Proposed in this paper is an MES implementation approach for the successful construction of MES infrastructure, implementation and operation in medium-sized manufacturing companies with multiple-types of products and mixed process flows.