• 대한임베디드공학회논문지
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• 제14권5호
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• pp.259-267
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• 2019

This paper proposes a structure of a variable impedance control system based on sensor-less external force estimator of industrial manipulators for cyber physical production systems (CPPS). To implement CPPS, a feedback system is constructed by using the robot operating system (ROS) and an external force estimator which is designed to measure the external force applied to the manipulator without a force sensor. Based on the robot dynamics, the robot-human cooperating system for the cyber physics production system is implemented through a controller that changes the impedance characteristics of the manipulator according to the situation using the external force estimator. Simulation and experimental results verify the effectiveness of the proposed control system.

• 산업경영시스템학회지
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• 제43권1호
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• pp.143-150
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• 2020

To enhance the effectiveness of the FMS (flexible manufacturing system), it is necessary for the manufacturing control system to be upgraded by integrating the cyber and the physical manufacturing systems. Using the CPPS (Cyber-Physical Production System) concept, this study proposes a 4-stage vertical integration and control framework for an aircraft parts manufacturing plant. In the proposed framework, the process controller prepares the operations schedule for processing work orders generated from the APS (advanced planning & scheduling) system. The scheduled operations and the related control commands are assigned to equipments by the dispatcher of the line controller. The line monitor is responsible for monitoring the overall status of the FMS including work orders and equipments. Finally the process monitor uses the simulation model to check the performance of the production plan using real time plant status data. The W-FMCS (Wing rib-Flexible Manufacturing Control & Simulation) are developed to implement the proposed 4-stage CPPS based FMS control architecture. The effectiveness of the proposed control architecture is examined by the real plant's operational data such as utilization and throughput. The performance improvement examined shows the usefulness of the framework in managing the smart factory's operation by providing a practical approach to integrate cyber and physical production systems.

• 실천공학교육논문지
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• 제13권3호
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• pp.483-490
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• 2021

본 논문에서는 스마트팩토리 기반의 CPPS(Cyber Physical Production System) 및 VR(Virtual Reality) 기술을 활용한 스마트팩토리 통합 기술 교육 플랫폼 개발과 플랫폼을 활용한 교육 방법들을 제안하였다. 3D 디지털 트윈과 연동이 가능하며 BOP(Bill of Process) 기반의 제조 공정을 통합하는 방법을 학습할 수 있도록 플랫폼을 개발하였다. 또한 디지털 트윈은 OPC-UA 서버를 통해 메카니컬 시스템과 디지털 트윈 뿐만 아니라 가상 현실까지 연계하여 통합 스마트팩토리 기반의 교육 플랫폼을 구축하였다. 이러한 플랫폼을 기반으로 스마트팩토리 통합 플랫폼은 BOP 기반 디지털 트윈 시뮬레이션, OPC-UA 통합, MES 시스템, SCADA 시스템, VR 연동으로 스마트팩토리 통합 플랫폼의 개별 요소들을 가지도록 제안하였다.

• 한국정보시스템학회지:정보시스템연구
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• 제26권2호
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• pp.105-121
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• 2017

Purpose It is a major goal to improve the product yields during production operations in the manufacturing industry. Therefore, factory is trying to keep the good quality materials and proper production resources, also find the proper condition of facilities and manufacturing environment for yields improvement. Design/methodology/approach We propose the hybrid framework to analyze to dataset extracted from MES. Those data is about the alarm information generated from equipment, both measurement and equipment process value from production and cycle/pitch time measured from production data these covered products during production. We adapt a data warehousing techniques for organizing dataset, a logistic regression for finding out the significant factors, and a association analysis for drawing the rules which affect the product yields. And then we validate the framework by applying the real data generated from the discrete process in secondary cell battery manufacturing. Findings This paper deals with challenges to apply the full potential of modeling and simulation within CPPS(Cyber-Physical Production System) and Smart Factory implementation. The framework is being applied in one of the most advanced and complex industrial sectors like semiconductor, display, and automotive industry.