• Journal of Korean Institute of Industrial Engineers
• /
• v.22 no.4
• /
• pp.719-739
• /
• 1996

A common control model used to implement computer integrated manufacturing(CIM) is based on the hierarchical decomposition of the shop floor activities, in which supervisory controllers are responsible for all the interactions among subordinates. Although the hierarchical control philosophy provides for easy understanding of complex systems, an emerging manufacturing paradigm, agile manufacturing, requires a new control structure necessary to accommodate the rapid development of a shop floor controller. This is what is called autonomous agent-based heterarchical control. As computing resources and communication network on the shop floor become increasingly intelligent and powerful, the new control architecture is about to come true in a modern CIM system. In this paper, heterarchical control is adopted and investigated, in which a controller for a unit of device performs three main functions - planning, scheduling and execution. Attention is paid to the planning function and all the detailed planning activities for heterarchical shop floor control are identified. Interactions with other functions are also addressed. In general, planning determines tasks to be scheduled in the future. In other words, planning analyzes process plans and transforms process plans into detailed plans adequate for shop floor control. Planning is also responsible for updating a process plan and identifying/resolving replanning activities whether they come from scheduling or execution.

• Journal of Korean Society for Quality Management
• /
• v.22 no.4
• /
• pp.79-101
• /
• 1994

In modern manufacturing, a product consists of many components created by different processes. Variations in the individual component dimensions and in the processes may result in unacceptable final assemblies. Thus, engineers have increased pressure to properly set tolerance specifications for individual components and to control manufacturing processes. When a proper variation stack-up analysis is not performed for all of the components in a functional system, all component parts can be within specifications, but the final assembly may not be functional. Thus, in order to improve the performance of the final assembly, a proper variation stack-up analysis is essential for specifying dimensional tolerances and process control. This research provides a detailed case example of the use of variation stack-up analysis using a Monte Carlo simulation method to improve the defect rate of a complex process, which is the commutator brush track undercut process of an armature assembly of a small motor. Variations in individual component dimensions and process mean shifts cause high defect rate, Since some dimensional characteristics have non-normal distributions and the stack-up function is non-linear, the Monte Carlo simulation method is used.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.32 no.2
• /
• pp.132-139
• /
• 2009

Yield is a very important measure that can expresses simply for productivity and performance of company. So, yield is used widely in many industries nowadays. With the development of the information technology and online based real-time process monitoring technology, many industries operate the production lines that are developed into automation system. In these production lines, the product structures are very complexity and variety. So, there are many multi-variate processes that need to be monitored with many quality characteristics and associated process variables at the same time. These situations have made it possible to obtain super-large manufacturing process data sets. However, there are many difficulties with finding the cause of process variation or useful information in the high capacity database. In order to solve this problem, neural networks technique is a favorite technique that predicts the yield of process for process control. This paper uses a neural networks technique for improvement and maintenance of yield in manufacturing process. The purpose of this paper is to model the prediction of a sub process that has much effect to improve yields in total manufacturing process and the prediction of adjustment values of this sub process. These informations feedback into the process and the process is adjusted. Also, we show that the proposed model is useful to the manufacturing process through the case study.

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2008.06a
• /
• pp.527-528
• /
• 2008

• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2007.06a
• /
• pp.425-426
• /
• 2007

• Journal of the Korean Society of Industry Convergence
• /
• v.22 no.2
• /
• pp.235-241
• /
• 2019

The shoe manufacturing process is very low compared to other industries due to the labor-intensive process. As automation and smart factories are becoming more and more automated, changes in the shoe manufacturing process are also needed. In this paper, we want to standardize the fuse manufacturing process by modularizing it. First, we defined the terms of shoeupper and fuse process, the shoe upper fuse process by function and classified it as a modular process. The fuse process can be modularized with pattern supply module, pattern recognition module, pattern laminate module, pattern waiting module, adhesion module, heat pressing module, transmission module, etc.

• Journal of the Korean Institute of Plant Engineering
• /
• v.23 no.4
• /
• pp.29-38
• /
• 2018

Through process quality information, the time required for process quality analysis has been drastically shortened, the process defect rate has been reduced, and the manufacturing lead time has been shortened and the on-time delivery rate has been improved. Therefore, The purpose of this study is to develop a quality information analysis system model that effectively shortens the time required for process quality analysis in automobile safety belt parts manufacturing process. As a result of experiments on communication operation between manufacturing execution system (MES) quality server, injection machine control computer, injection machine programmable logic controller (PLC) and terminal, in analyzing quality information, the conventional handwriting input method took an average of 20 minutes, but the new multi-network method took about 2 minutes on average. In addition, the process defect rate was reduced by 13% and the manufacturing lead time was shortened from 28 hours to 20 hours. The delivery compliance rate improved from 96 to 99%.

• Journal of Korean Society of Industrial and Systems Engineering
• /
• v.43 no.1
• /
• pp.143-150
• /
• 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.

• The Transactions of The Korean Institute of Electrical Engineers
• /
• v.57 no.11
• /
• pp.2054-2060
• /
• 2008

This paper aims at the performance enhancement of tension controller for the yarn manufacturing process. The tension controller is required to keep the tension constant while the yarn is manufactured by a draw and twist machine, which is essential and critical for good quality production of yarn, steel, paper, etc. This paper proposes a linear model of tension control plant to develop a precise tension control system, which is derived by the close observation of the conventional mathematical model of motor driving and tension control systems. It is shown by experiments that the proposed control system precisely maintains the tension constant within the error bound of 0.05% while the conventional PI controller has about 0.2% error. The control performance of the system has been compared to that of conventional PI control not only for constant speed control but also for transient speed control experiments.

• Journal of the Korean Institute of Intelligent Systems
• /
• v.15 no.2
• /
• pp.264-269
• /
• 2005

Advances in sensors, actuators, and computers and developments In information systems offer unprecedented opportunities to implement highly ambitious automation, control and decision strategies. There are also new challenges and demands for control and automation in modern industrial practices. There is a growing need for an active participation from the information systems in industrial, manufacturing and process industry environments because currently there are many control problems. This paper provides pattern recognition to the monitoring system for solvent manufacturing process and shows performance in real-time response with multiple input signals. Data is teamed by a multilayer feedforward network trained by error-backpropagation. The two kinds of test results show that the trained network has the ability to show the current system status with different input data sets.