• Journal of the Korean Society of Manufacturing Process Engineers
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• v.20 no.4
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• pp.66-72
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• 2021

Since the behavior of an autonomous underwater vehicle (AUV) is influenced by disturbances and moments that are not accurately known, the depth control law of AUVs must have the ability to track the input signal and to reject disturbances simultaneously. Here, we proposed robust tracking control for controlling the depth of an AUV. An augmented closed-loop system is represented by an error dynamic equation, and we can easily show the asymptotic stability of the overall system by using a Lyapunov function. The robust tracking controller is consisted of the internal model of the command signal and a state feedback controller, and it has the ability to track the input signal and reject disturbances. The closed-loop control system is robust to parameter uncertainties. Simulation results showed the control performance of the robust tracking controller to be better than that of a P + PD controller.

• International Journal of Precision Engineering and Manufacturing
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• v.1 no.2
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• pp.124-131
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• 2000

A shop floor can be considered as and importand level to develop a Computer Integrated Manufacturing system (CIMs). The shop foor is a dynamic environment where unexpected events contrinuously occur, and impose changes to planned activities. The shop floor should adopt an appropriate control system that is responsible for scheduling coordination and moving the manufacturing material and information flow. In this paper, the architecture of the hybrid control model identifies three levels; i.e., the shop floor controller (SFC), the cell controller(CC) and the equipment controller (EC). The methodology for developing these controller is employ an object-oriented approach for static models and IDEF0 for function models for dispatching a job. SFC and CC are coordinated by employing a multi-factors bidding and an adapted Analytic Hierarchy Process(AHP) prove applicability of the suggested method. Test experiment has been conducted by with the shopfloor, consisting of six manufacturing cells.

• Industrial Engineering and Management Systems
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• v.4 no.1
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• pp.54-67
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• 2005

This paper provides an evaluation of an optimization-based, multiple-input double-output (MIDO) run-to-run (R2R) control scheme for general semiconductor manufacturing processes. The controller in this research, termed adaptive dual response optimizing controller (ADROC), can serve as a process optimizer as well as a recipe regulator between consecutive runs of wafer fabrication. In evaluation, it is assumed that the equipment model could be appropriately described by a pair of second-order polynomial functions in terms of a set of controllable variables. Of practical relevance is to consider a drifting effect in the equipment model since in common semiconductor practice the process tends to drift due to machine aging and tool wearing. We select a typical application of R2R control to chemical mechanical planarization (CMP) in semiconductor manufacturing in this evaluation, and there are five different CMP process scenarios demonstrated, including mean shift, variance increase, and IMA disturbances. For the controller, ADROC, an on-line estimation technique is implemented in a self-tuning (ST) control manner for the adaptation purpose. Subsequently, an ad hoc global optimization algorithm based on the dual response approach, arising from the response surface methodology (RSM) literature, is used to seek the optimum recipe within the acceptability region for the execution of next run. The main components of ADROC are described and its control performance is assessed. It reveals from the evaluation that ADROC can provide excellent control actions for the MIDO R2R situations even though the process exhibits complicated, nonlinear interaction effects between control variables, and the drifting disturbances.

• 제어로봇시스템학회:학술대회논문집
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• 2001.10a
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• pp.133.4-133
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• 2001

In the paper, a Visual factory model for a optical-components manufacturing process is built. The optical-components manufacturing process is composed of 3 operation processes; optical sub assembly process, package assembly process, and fiber assembly process. Each process is managed not a batch mode, which is one of most popular manufacturing styles to produce a great deal of industrial output, but though a modular cell. In the processes, a modular cell has to be processed independently of the other cells. Optimization for the composition of assembly cell in the optical-components system is made by the Visual factory model.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.17 no.5
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• pp.161-172
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• 2018

This paper proposed the robot vision control method to track a moving rigid body target using the vision system model that can actively control camera parameters even if the relative position between the camera and the robot and the focal length and posture of the camera change. The proposed robotic vision control scheme uses a batch method that uses all the vision data acquired from each moving point of the robot. To process all acquired data, this robot vision control scheme is divided into two cases. One is to give an equal weight for all acquired data, the other is to give weighting for the recent data acquired near the target. Finally, using the two proposed robot vision control schemes, experiments were performed to estimate the positions of a moving rigid body target whose spatial positions are unknown but only the vision data values are known. The efficiency of each control scheme is evaluated by comparing the accuracy through the experimental results of each control scheme.

• The Journal of Bigdata
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• v.1 no.1
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• pp.41-51
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• 2016

Big data is an emerging issue as large data which was impossible to be processed in the past is possible to be handled with the development of information and communication technology. Manufacturing is the most promising field that big data is applied such that there are abundant data available. It is important to improve an efficiency of manufacturing process for quality control and production efficiency because the processes from production design, sales, productions and so on are mixed intricately. This study proposes big data cloud service for manufacturing analysis using a big data technology and a process mining technique. It is expected for manufacturing corporations to improve a manufacturing process and reduced the cost by applying the proposed service. The service provides various analyses including manufacturing analysis and manufacturing duration analysis. Big data cloud service has been implemented and it has been validated by conducting a case study.

• Proceedings of the Korean Society for Technology of Plasticity Conference
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• 2007.05a
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• pp.379-382
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• 2007

The MEMS (Micro Electro Mechanical Systems) process is used in a micro/nano pattern manufacturing method. This method is based on the lithography technology. But the MEMS process has some problems such as complicated process, long processing time and high production costs. Many researchers are doing research in substitute manufacturing method to work out a solution to these problems. In this paper, we apply a dieless incremental forming technology to a substitute method of MEMS process. This dieless forming technology is using in the commercial scale sheet forming such as a prototype of automobile sheet parts. 5-axes CNC (Computerized Numeric Control) method are applied in this system to get a micro-scale dieless forming results. These 5-axes system are composed of precision AC servo motor stages (4-axes) and PZT actuator (1-axis). A PZT actuator is used in a precision actuating axis because it can be operated in the nano scale stroke resolution. This micro dieless incremental forming system has the advantage of minimization in manipulating distance and working space. As equipment and tools become smaller in size, minute inertia force and high natural frequency can be obtained. Therefore, high precision forming performance can be obtained. This allows the factory to quickly provide the customer with goods because the manufacturing system and process are reduced. To construct this micro manufacturing system, many technologies are necessary such as high stiffness frame, high precision actuating part, structural analysis, high precision tools and system control. To achieve the optimal forming quality, the micro dieless forming system is designed and made with high stiffness characteristic.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.17 no.2
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• pp.47-53
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• 2018

Nowadays, additive manufacturing (AM) technology is a promising process to fabricate complex shaped devices applied in medical and dental services. Among the AM processes, a DLP (digital light processing) type 3D printing process has some advantages, such as high precision, relatively low cost, etc. In this work, we propose a simple method to fabricate precise dental models using a DLP 3D printer. After 3D printing, a part is commonly post-cured using secondary UV-curing equipment for complete polymerization. However, some shrinkage occurs during the post-curing process, so we adaptively control the UV-exposure time on each layer for over- or under-curing to change the local shape-size of a part in the DLP process. From the results, the shrinkage amounts in the post-curing process vary due to the UV-dose in 3D printing. We believe that the proposed method can be utilized to fabricate dental models precisely, even with a change of the 3D CAD model.

• Journal of the Korean Society of Manufacturing Process Engineers
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• v.10 no.3
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• pp.19-27
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• 2011

A weaving machine for texture industry uses a lot of needles and the nib of these needles is necessary to be kept with sharp edge. The re-grinding of the needle by a special purpose of the grinding wheel can be selected for achieving this aim. This study focused on the manufacture and performance assessment the special grinding wheel. A forming mold for the grinding wheel was designed and a sintering process for furnace process control was established. Manufactured wheels were tested for determining suitable grade of the wheel. The selection of optimal grinding conditions was achieved by a response surface method and a genetic algorithm.

• IE interfaces
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• v.10 no.1
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• pp.15-22
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• 1997

In semiconductor manufacturing, the probe process between fabrication and assembly process is constrained mostly by the equipment capacity because most products pass through the similar procedures. The probe process is usually performed in a batch mode with relatively short cycle times. The capability of the probe process can be determined by the optimal combination of the equipments and the products. A probe line usually has several types of equipment with different capacity. In this study, the probe line is modeled in terms of capacity to give the efficient planning and control procedure. For the practical usage, the hierarchical capacity planning procedure is used. First, a monthly capacity plan is made to meet the monthly production plan of each product. Secondly, the daily capacity planning is performed by considering the monthly capacity plan and the daily fabrication output. Simple heuristic algorithms for daily capacity planning are developed and some experimental results are shown.