• Industrial Engineering and Management Systems
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• v.4 no.2
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• pp.158-164
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• 2005

Kusukawa and Ohta presented the $CS_{CQ-r}$ chart to monitor the process defect $rate{\lambda}$ in high-yield processes that is derived from the count of defects. The $CS_{CQ-r}$ chart is more sensitive to $monitor{\lambda}$ than the CQ (Cumulative Quantity) chart proposed by Chan et al.. As a more superior chart in high-yield processes, we propose a Synthetic chart that is the integration of the CQ_-r chart and the $CS_{CQ-r}$chart. The quality characteristic of both charts is the number of units y required to observe r $({\geq}2)$ defects. It is assumed that this quantity is an Erlang random variable from the property that the quality characteristic of the CQ chart follows the exponential distribution. In use of the proposed Synthetic chart, the process is initially judged as either in-control or out-of-control by using the $CS_{CQ-r}$chart. If the process was not judged as in-control by the $CS_{CQ-r}$chart, the process is successively judged by using the $CQ_{-r}$chart to confirm the judgment of the $CS_{CQ-r}$chart. Through comparisons of ARL (Average Run Length), the proposed Synthetic chart is more superior to monitor the process defect rate in high-yield processes to the stand-alone $CS_{CQ-r}$ chart.

• Journal of Korean Institute of Industrial Engineers
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• v.32 no.2
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• pp.126-132
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• 2006

Recently, business environments have been changing quickly. To establish competitive advantage, most enterprises have been using information systems such as Enterprise Resource Planning (ERP), Supply Chain Management (SCM) and Customer Relationship Management (CRM). Many consider Business Process Management (BPM) a new innovative solution for enterprise-wide processes. As the BPM system is used more widely and matures, new techniques and functions will be developed by commercial vendors. However, they mainly focus on correctly executing process models, and user convenience has not been considered. In this paper, we have developed a new method of designing business processes, which provides users with an easy modeling interface. The method is based on version management. Version management of a process enables a history of the process model to be recorded. In order to prevent wasted storage, not all of the process versions are stored. An initial version and changes to each process are stored by automatically detecting changes. Our method enhances the convenience of the modeling business processes and thus helps the process designer. A prototype system is presented to verify the effectiveness of our method.

• Biotechnology and Bioprocess Engineering:BBE
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• v.11 no.5
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• pp.432-441
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• 2006

2D fluorescence sensors produce a great deal of spectral data during fermentation processes, which can be analyzed using a variety of statistical techniques. Principal component analysis (PCA) and a self-organizing map (SOM) were used to analyze these 2D fluorescence spectra and to extract useful information from them. PCA resulted in scores and loadings that were visualized in the score-loading plots and used to monitor various fermentation processes with recombinant Escherichia coli and Saccharomyces cerevisiae. The SOM was found to be a useful and interpretative method of classifying the entire gamut of 2D fluorescence spectra and of selecting some significant combinations of excitation and emission wavelengths. The results, including the normalized weights and variances, indicated that the SOM network is capable of being used to interpret the fermentation processes monitored by a 2D fluorescence sensor.

• Journal of international Conference on Electrical Machines and Systems
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• v.2 no.4
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• pp.380-389
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• 2013

Application of linear electric motors to automation of manufacturing processes, gantry robots, machining processes, machining centers, additive manufacturing and laser scribing has been discussed. The paper focuses on replacement of ball lead screw mechanisms with linear electric motors, linear motor driven positioning stages, linear motor driven gantries, machining centers, machining of large objects and industrial lasers. The best linear electric motors for application to machining processes are permanent magnet (PM) linear synchronous motors (LSMs), especially those without PMs in the reaction tail, e.g., high thrust density linear (HDL) LSMs and PM flux switching (FS) LSMs.

• Journal of Korean Institute of Industrial Engineers
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• v.19 no.4
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• pp.49-70
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• 1993

The purpose of this study was to develop a semigenerative process planning system for the turning processes required for rotational parts. The system developed in this study showed three major roles for a given part : selection of appropriate turning processes, scheduling of selected processes, and selection of appropriate tools to be used for selected processes. Four information files and six modules were developed to produce a process plan. When geometric features, dimension, tolerance, material types, and surface finish data are inputted to the system, optimal processes, processing sequences, selected tools, and machining costs are to be produced as a process plan.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.34 no.4
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• pp.57-65
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• 2011

Monitoring auto correlated processes is prevalent in recent manufacturing environments. As a proactive control for manufacturing processes is emphasized especially in the semiconductor industry, it is natural to monitor real-time status of equipment through sensor rather than resultant output status of the processes. Equipment's sensor data show various forms of correlation features. Among them, considerable amount of sensor data, statistically autocorrelated, is well represented by Box-Jenkins autoregressive moving average (ARMA) model. In this paper, we present a design method of statistical process control (SPC) used for monitoring processes represented by the ARMA model. The proposed method shows benefits in the power of detecting process changes, and considers robustness to ARMA modeling errors simultaneously. We prove benefits through Monte carlo simulation-based investigations.

• Korean Chemical Engineering Research
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• v.44 no.5
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• pp.425-434
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• 2006

The operability and productivity of continuous processes, especially in petrochemical industries have made remarkable improvement during the past twenty years through advanced process control (APC) typified by model-based predictive control. On the other hand, APC have not been actively practiced in industrial batch processes typified by batch polymerization reactors. Perhaps the main cause for this has been the lack of reliable batch process APC techniques that can overcome the unique problems in industrial batch processes. Recently, some noteworthy progress is being made in this area. New high-performance batch process control techniques that can accommodate and also overcome the unique problems of industrial batch processes have been proposed on the basis of iterative learning control (ILC). In this review paper, recent advancement in the batch process APC techniques are presented, with a particular focus on the variations of the so called Q-ILC method, with the hope that they are widely practiced in different industrial batch processes and enhance their operations.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.33 no.3
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• pp.184-191
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• 2010

In the environment of 450mm wafers production known as the next-generation semiconductor production process, one of the most significant features is the full automation over the whole manufacturing processes involved. The full automation system for 450mm wafer production will minimize the human workers' involvement in the manufacturing process as much as possible. In addition, since the importance of an individual wafer processing increases noticeably, it is necessary to develop more robust scheduling systems in the whole manufacturing process than so ever. The scheduling systems for the next-generation semiconductor production processes also should be capable of monitoring individual wafers and collecting useful data on them in real time. Based on the information gathered from these processes, the system should finally have a real-time scheduling functions controlling whole the semiconductor manufacturing processes. In this study, preliminary investigations on the requirements and needed functions for constructing the real time scheduling system and transforming manufacturing environments for 300mm wafers to those of 400mm are conducted and through which the next generation semiconductor processes for efficient scheduling in a clustered production system architecture of the scheduler is proposed. Our scheduling architecture is composed of the modules for real-time scheduling, the clustered production type supporting, the optimal scheduling and so on. The specifications of modules to define the major required functions, capabilities, and the relationship between them are presented.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.40 no.4
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• pp.29-37
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• 2017

This papers focuses on remanufacturing processes in a closed loop supply chain. The remanufacturing processes is considered as one of the effective strategies for enterprises' sustainability. For this reason, a lot of companies have attempted to apply remanufacturing related methods to their manufacturing processes. While many research studies focused on the return rate for remanufacturing parts as a control parameter, the relationship with demand certainties has been studied less comparatively. This paper considers a closed loop supply chain environment with remanufacturing processes, where highly fluctuating demands are embedded. While other research studies capture uncertainties using probability theories, highly fluctuating demands are modeled using a fuzzy logic based ambiguity based modeling framework. The previous studies on the remanufacturing have been limited in solving the actual supply chain management situation and issues by analyzing the various situations and variables constituting the supply chain model in a linear relationship. In order to overcome these limitations, this papers considers that the relationship between price and demand is nonlinear. In order to interpret the relationship between demand and price, a new price elasticity of demand is modeled using a fuzzy based nonlinear function and analyzed. This papers contributes to setup and to provide an effective price strategy reflecting highly demand uncertainties in the closed loop supply chain management with remanufacturing processes. Also, this papers present various procedures and analytical methods for constructing accurate parameter and membership functions that deal with extended uncertainty through fuzzy logic system based modeling rather than existing probability distribution based uncertainty modeling.

• Journal of the Korean institute of surface engineering
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• v.55 no.6
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• pp.363-367
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• 2022

Transparent ZnO/Ti/ZnO (ZTZ) tri-layered films were prepared with radio frequency (RF) and direct current (DC) magnetron sputtering on the glass substrate. The thickness of the ZnO and Ti films was kept at 50 and 10 nm to consider the effect of the electron irradiation on the crystallization and optoelectrical properties of the films. From the XRD spectra, post-depostion electron irradiated films showed the characteristic peaks of ZnO(002) and Ti(200), respectively. the observed grain size of the ZnO(002) and Ti(200) enlarged up to 18.27 and 12.16 nm at an irradiation condition of 750 eV. In the figure of merit which means an optoelectrical performance of the films, as deposited films show a figure of merit of 2.0×10^-5 𝛺^-1, while the films electron irradiated at 750 eV show a higher figure of merit of 5.7×10^-5 𝛺^-1.