• Journal of Korean Institute of Industrial Engineers
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• v.23 no.2
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• pp.249-260
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• 1997

The manufacturing environment is rife with nonlinear processes. In this context, an intelligent production controller should be able to predict the dynamic behavior of various subsystems as they react to transient environmental conditions, the varying internal condition of the manufacturing plant, and the changing demands of the production schedule. This level of adaptive capability may be achieved through a coherent methodology for a learning coordinator to predict nonlinear and stochastic processes. The system is to serve as a real time, online supervisor for routine activities as well as exceptional conditions such as damage, failure, or other anomalies. The complexity inherent in a learning coordinator can be managed by a modular architecture incorporating case based reasoning. In the interest of concreteness, the concepts are presented through a case study involving a knowledge based robotic system.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.10 no.16
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• pp.39-51
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• 1987

This paper deals with the case analysis of second order processes under sampled-data. Proportional Integral-Derivative(PID) control, and development of Decision Support Systems(DSS) for such processes. In this paper three techniques were described for identifying the dynamics of closed loop stable processes. The first, called pulse testing is a frequency-domain method, which yields the frequency response diagram of an open loop process. The second is a time-domain method which yields the gain and time constants of the process model. The third technique is based on step response and gives the parameters of PID controllers. The development of DSS design programs consisting of above three techniques will provide very powerful tools in the microcomputer based process control.

• Industrial Engineering and Management Systems
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• v.2 no.1
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• pp.63-70
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• 2003

In this study, we employed an arithmetic process (AP) approach to resolve gearbox maintenance problems. The approach is realistic and direct in modelling the characteristics of a deteriorating system such as a gearbox since a decreasing AP can model a gearbox's successive operating times and an increasing AP can model the corresponding consecutive repair times. First of all, two test statistics were used to check whether the process is arithmetic or not. Next, model parameters of the AP were estimated using the simple linear regression method. Finally, the optimal replacement policy based on minimising the long-run average cost per day was determined for each type of gearbox.

• Journal of Korean Society of Occupational and Environmental Hygiene
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• v.7 no.2
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• pp.181-195
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• 1997

The purpose of this study was to investigate factors affecting the composition and concentrations of fumes generated from various types of welding processes. The results are as follows. 1. Iron(Fe), zinc(Zn) and manganese(Mn) were predominant in Welding fumes. The Fe content in total fumes was 25.5% in coated electrode and 28.2% in $CO_2$ are welding, and the Zn content was 4.5% and 9.1%, respectively, and the Mn was 3.6% and 7.8%, respectively. 2. It was found that the important factors determining composition and concentration of fumes were type of industries, type of welding processes, type and composition of electrodes, composition of base metals, confinement of workplaces or condition of ventilation, work intensity, coated metals such as lead and Zn in paint. 3. The Mn content in airborne fumes was highly correlated with that of electrode(r=0.77, p<0.01) and was about 4 times higher than that in electrodes or base metals. The results lindicate that Mn is well evaporated into air during welding. The higher vapor pressure of Mn may explain this phenomenon. 4. the airborne total fume concentrations were significantly different among types of industries(p<0.001). The airborne total fume concentration was higher in order of sleel-structure manufacturing($GM=15.1mg/m^3$), shipbuilding($GM=13.2mg/m^3$), automobile-component manufacturing ($GM=7.8mg/m^3$) and automobile assembling industry($GM=3.0mg/m^3$) 5. The airbone total fume concentration was 6 times higher in $CO_2$ welding than in coated electrode welding, and approximately 3 times higher in confined area than in open area, in steel-structure manufacturing industry. 6. The concentration of welding fume outside welding helmet was about 2 times higher than that inside it. It is recommened that air sampling be done inside helmet to evaulate worker's exposure accurately, for it has an outstanding effect on reducing worker exposure to fumes and other contaminants.

• Journal of Information Technology Applications and Management
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• v.23 no.3
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• pp.13-23
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• 2016

In recent years, big data has usefully been deployed by organizations with the aim of getting a better prediction for the future. Moreover, knowledge management systems are being used by organizations to identify and create knowledge. Here, the output from analysis of big data and a knowledge management system are used to develop a new model with the goal of minimizing the cost of implementing new recognized processes including staff training, transferring and employment costs. Strategies are proposed from big data analysis and new processes are defined accordingly. The company requires various skills to execute the proposed processes. Organization's current experts and their skills are known through a pre-established knowledge management system. After a gap analysis, managers can make decisions about the expert arrangement, training programs and employment to bridge the gap and accomplish their goals. Finally, deduction graph is used to analyze the model.

• Journal of the Korea Safety Management & Science
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• v.9 no.4
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• pp.99-112
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• 2007

In most recent years, the business competition has spreads over all fields of corporations and their management area regardless of time and place, which makes the survival environment of each enterprise fiercer. In order to secure a high position in the competitive market, the various firms has implemented many methods related to price, quality, and service efficiency. However, the implementation with only low price or high quality might be helpless to hold a high position in modem market. Moreover more attention should be paid to the internal business processes of an organization. Therefore, a new and different method should be searched or developed in order to win the competitive power among other enterprises. This research will focus on the improvement of the business processes within the non-manufacturing industry by applying Lean Six Sigma methodology. DMAIC method will be applied to improve the inbound and outbound logistics processes, manage the inbound and outbound vehicles, and control the receiving and shipping activities.

• Journal of Korean Institute of Industrial Engineers
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• v.39 no.6
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• pp.577-586
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• 2013

In a shipyard, it is hard to predict block movement due to the uncertainty caused during the long period of shipbuilding operations. For this reason, block movement is rarely scheduled, while main operations such as assembly, outfitting and painting are scheduled properly. Nonetheless, the high operating costs of block movement compel task managers to attempt its management. To resolve this dilemma, this paper proposes a new block movement analysis framework consisting of the following operations: understanding the entire process, log clustering to obtain manageable processes, discovering the process model and detecting exceptional processes. The proposed framework applies fuzzy mining and trace clustering among the process mining technologies to find main process and define process models easily. We also propose additional methodologies including adjustment of the semantic expression level for process instances to obtain an interpretable process model, definition of each cluster's process model, detection of exceptional processes, and others. The effectiveness of the proposed framework was verified in a case study using real-world event logs generated from the Block Process Monitoring System (BPMS).

• Journal of Radiation Industry
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• v.2 no.1
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• pp.43-51
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• 2008

Radiation technology is currently used in a number of industrial processes such as sterilization, cross linking of polymer, food irradiation, rubber vulcanization in the tire manufacturing, contaminated medical waste, etc. Gamma ray and electron beam are the key examples of well-established economical applications of radiation processes. The purpose of this paper is to review the recent technological trends and activities for radiation processes in order for the industrial end users to better understand, and obtain useful information about the technology. It is clear that the radiation processing technology has potential for a variety of the industrial applications.

• Industrial Engineering and Management Systems
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• v.14 no.1
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• pp.88-93
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• 2015

In this paper, we identify the characteristics of modeling and simulation (M&S) for military and defense and propose the method of verification, validation, and accreditation (VV&A) using the identified characteristics. M&S has been widely used for many different applications in military and defense, including training, analysis, and acquisition. Various methods and processes of VV&A have been proposed by researchers and M&S practitioners to guarantee the correctness of M&S. The notion of applying formal credibility assessment in VV&A originated in software engineering reliability testing and the systems engineering development process. However, the VV&A techniques and processes proposed for M&S by the research community have not addressed the characteristics and issues specific to military and defense. We first identify the characteristics and issues of military/defense M&S and then propose techniques and methods for VV&A that are specific for military/defense M&S. Possible approaches for the development of VV&A are also proposed.

• Environmental Engineering Research
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• v.22 no.3
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• pp.266-276
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• 2017

A life cycle impact assessment was applied in an industrial waste incineration plant to evaluate the direct and indirect environmental impacts based on toxicity and non-toxicity categories. The detailed life cycle inventory of material and energy inputs and emission outputs was compiled based on the realistic data collected from a local industrial waste incineration plant, and the Korean life cycle inventory and ecoinvent database. The functional unit was the treatment of 1 tonne of industrial waste by incineration and the system boundary included the incineration plant and landfilling of ash. The result on the variation of the impact by the unit processes showed that the direct impact was decreased by 79.3, 71.6, and 90.1% for the processes in a semi dry reactor, bag filter, and wet scrubber, respectively. Considering the final impact produced from stack, the toxicity categories comprised 91.7% of the total impact. Among the toxicity impact categories, the impact in the eco-toxicity category was most significant. A separate estimation of the impact due to direct and indirect emissions showed that the direct impact was 97.7% of the total impact. The steam recovered from the waste heat of the incineration plant resulted in a negative environmental burden.