• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.23 no.1
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• pp.75-82
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• 2014

For accurate gain tuning of the lab-manufactured six-axis articulated robot RS2 with less noise, in this study, a program routine using dynamic signal analyzer, which is a realization of a controller design algorithm in the frequency domain, is programmed using LabVIEW$^{(R)}$. The contribution of this paper is the proposal of a simulation technique based on SolidWorks$^{(R)}$ and LabVIEW$^{(R)}$ for the gain tuning of a six-axis articulated robot. To realize the simulation, the LabVIEW$^{(R)}$ program used for experimental gain tuning is incorporated in to SolidWorks$^{(R)}$. A comparison shows that the results of simulation-based gain tuning and experimental gain tuning are almost the same within a 5% error bound. On the basis of the comparison, it can be suggested that the simulation-based technique for gain tuning can be applied instead of experimental gain tuning to a six-axis articulated robot by interlocking SolidWorks$^{(R)}$ and LabVIEW$^{(R)}$.

• Journal of the Korean Society of Manufacturing Technology Engineers
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• v.19 no.3
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• pp.359-364
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• 2010

The objective of this study is to propose an effective method for measurement and analysis of fatigue crack. A technique that can measure the statue of fatigue crack propagation fast and correctly for enhancing safety of constructions and securing reliability is necessary. Moreover, the crack propagation behavior characteristics evaluation technique has to be developed using this technique. In this paper, fatigue crack was caused via the fatigue experiment with repeated load on the CT specimen that is made up of STS304. Fatigue crack propagation was measured by tracing the position of the maximum temperature according to the cycles using infrared thermography. The crack growth characteristics was evaluated by applying the moment values on the measuring area to the measured value. As a result of this study, the possibility that the infrared thermography could be applied to measure the fatigue crack was identified. Moreover, it was identified that fatigue crack propagation have a relationship with the moment value of construction.

• 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 Korea Contents Association Conference
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• 2008.05a
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• pp.198-202
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• 2008

Manufacturing process of large-scale 3D computer animation is becoming sophistication, ramification because of development of manufacturing technique and extravagant budget. Form of manufacturing pipeline has been variously changed to production type, manufacturing scale, manufacturing form. But it is time that renewed discussion is needed because change and development for the organization is insufficient in small manufacturing company. The project aims to try to help understanding for manufacturing pipeline of internal small-scale 3D animation and to find a plan of organization for internal small-scale production of the real situation. Organization model and methodology of manufacturing pipeline of small manufacturing company is not absolute because it is enough possible to be changed to inclination of the project and its environment. People must fully understand the purpose for organization of manufacturing pipeline of 3D computer animation and it must be organized to the situation for small-scale production so that every worker in production can share the information perfectly.

• Journal of the Korea Safety Management & Science
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• v.15 no.4
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• pp.171-178
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• 2013

Workers are avoiding production/manufacturing sites due to the poor working environment and concern over safety. Small and medium-sized businesses introduce new equipment to secure safety in the production site or ensure effective process management by introducing the real-time monitoring technique for existing equipment. The importance of real-time monitoring of equipment and process in the production site can also be found in the ANSI/ISA-195 model. Note, however, that most production sites still use paper-based work slip as a process management technique. Data reliability may deteriorate because information on the present condition of the production site cannot be collected/analyzed properly due to manual data writing by the worker. This paper introduces the monitoring and process management technique based on a direct facility interface to secure safety in the field by improving the poor working environment and enhance there liability and real-time characteristics of the production data. Since the data is collected from equipment in real-time directly through the SIB-based interface and PLC-based interface, problems associated with workers' manual data input are expected to be solved; safety can also be improved by enhancing workers' attention to work by minimizing workers' injuries and disruption.

• Asia pacific journal of information systems
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• v.14 no.1
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• pp.143-163
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• 2004

Management is under constant pressures to achieve competitiveness in production in most manufacturing companies. The adoption of management techniques(MT) such as TQM, MRP, ERP and so on has been a logical response for better performance to many companies. Besides, these companies commonly adopt a number of such techniques with high expectation for performance improvement. However, expected improvement in performance is not guaranteed unless necessary ingredients exist for those techniques. Many research studies have focused on the nature of successful adoption of management techniques in the past. However, most studies have been related to a single technique and its effects. When more than one techniques are in use in a company, focusing on a single technique limits the value of analysis. This paper focuses the value of MTs adopted in a company in multiplicity and compares the relative characteristics of MTs one another. Especially, the purpose of this paper is to examine the comparative nature of MTs adopted In manufacturing companies and the elements of MT success in relationship with information systems and organizational adjustment for adoption of MTs. The result of the analysis shows that the more efforts are exhorted for the adjustment of information systems and organizational structures to accommodate the MTs, the more success from the adopted techniques results. However, the extent of adjustment for different management techniques differs one another due to the nature of each technique. With regard to the comparative impact of adjustment of information systems and that of organizational structures, the result shows that the latter has more direct and greater impact than the former.

• Journal of Conservation Science
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• v.36 no.6
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• pp.483-493
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• 2020

In this paper, we present a nondestructive analysis using X-ray and microscopic investigation to detect the structure, manufacturing technique and preservation status of the Goryeo lacquered box Inlaid with Mother-of-pearl Chrysanthemum and Scroll Design (Goryeo Lacquered Box). We confirm that the Goryeo Lacquered Box consists of the soft wood as the basic material. The soft wood was coated with textile and then lacquered. The box structure of the Goryeo Lacquered Box was formed of wooden boards with wood plants added to the side, after processing into a trefoil-shaped. The wooden sides of the Goryeo Lacquered Box were cut at regular intervals for easier processing into a curved shape. Moter-of-pearl, tortoiseshell, and metal wire were used to decorate the surface. mother-of pearl was the cutting processing, and tortoiseshell was used for back coloring. The metal line was constructed using one line and twist line.

• Smart Media Journal
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• v.9 no.3
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• pp.31-40
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• 2020

Currently, black-box-based machine learning algorithms are used to analyze big data in manufacturing. This algorithm has the advantage of having high analytical consistency, but has the disadvantage that it is difficult to interpret the analysis results. However, in the manufacturing industry, it is important to verify the basis of the results and the validity of deriving the analysis algorithms through analysis based on the manufacturing process principle. To overcome the limitation of explanatory power as a result of this machine learning algorithm, we propose a manufacturing big data analysis method using genetic programming. This algorithm is one of well-known evolutionary algorithms, which repeats evolutionary operators such as selection, crossover, mutation that mimic biological evolution to find the optimal solution. Then, the solution is expressed as a relationship between variables using mathematical symbols, and the solution with the highest explanatory power is finally selected. Through this, input and output variable relations are derived to formulate the results, so it is possible to interpret the intuitive manufacturing mechanism, and it is also possible to derive manufacturing principles that cannot be interpreted based on the relationship between variables represented by formulas. The proposed technique showed equal or superior performance as a result of comparing and analyzing performance with a typical machine learning algorithm. In the future, the possibility of using various manufacturing fields was verified through the technique.

• Journal of Powder Materials
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• v.10 no.6
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• pp.383-389
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• 2003

As in other areas of materials technology, the tendency towards light weight constructions becomes more and more important also for powder metallurgy. The development is mainly driven by the automotive industry looking for mass reduction of vehicles as a major factor for fuel economy. Powder metallurgy has to offer a number of interesting areas including the development of sintered materials of light metals. PM aluminium alloys with improved properties are on the way to replace ferrous pars. For high temperature applications in the engine, titanium aluminide based materials offer a great potential, e.g. for exhaust valves. The PM route using elemental powders and reactions sintering is considered to be a cost effective way for net shape parts production. Furthermore it is expected that lower costs for titanium raw materials coming from metallurgical activities will offer new chances for sintered parts with titanium alloys. The field of cellular metals expands with the hollow sphere technique, that can provide materials of many metals and alloys with a great flexibility in structure modifications. These structures are expected to be used in improving the safety (crash absoption) and noise reduction in cars in the near future and offer great potential for many other applications.

• Journal of Korean Society of Industrial and Systems Engineering
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• v.44 no.4
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• pp.12-22
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• 2021

This article suggests the machine learning model, i.e., classifier, for predicting the production quality of free-machining 303-series stainless steel(STS303) small rolling wire rods according to the operating condition of the manufacturing process. For the development of the classifier, manufacturing data for 37 operating variables were collected from the manufacturing execution system(MES) of Company S, and the 12 types of derived variables were generated based on literature review and interviews with field experts. This research was performed with data preprocessing, exploratory data analysis, feature selection, machine learning modeling, and the evaluation of alternative models. In the preprocessing stage, missing values and outliers are removed, and oversampling using SMOTE(Synthetic oversampling technique) to resolve data imbalance. Features are selected by variable importance of LASSO(Least absolute shrinkage and selection operator) regression, extreme gradient boosting(XGBoost), and random forest models. Finally, logistic regression, support vector machine(SVM), random forest, and XGBoost are developed as a classifier to predict the adequate or defective products with new operating conditions. The optimal hyper-parameters for each model are investigated by the grid search and random search methods based on k-fold cross-validation. As a result of the experiment, XGBoost showed relatively high predictive performance compared to other models with an accuracy of 0.9929, specificity of 0.9372, F₁-score of 0.9963, and logarithmic loss of 0.0209. The classifier developed in this study is expected to improve productivity by enabling effective management of the manufacturing process for the STS303 small rolling wire rods.