• Proceedings of the Korean Society of Precision Engineering Conference
• /
• 2005.06a
• /
• pp.143-146
• /
• 2005

Many data mining techniques have been proved useful in revealing important patterns from large data sets. Especially, data mining techniques play an important role in a customer data analysis in a financial industry and an electronic commerce. Also, there are many data mining related research papers in a semiconductor industry and an automotive industry. In addition, data mining techniques are applied to the bioinformatics area. To satisfy customers' various requirements, each industry should develop new processes with more accurate production criteria. Also, they spend more money to guarantee their products' quality. In this manner, we apply data mining techniques to the production-related data such as a test data, a field claim data, and POP (point of production) data in the automotive parts industry. Data collection and transformation techniques should be applied to enhance the analysis results. Also, we classify various types of manufacturing processes and proposed an analysis scheme according to the type of manufacturing process. As a result, we could find inter- or intra-process relationships and critical features to monitor the current status of the each process. Finally, it helps an industry to raise their profit and reduce their failure cost.

• Journal of the Korean association of regional geographers
• /
• v.4 no.1
• /
• pp.99-120
• /
• 1998

The purpose of this study is to clarify the industrialization process, and locational factors and linkages of manufacturing in Jangyu-Myun, a suburb of Metropolitan Pusan, toward which heavy decentralization of manufacturing from Pusan has been done. Hard data and soft data were used as the basic data. Hard data used for this study were both the statistical data which consists of the number of establishments and employee classified by product type, firm size, organizational type and unit area(dong) which were listed in statistics yearbooks, and the list of the owner's names, addresses, employee number, products and headquarters of firms which were listed in firm directories. Soft data were the results of the interviews with the 53 owners of firms surveyed among the firms selected by Proportional Stratified Sampling Method. The major findings were as follows: (1) Manufacturing location in Jangyu-Myun was regularized in 1980's in which decentralization of manufacturing was activiated. Though the industrialization of study area resulted from the birth, relocation and establishment of branches of the firms originated from the other regions, the relocation of small outer-oriented firms from the central city was the most important factor among them. (2) The main locational factors which induced the decentralizing manufacturing from the central city into Jangyu-Myun are closely related to land, transportation, personal factor, raw material suppliers and market. (3) The differences of important locational factors by the size and organizational type of firms are relevant to the characteristics of manufacturing location. (4) The changes of linkages attendant upon locational changes of firms were not so great and were localized in labor supply and marketing. (5) The strength of linkages is strong in the procurement of materials, in the subcontraction and in the marketing, but not in the ordering. (6) The main factors influencing on the formation of linkages are different by the types of linkages: monopolistic and oligopolistic supply are important in procurement linkages; characteristics of products and production capacity in the subcontraction and ordering; characteristics of products and the subsequent difficulties, in the marketing. (7) With the exception of procurement linkages, the strength of linkages with the outside of the study area are stronger than the linkages with the inside. The strength of linkages with the outside has distance-decay-function and strong linkages with the central city. (8) These spatial characteristics of linkages are different by products type, firm size and organizational type of firms: the spatial ranges of linkages are wider in the multi-location firms than in the single-location firms; the larger the firm size, the wider the spatial range of linkages: there is no consistent trend by products type. In conclusion, some facts described above were proved to be consistent with the results of proceeding studies in the other areas: influence of central city manufacturing relocation on industrialization in the suburb: different decentralization by products type, firm size and organizational types of firms: different locational factors by products type, firm size and organizational types of firms; linkage changes attendant upon locational changes of firms; spatial differences of linkages by products type, firm size and organizational type of firms. Some other factors were proved to be partly consistent: locational factors and spatial characteristics of linkages. Accordingly I think that the results of previous studies on the other areas can be applicable to the explanation of the location and linkage of manufacturing in Jangyu-Myun. For the better explanation on the characteristics of manufacturing decentralization from the central city, more empirical case studies on the location and linkage of manufacturing in the suburb areas are necessary.

• The Journal of Information Systems
• /
• v.20 no.3
• /
• pp.1-24
• /
• 2011

Recently, six sigma has been widely adopted in a variety of industries as a disciplined, data-driven problem solving approach or methodology supported by a handful of powerful statistical tools in order to reduce variation through continuous process improvement. Also, data mining has been widely used to discover unknown knowledge from a large volume of data using various modeling techniques such as neural network, decision tree, regression analysis, etc. This paper proposes a six sigma methodology based on data mining for effectively and efficiently processing massive data in driving six sigma projects. The proposed methodology is applied in the hot stove system which is a major energy-consuming process in a "P" steel company for improvement of heat efficiency through reduction of energy consumption. The results show optimal operation conditions and reduction of the hot stove energy cost by 15%.

• Journal of the Korean Society for Precision Engineering
• /
• v.17 no.7
• /
• pp.63-73
• /
• 2000

Internet becomes very common tool for communication and data sharing. Virtual reality(VR) on web browser, and virtual prototyping and virtual manufacturing is widely used in many engineering folds. The reduction of overall development process and error minimization during data conversion becomes very crucial where sharing data via Internet and VR. This paper deals with the advantage and disadvantage of VRML format used in RP(Rapid Prototyping), and a software for RP data preparation is developed. If VRML format as an international standard for VR, is replaced with STL format, the weak points of STL format can be overcome and the technique related to virtual prototyping and virtual manufacturing can be addressed more systematically by sharing the data. The system developed in this work shows a good window to get access to a more realistic observation of an object fur an RP system from a long remote sites in a more systematic way.

• Journal of the Semiconductor & Display Technology
• /
• v.19 no.4
• /
• pp.121-125
• /
• 2020

With miniaturization of semiconductor, the manufacturing process become more complex, and undetected small changes in the state of the equipment have unexpectedly changed the process results. Fault detection classification (FDC) system that conducts more active data analysis is feasible to achieve more precise manufacturing process control with advanced machine learning method. However, applying machine learning, especially in supervised learning criteria, requires an arduous data labeling process for the construction of machine learning data. In this paper, we propose a semi-supervised learning to minimize the data labeling work for the data preprocessing. We employed equipment status variable identification (SVID) data and optical emission spectroscopy data (OES) in silicon etch with SF6/O2/Ar gas mixture, and the result shows as high as 95.2% of labeling accuracy with the suggested semi-supervised learning algorithm.

• Korean Journal of Computational Design and Engineering
• /
• v.17 no.3
• /
• pp.216-223
• /
• 2012

Bill of material (BOM), which structurally represents the relation among parts constructing a product, is usually created when enterprises start to develop a new product. And it is shown as various types of BOM according to business needs and usage such as eBOM (engineering BOM), gBOM (green BOM), mBOM (manufacturing BOM), pBOM (process BOM), etc. eBOM, generally called BOM and created in the design stage of the new product, includes the drawing information of parts in the view of product function. eBOM is extended to gBOM adding the material information of parts to cope with international regulations for environment. eBOM is transformed to mBOM, which includes manufacturing sequence of parts and adds some parts required to fabricate parts and to assemble the product. mBOM is also extended to pBOM adding the process information of each part and additional assembly processes. This study introduces the concept of multi-BOM covering eBOM, gBOM, mBOM and pBOM, and proposes an advanced way to manage product data using multi-BOM system. The multi-BOM system proposed is to manage their relations using transformation function of BOM and master information of all BOMs.

• IE interfaces
• /
• v.24 no.4
• /
• pp.330-340
• /
• 2011

This research aims at conducting a comparative study on the relative efficiency of technologically innovative activities between manufacturing and service industries using data envelopment analysis (DEA). First, as an individual approach, efficiency of technologically innovative activities between manufacturing and service industries is separately evaluated. The results show that efficiency of both industries is similarly low, but patterns of technologically innovative activities differ from each other. Manufacturing industries usually do innovation focusing on various outputs with a single input, whereas service industries tend to do innovation emphasizing on a single output with mixed inputs. Second, as a holistic approach to both industries, efficiency is collectively assessed. The analysis demonstrates that efficiency of service industries is higher than that of manufacturing industries, and there are similar patterns of technologically innovative activities between both manufacturing and service industries. This study provides industrial managers with policy implications based on similarities and differences between manufacturing and service industries.

• Journal of the Korean Society of Manufacturing Process Engineers
• /
• v.18 no.5
• /
• pp.37-47
• /
• 2019

Recently, as demand for various paper containers has rapidly grown, it is inevitable that paper cup-forming machines have increased their manufacturing speed. However, the faster manufacturing speed naturally brings more frequent manufacturing failures, which decreases manufacturing efficiency. As such, it is necessary to develop a system that monitors the failures in real time and diagnoses the failure progress in advance. In this research, a paper cup-forming machine diagnosis system was developed. Three major failure targets, paper deviation, temperature failure, and abnormal vibration, which dominantly affect the manufacturing process when they occur, were monitored and diagnosed. To evaluate the developed diagnosis system, extensive experiments were performed with the actual data gathered from the paper cup-forming machine. Furthermore, the desired system validation was obtained. The proposed system is expected to anticipate and prevent serious promising failures in advance and lower the final defect rate considerably.

• The Journal of Information Systems
• /
• v.31 no.1
• /
• pp.25-58
• /
• 2022

Purpose The purpose of this study is to analyzes the RPA fitting processes by the casese of manufacturing SMEs(Small and Medium-sized Enterprises) in an exploraty approach. Based on the findings on the RPA fitting processes, we intend to provide a cornerstone for developing a general-purpose RPA introduction model in the future. Design/methodology/approach In this study, empirical cases of RPA fitting processes were analyzed based on interviews with project managers of specialized IT suppliers in charge of RPA development and managers of IT departments of manufacturing SMEs that actually introduced RPA. In order to explore various RPA fitting process in the manufacturing value chain, a total of 7 manufacturing SMEs were interviewed, ranging from companies using a legacy system to companies without a legacy system. Over the primary and secondary activity processes, the details of RPA processes were analyzed in the steps of 'Frequency Identification, Input Processing, Source Identification, Inquiry and Processing, Information Registration, Result Reporting'. Findings From the analysis, we derived some exploratory results that the processes over 0.25 FTE and related with many suppliers and clients are fitting for RPA introduction in manufacturing SMEs Our results will provide basic data for the development of the future general-purpose RPA introduction model for manufacturing SMEs, providing practical reference for RPA introduction.

• Journal of Information Processing Systems
• /
• v.18 no.2
• /
• pp.208-222
• /
• 2022

Through the analysis of the coordination mechanism of the supply chain system of China's automobile manufacturing industry, the factors affecting the supply subsystem, the manufacturing subsystem, the sales subsystem, and the consumption subsystem are sorted out, the supply chain coordination index system based on the influence factor of four subsystems is established. The evaluation models of the coordination degree in the subsystem of the supply chain, the coordination degree among the subsystems, and the comprehensive coordination degree are established by using the efficiency coefficient method and the collaborative entropy method. Experimental results verify the accuracy of the evaluation model using the empirical analysis of the collaborative evaluation index data of China's automobile manufacturing industry from 2000 to 2019. The supply chain synergy of automobile manufacturing industry was low from 2001 to 2005, and it increased to a certain extent from 2006 to 2008 with a small growth rate from 0.10 to 0.15. From 2009 to 2013, the supply chain synergy of automobile manufacturing industry increased rapidly from 0.24 to 0.49, and it also increased rapidly but fluctuated from 2014 to 2019, first rising from 0.68 to 0.84 then dropping to 0.71. These results provide reference for the development of China's automobile manufacturing supply chain system and scientific decision-making basis for the formulation of relevant policies of the automobile manufacturing industry.