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Milling Cutter Selection in Machining Center Using AHP

AHP를 활용한 머시닝센터의 밀링커터 선정

  • Lee, Kyo-Sun (Dept. of Industrial & Management Engineering, Hanbat National University) ;
  • Park, Soo-Yong (Dept. of Industrial & Management Engineering, Hanbat National University) ;
  • Lee, Dong-Hyung (Dept. of Industrial & Management Engineering, Hanbat National University)
  • 이교선 (한밭대학교 산업경영공학과) ;
  • 박수용 (한밭대학교 산업경영공학과) ;
  • 이동형 (한밭대학교 산업경영공학과)
  • Received : 2017.07.19
  • Accepted : 2017.11.22
  • Published : 2017.12.31

Abstract

The CNC machine tool field is showing a growing trend with the recent rapid development of manufacturing industries such as semiconductors, automobiles, medical devices, various inspection and test equipment, mechanical metal processing equipment, aircraft, shipbuilding and electronic equipment. However, small and medium-sized machining companies that use CNC machine tools are experiencing difficulties in increasingly intense competition. Especially, small companies which are receiving orders from 3rd or 4th venders are very difficult in business management. In recent years, company S experienced difficulty to make product quality and delivery time due to the ignorance of the processing method when manufacturing cooling plate jig made of SUS304 material used for cell phone liquid crystal glass processing. In order to solve these problems, we redesigned the process according to the size of our company and tried to manage all processes with quantified data. In the meantime, we have found that there is a need to improve the cutter process, which accounts for most of the machining process. Therefore, we have investigated the correlation between RPM and FEED of three cutters that have been used in the past. As a result, we found that it is the most urgent problem to solve the roughing process during the cutter operation which occupies more than 70% of the total machining. In order to shorten the machining time and improve the quality in machining of SUS304 cooling plate jig, we select the main factors such as price, tool life, maintenance cost, productivity, quality, RPM, and FEED and use AHP to find the most suitable milling cutter. We also tried to solve the problem of delivery, quality and production capacity which was a big problem of S company through experiment operation with selected cutter tool. As a result, the following conclusions were drawn. First, the most efficient of the three cutters currently available in the machining center has proven to be an M-cutter. Second, although one additional facility was required, it was possible to produce the existing facilities without additional investment by supplementing the lack of production capacity due to productivity improvement. Third, the Company's difficulties in delivery and capacity shortfalls have been resolved. Fourth, annual sales increased by KRW 109 million and profits increased by KRW 32 million annually. Fifth, it can confirm the usefulness of AHP method in corporate decision making and it can be utilized in various facility investment and process improvement in the future.

Keywords

References

  1. Ayag, Z., A Hybrid Approach to Machine-tool Selection through AHP and Simulation, International Journal of Production Research, 2007, Vol. 45, No. 9, pp. 2029-2050. https://doi.org/10.1080/00207540600724856
  2. Cimren, E., Catay, B., and Budak, E., Development of a machine tool selection system using AHP, International Journal of Advanced Manufacturing Technology, 2007, Vol. 35, No. 3-4, pp. 363-376. https://doi.org/10.1007/s00170-006-0714-0
  3. Ic, Y.T., Yurdakul, M., and Eraslan, E., Development of a Component-based Machining Centre Selection Model using AHP, International Journal of Production Research, 2012, Vol. 50, No. 22, pp. 6489-6498. https://doi.org/10.1080/00207543.2011.653011
  4. Jung, Y.J., Kim, J.Y., and Joung, T.Y., The Study on Development of R&D Technology Rating Methodology in the Defense Area, Journal of the Korea Academia-Industrial cooperation Society, 2017, Vol. 18, pp. 158-167.
  5. Kim, S.Y., A Study on the Strategic Priority for Defence Quality Management Factors by using Analytic Hierarchy Process, Journal of Society of Korea Industrial and Systems Engineering, 2012, Vol. 35, No. 3, pp. 217-224.
  6. Lee, D.H., Plant Engineering, Ewha Publishing Co., 2011.
  7. Ryu, H.J., A Study on Prioritizing in Job Creation Policies : Focusing on AHP Analysis on the Policies of Daejeon Metropolitan City, Paichai University, [PhD's Thesis], 2016.
  8. Saaty, T.L., How to Make a Decision : The Analytic Hierarchy Process, European Journal of Operations Research, 1990, Vol. 48, No. 1, pp. 9-26. https://doi.org/10.1016/0377-2217(90)90057-I
  9. Saaty, T.L., The Analytic Hierarchy Process, New York, McGraw-Hill, 1980.
  10. Samvedi, A., Jain, V., and Felix, T.S., An Integrated Approach for Machine Tool Selection using Fuzzy Analytical Hierarchy Process and Grey Relational Analysis, International Journal of Production Research, 2012, Vol. 50, No. 12, pp. 3211-3221. https://doi.org/10.1080/00207543.2011.560906
  11. Wee, W.B., Analysis of Risk Factors for Engineering Work of the Russian LNG Plant by AHP Method, Hanyang University, [Master's Thesis], 2016.
  12. Yurdakul, M., AHP as a Strategic Decision-making Tool to Justify Machine Tool Selection, Journal of Materials Processing Technology, 2004, Vol. 146, Issue 3, pp. 365-376. https://doi.org/10.1016/j.jmatprotec.2003.11.026

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