اولویت بندی استراتژی های پایش وضعیت برای افزایش قابلیت دسترسی تجهیزات با استفاده از رویکرد ترکیبی AHP-QFD با مطالعه موردی در شرکت سهامی ذوب آهن اصفهان
محورهای موضوعی : مدیریت صنعتیArash Shahin 1 , Hadi Balouei Jamkhaneh 2 , Pezhman Soleymanpoor 3
1 - Associate Professor, Department of Management, University of Isfahan
2 - Master Student in Industrial Management, University of Isfahan
3 - Master Student in Industrial Management, University of Isfahan
کلید واژه: پایش وضعیت(CM), QFD, AHP, Condition Monitoring, شبکه تصمیم گیری(DMG), Decision Making Grid,
چکیده مقاله :
امروزه مدیریت دارایی های فیزیکی یکی از شاخه های مهم دانش و فناوری به شمار می رود. کاهش خرابی های اتفاقی و تعمیرات ناخواسته یکی از مهم ترین اهداف استفاده کنندگان از تجهیزات و ماشین آلات پیشرفته می باشد. در این میان تعمیرات مبتنی بر پایش وضعیت به عنوان راهکاری چاره ساز در مهار مشکلات فنی، اقتصادی و مدیریت راهبردی ماشین آلات و تجهیزات به کار برده می شود.در این تحقیق ضمن تشریح مبانی پایش وضعیت (CM) و استانداردهای موجود در این زمینه، روند تأثیرگذاری شاخص های موثر پایش وضعیت بر افزایش "قابلیت دسترسی تجهیزات" در سطح شرکت سهامی ذوب آهن اصفهان مورد بررسی قرارگرفته است و با استفاده از روش ترکیبی AHP - QFD، استراتژی های پایش وضعیت به منظور افزایش قابلیت دسترسی تجهیزات اولویت بندی شود. بدین صورت که اطلاعات مربوط به ماتریس خانه کیفیت را از طریق توزیع پرسشنامه طیف لیکرت بین مدیران و متخصصان بخش نگهداری و تعمیرات شرکت سهامی ذوب آهن اصفهان جمع آوری شد. یافته ها نشان دهنده آن است که استراتژی های تحلیل فرکانس و کل سطح ارتعاش با وزن2810/0 و استراتژی کلیدهای مغناطیسی و فیلترها با وزن 1026/0 به ترتیب بیشترین تاثیر را در افزایش قابلیت دسترسی تجهیزات دارند.
Nowadays management of physical assets is considered as one of the important fields of science and technology. Reduction of undesirable random failures and repairs is one of the most important objectives of those who utilize advanced types of equipment and machinery. Meanwhile, Condition Based Maintenance (CBM) has been recognized as an effective solution for the problems of technical, economic and strategic management of machinery and types of equipment. In this study, besides explaining the basics of this condition monitoring (CM) and existing standards, The influencing trend of CM process parameters on "increased equipment availability" have been studied in Isfahan Steel Company and, CM strategies have been prioritized using an integrated approach of Analytic Hierarchy Process (AHP) and Quality Function Deployment (QFD) towards improvement of equipment availability. Data related to house of quality is also via Likert questionnaire, have been collected between managers and experts of THE Maintenance department in the Isfahan Steel Company. The findings indicate that strategies of frequency analysis and overall vibration level with a total weight of 0.2810 and strategies of magnetic keys and filters with a total weight of 0.1026 have the most influence on increasing the availability of the equipment.
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2- Aslam Zainudeen, N & Labib, A.(2011). Practical application of the decision making grid.Journal of quality in maintenance engineering, 17(2), 138-149.
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7- Hauser, J.R. Clausing, D. (1988). The house of quality: Harvard Business Review, 96: 63–73.
8- Kelly, A. (2006). Strategic Maintenance Planning: Butterworth-Heinemann, http:www.amazon.com
9- Martins, A. & Aspinwall, E. M. (2001). Quality Function Deployment: An Empirical Study in the UK. Total Quality Management, 12(5), 575-588.
10- Rao, R.V.& Davim, J. P. (2008). A decision-making framework model for material selection using combined multiple attribute decision-making method. Journal of Adv Manufacturing Technology, 35(1), 751 – 760.
11- Williams, J.H. Davies, A. Drake, P.R. (1994). Condition-based maintenance and machine diagnostic.
12- Faqih, N. (1989). Maintenance engineering, printing. Shiraz: Navid Publications.
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14- Momeni, M. (2006). Topics modern operational research. Tehran: Tehran University Business School Press.
15- Nouri Khajavi, M. (2003). Technology, engineering and condition monitoring, fault diagnosis requires the industry. Fourth National Energy Congress, Tehran.
16- Rahmani, K. (2005). Maintenance Engineer (practical approach), first edition, first printing. Tabriz Sahand publications.
17- Shahin, A. Salehzadeh, M. R. Ghandahary, M. (2011). Integrated Model of QFD and clustering methods to improve the quality of customer services based on case studies in Qom Saman. Journal of Industrial Management Science Humanities, Islamic Azad University, 4(16),83-96.
18- Tavakkoli-Moghaddam, R. Mirzapur, H. Hosseini, A.(2009). Introduction to maintenance planning, Mashhad: publisher Sanabad.
19- Varani Farahani, H. (2007). Fundamentals of designing and implementing condition-based maintenance in industrial units - Case Study: Shazand thermal power plant. Second Technical Conference and troubleshooting machinery condition monitoring, Tehran, Sharif University of Technology.
_||_1- Alnajjar, B., & Alyousef, I. (2002). Selecting the most efficient maintenance approach using fuzzy multiple criteria decision-making. International journal of production economics, 84(1), 85-98.
2- Aslam Zainudeen, N & Labib, A.(2011). Practical application of the decision making grid.Journal of quality in maintenance engineering, 17(2), 138-149.
3- Bevilacqua, M & Braglia, M. (2000). The analytic hierarchy process applied to maintenance strategy selection. Reliability engineering and system safety, 70(2), 71-83.
4- Fernandz, O. Labib, W. Walmsley, R & Petty, D. (2003). A decision support maintenance management system developing and implementation. International Journal of Quality & Reliability Management, 20(8), 965-979.
5- Ferriera, A. Dealmeyda, D.Cavalcante, C.(2008). A multi-criteria model to determine inspection intervals of condition monitoring based on delay time analysis. Reliability engineering and systems safety, 94(1), 905-912.
6- Garcia, M.Sanzi-bobi, M. & Delpico, J. (2006). Intelligent system for predictive maintenance application to the health condition monitoring of a wind turbin gearbox. Computer in industry, 57(1), 552-568.
7- Hauser, J.R. Clausing, D. (1988). The house of quality: Harvard Business Review, 96: 63–73.
8- Kelly, A. (2006). Strategic Maintenance Planning: Butterworth-Heinemann, http:www.amazon.com
9- Martins, A. & Aspinwall, E. M. (2001). Quality Function Deployment: An Empirical Study in the UK. Total Quality Management, 12(5), 575-588.
10- Rao, R.V.& Davim, J. P. (2008). A decision-making framework model for material selection using combined multiple attribute decision-making method. Journal of Adv Manufacturing Technology, 35(1), 751 – 760.
11- Williams, J.H. Davies, A. Drake, P.R. (1994). Condition-based maintenance and machine diagnostic.
12- Faqih, N. (1989). Maintenance engineering, printing. Shiraz: Navid Publications.
13- Hashemi, S.J. Javadpoor, S. Mojaradian, A. (2007). Complementary role reliability techniques based maintenance (RCM) of condition monitoring (CM). Second Technical Conference and troubleshooting machinery condition monitoring, Tehran, Sharif University of Technology.
14- Momeni, M. (2006). Topics modern operational research. Tehran: Tehran University Business School Press.
15- Nouri Khajavi, M. (2003). Technology, engineering and condition monitoring, fault diagnosis requires the industry. Fourth National Energy Congress, Tehran.
16- Rahmani, K. (2005). Maintenance Engineer (practical approach), first edition, first printing. Tabriz Sahand publications.
17- Shahin, A. Salehzadeh, M. R. Ghandahary, M. (2011). Integrated Model of QFD and clustering methods to improve the quality of customer services based on case studies in Qom Saman. Journal of Industrial Management Science Humanities, Islamic Azad University, 4(16),83-96.
18- Tavakkoli-Moghaddam, R. Mirzapur, H. Hosseini, A.(2009). Introduction to maintenance planning, Mashhad: publisher Sanabad.
19- Varani Farahani, H. (2007). Fundamentals of designing and implementing condition-based maintenance in industrial units - Case Study: Shazand thermal power plant. Second Technical Conference and troubleshooting machinery condition monitoring, Tehran, Sharif University of Technology.
