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
الموضوعات :
Arash Shahin
1
(Associate Professor, Department of Management, University of Isfahan)
Hadi Balouei Jamkhaneh
2
(Master Student in Industrial Management, University of Isfahan)
Pezhman Soleymanpoor
3
(Master Student in Industrial Management, University of Isfahan)
الکلمات المفتاحية: پایش وضعیت(CM), QFD, AHP, Condition Monitoring, شبکه تصمیم گیری(DMG), Decision Making Grid,
ملخص المقالة :
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.
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.
_||_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.
