Designing a Model for Evaluating Performace Flexible Manufaturing Systems in Production Lines of Car Cylinder Block

Subject Areas : تحقیق در عملیات

Morteza Azarbad ¹ , Akbar Alemtabriz ^{2 *} , Farhad Hoseinzadeh ³ , محسن رستمی مال خلیفه ⁴

1 -
2 -
3 -
4 -

Received: 2022-06-29 Accepted : 2023-03-14 Published : 2024-09-25

Keywords: روش بهترین و بدترین, روش دلفی, سیستم تولید انعطاف پذیر, تحلیل پوششی داده ها, ارزیابی عملکرد,

Abstract :

With the advent of technology in informatic era and due to environmental intricacy, many organizations, companies, institutions and industries encounter many challenges to improve their status-quo and enhance their performance. In order to maintain competition, many manufacturing units, particularly auto parts manufacturers, deal with the conflicts of reducing costs, evading waste of time, being aptly accountable towards customers and improving quality. To resolve these shortcomings, many manufacturers apply a system called Flexible Manufacturing System. This production system is mainly designed by a group of machines with flexible workshops to produce various parts with the objectives of diminishing the time from order to delivery of goods, increasing the number of the final product, rising the efficiency of machines, developing the ability to deliver goods, reducing the level of inventory, lessening the work in process and increasing quality. In the current research, through surveying the scientific and industrial foundations, comprehensive indicators that affect the performance of the flexible manufacturing system collected and thanks to the frequency of indicators and the direction of screening via the Delphi Method, effective indicators are identified and subsequently in order to evaluate the performance of generating units in Tiba car cylinder block, the mathematical method of Developed Data Envelopment Analysis is utilized and the Best-Worst Method is applied for prioritizing the efficient units .The findings illustrate appropriate investment, utilization of advanced machinery and equipment and integration between equipment as well would make flexible production systems more efficient.

References:


[1]آذرباد، مرتضی. حسین¬زاده لطفی، فرهاد. (1396). شاخص بهره¬وری مالمکوئیست در شبکه و کاربرد آن برای محاسبه پیشرفت و پسرفت پژوهش دانشکده¬ها در یک دانشگاه. فصلنامه مدیریت بهره¬وری، 11(42)، 115-147.

[2]توکلی گلپایگانی، مریم. عالم¬تبریز، اکبر. امیری، مقصود. موتمنی علیرضا. (1394). طراحی و تبیین مدل ارزیابی عملکرد با رویکرد تلفیقی تحلیل پوششی داده¬ها، تحلیل عاملی و اوزان مشترک (مطالعه موردی: صنعت بیمه). فصلنامه چشم¬انداز مدیریت صنعتی، 5(17)، 45-76.

[3]جهانشاهلو، غلامرضا. حسین¬زاده لطفی، فرهاد. نیکومرام، هاشم. (1387). تحلیل پوششی داده¬ها و کاربردهای آن. انتشارات آثار نفیس.

[4]مهدوری، کاوه. (1397(. سیستم¬های تولید انعطاف¬پذیر. انتشارات ساپکو.

[5]میلتن برگ، جان. (1388). مدیریت راهبردی صنعتی. انتشارات مرکز تحقیق و توسعه علوم انسانی.

[6]Bagheri, M., Ebrahimnezhad, A., Razavyan, S., Hosseinzadeh Lotfi, F. & Malekmohammadi,N. (2020). Fuzzy Arithmetic Dea Approach For Fuzzy Multi-Objective Transportation Problem. Journal Of Operational Research, Https:// Link.Springer.Com/Article/10.1007/S12351-020-00592-4.

[7]Bayazit, Ozden. (2004). Use Of Ahp In Decision-Making For Flexible Manufacturing Systems. Journal Of Manufacturing Technology Management, 808-819.

[8]Ebrahimi, Bohlool., Dellnitz, Andreas., Kleine, Andreas. & Tavana, Madjid. (2021). A Novel Method For Solving Data Envelopment Analysis Problems With Weak Ordinal Data Using Robust Measures. Expert Systems With Applications, 164 (2021) 113835.

[9]Ebrahimi, Bohlool & Rahmani, Morteza. (2017). An Improved Approach To Find And Rank Bcc-Efficient Dmus In Data Envelopment Analysis (Dea). Journal Of Industrial And Systems Engineering, 25-34.

[10]Eguía, Ignacio., Villa, Gabriel. & Lozano, Sebastián. (2017, June). Efficiency Assessment Of Reconfigurable Manufacturing Systems. 27th International Conference On Flexible Automation And Intelligent Manufacturing, Faim2017, 27-30 June 2017, Modena, Italy [3] Do Tan Si, The Fourier Transform And Principles Of Quantum Mechanics, Applied Mathematics, 09(04):347-354 ,(2018).
[11]Ertugrul Karsak, E. (2006). Using Data Envelopment Analysis For Evaluating Flexible Manufacturing Systems In The Presence Of Imprecise Data. Int J Adv Manuf Technol, 867–874.

[12]Ertugrul Karsak, E & Kuzgunkaya, Onur. (2002). A Fuzzy Multiple Objective Programming Approach For The Selection Of A Fexible Manufacturing System. Int. J. Production Economics, 101-111.

[13]Florescu, Adriana & Barabas, Sorin Adrian. (2020). Modeling And Simulation Of A Flexible Manufacturing System—A Basic Component Of Industry 4.0. Applied Sciences, Https://Www.Mdpi.Com/Journal/Applsci.

[14]Jahanshahloo, G. R., Sanei, M., Rostami-Malkhalifeh, M & Saleh, H. (2009). A Comment On "A Fuzzy Dea/Ar Approach To The Selection Of Flexible Manufacturing Systems". Journal Of Computers & Industrial Engineering, 1713–1714.
[15]Kapitanov, A. V. (2017). Manufacturing System Flexibility Control. International Conference On Industrial Engineering, 1470-1475.

[16]Khouja, Moutaz. (1994). The Use Of Data Envelopment Analysis For Technology Selection. Computer Ind, 123-132.

[17]Kianfar, K., Ahadzade Namin, M., Alam Tabriz, A., Najafi, E. & Hosseinzadeh Lotfi, F. (2018). The Ndea-Mop Model In The Presence Of Negative Data Using Fuzzy Method. Journal Of Scientia Iranica, 398-409.

[18]Li, Yongjun., Chen, Yao., Liang, Liang. & Xie, Jianhui. (2012). Dea Models For Extended Two-Stage Network Structures. International Series In Operations Research & Management Science, 261-285.

[19]Liu, Shiang-Tai. (2008). A Fuzzy Dea/Ar Approach To The Selection Of Flexible Manufacturing Systems. Computers & Industrial Engineering, 66–76.

[20]Mahmood, Kashif., Karaulova, Tatjana., Otto, Tauno. & Shevtshenko, Eduard. (2017). Performance Analysis Of A Flexible Manufacturing System (Fms). The 50th Cirp Conference On Manufacturing Systems, Procedia Cirp 63 ( 2017 ) 424 – 429.

[21]Peykani, Pejman., Mohammadi, Emran., Farzipoor Saen, Reza., Sadjadi, Seyed Jafar. & Rostamy-Malkhalifeh, Mohsen. (2020). Data Envelopment Analysis And Robust Optimization: A Review. Journal Of Expert Systems, Doi: 10.1111/Exsy.12534.

[22]Rezaei, Jafar. (2015). Best-Worst Multi-Criteria Decision-Making Method. Journal Of Omega, 49–57.

[23]Sarki, Joseph & University, Clark. (1997). Evaluating Flexible Manufacturing Systems Alternatives Using Data Envelopment Analysis. A Journal Devoted To The Problems Of Capital Investment, 25-47.

[24]Shakouri, B., Abbasi Shureshjani, R., Daneshian, B & Hosseinzadeh Lotfi, F. (2020). A Parametric Method For Ranking Intuitionistic Fuzzy Numbers And Its Application To Solve Intuitionistic Fuzzy Network Data Envelopment Analysis Models. Journal Of Hindawi, Https://Doi.Org/10.1155/2020/6408613.

[25]Shang, Jen & Sueyoshi, Toshiyuki. (1995). A Unified Framework For The Selection Of A Flexible Manufacturing System. European Journal Of Operational Research, 297-315.

[26]Shavazipour, Babooshka. (2014). Measuring Efficiency And Effectiveness For Non-Storable Commodities: A Mixed Separate Data Envelopment Analysis Spproaches With Real And Fuzzy Data. International Journal Of Data Envelopment Analysis And *Operations Research, 1-11.

[27]Singh, Sanjeet. (2018). Intuitionistic Fuzzy Dea/Ar And Its Application To Flexible Manufacturing Systems. Journal Of Rairo Operations Research, 241-257.

[28]Shivanand, H. K., Benal, M. M. & Koti, V. (2006). Flexible Manufacturing System. New Age International Publishers.

[29]Song, Lianlian. & Liu, Fan . (2016). An Improvement In Dea Cross Efficiency Aggregation Based On The Shannon Entropy. Journal Of International Transactions In Operational Research, 1-10.
[30]Talluri, Srinivas., Whiteside, Mary M. & Seipel, Scott J. (2000). A Nonparametric Stochastic Procedure For Fms Evaluation. European Journal Of Operational Research, 529–538.

[31]Toloo, Mehdi & Salahi, Maziar. (2018). A Powerful Discriminative Approach For Selecting The Most Efficient Unit In Dea. Computers & Industrial Engineering, 269-277.

[32]Vaez, E., Najafi, S. E., Hajimolana, S. M., Hosseinzadeh Lotfi, F & Ahadzadeh Namin, M. (2021). Efficiency Evaluation Of A Three-Stage Leader-Follower Model By Data Envelopment Analysis With Double-Frontier View Point. Journal Of Scientia Iranica, 492-515.

[33]Wang, Meiqiang. & Li, Yongjun. (2012). A Fuzzy Dea Model Based On Weighted Average Value Of Fuzzy Numbers. Journal Of Society Systems Science, Https://Www.Researchgate.Net/Publication/264440693.

[34]Wang, Yi-Chi., Chen, Toly., Chiang, Hsiangtsai. & Pan, Hui-Chen. (2016). A Simulation Analysis Of Part Launching And Order Collection Decisions For A Flexible Manufacturing System. Simulation Modelling Practice And Theory, 80-91.

[35]Wang, Ying-Ming. & Chin, Kwai-Sang. (2011). Fuzzy Data Envelopment Analysis: A Fuzzy Expected Value Approach. Expert Systems With Applications, 11678-11685.

[36]Wang, Zhiguo., Pang, Chee Khiang. & Ng, Tsan Sheng. (2019). Robust Scheduling Optimization For Flexible Manufacturing Systems With Replenishment Under Uncertain Machine Failure Disruptions. Control Engineering Practice, Https://Www.Sciencedirect.Com/Science/Article/Abs/Pii/S096706611930111x?Via%3dihub.

[37]Yadav, Anupma & Jayswal, S. C. (2020). Modelling Of Flexible Manufacturing System: A Review. International Journal Of Production Research, Https:// Doi.Org/10.1080/00207543.2017.1387302.

[38]Zacharia, Paraskevi T. & Xidias, Elias K. (2020). Agv Routing And Motion Planning In A Flexible Manufacturing System Using A Fuzzy-Based Genetic Algorithm. The International Journal Of Advanced Manufacturing Technology, Https://Doi.Org/10.1007/S00170-020-05755-3.

[39]Zohreh, Moghaddas, Babak, Mohamadpour Tosarkani & Samuel, Yousefi. (2022). Resource Reallocation For Improving Sustainable Supply Chain Performance: An Inverse Data Envelopment Analysis. International Journal Of Production Economics, Volume 252, October 2022, 108560.

[11]Ertugrul Karsak, E. (2006). Using Data Envelopment Analysis For Evaluating Flexible Manufacturing Systems In The Presence Of Imprecise Data. Int J Adv Manuf Technol, 867–874.

[12]Ertugrul Karsak, E & Kuzgunkaya, Onur. (2002). A Fuzzy Multiple Objective Programming Approach For The Selection Of A Fexible Manufacturing System. Int. J. Production Economics, 101-111.

[13]Florescu, Adriana & Barabas, Sorin Adrian. (2020). Modeling And Simulation Of A Flexible Manufacturing System—A Basic Component Of Industry 4.0. Applied Sciences, Https://Www.Mdpi.Com/Journal/Applsci.

[14]Jahanshahloo, G. R., Sanei, M., Rostami-Malkhalifeh, M & Saleh, H. (2009). A Comment On "A Fuzzy Dea/Ar Approach To The Selection Of Flexible Manufacturing Systems". Journal Of Computers & Industrial Engineering, 1713–1714.

[15]Kapitanov, A. V. (2017). Manufacturing System Flexibility Control. International Conference On Industrial Engineering, 1470-1475.

[16]Khouja, Moutaz. (1994). The Use Of Data Envelopment Analysis For Technology Selection. Computer Ind, 123-132.

[17]Kianfar, K., Ahadzade Namin, M., Alam Tabriz, A., Najafi, E. & Hosseinzadeh Lotfi, F. (2018). The Ndea-Mop Model In The Presence Of Negative Data Using Fuzzy Method. Journal Of Scientia Iranica, 398-409.

[18]Li, Yongjun., Chen, Yao., Liang, Liang. & Xie, Jianhui. (2012). Dea Models For Extended Two-Stage Network Structures. International Series In Operations Research & Management Science, 261-285.

[19]Liu, Shiang-Tai. (2008). A Fuzzy Dea/Ar Approach To The Selection Of Flexible Manufacturing Systems. Computers & Industrial Engineering, 66–76.

[20]Mahmood, Kashif., Karaulova, Tatjana., Otto, Tauno. & Shevtshenko, Eduard. (2017). Performance Analysis Of A Flexible Manufacturing System (Fms). The 50th Cirp Conference On Manufacturing Systems, Procedia Cirp 63 ( 2017 ) 424 – 429.

[21]Peykani, Pejman., Mohammadi, Emran., Farzipoor Saen, Reza., Sadjadi, Seyed Jafar. & Rostamy-Malkhalifeh, Mohsen. (2020). Data Envelopment Analysis And Robust Optimization: A Review. Journal Of Expert Systems, Doi: 10.1111/Exsy.12534.

[22]Rezaei, Jafar. (2015). Best-Worst Multi-Criteria Decision-Making Method. Journal Of Omega, 49–57.

[23]Sarki, Joseph & University, Clark. (1997). Evaluating Flexible Manufacturing Systems Alternatives Using Data Envelopment Analysis. A Journal Devoted To The Problems Of Capital Investment, 25-47.

[24]Shakouri, B., Abbasi Shureshjani, R., Daneshian, B & Hosseinzadeh Lotfi, F. (2020). A Parametric Method For Ranking Intuitionistic Fuzzy Numbers And Its Application To Solve Intuitionistic Fuzzy Network Data Envelopment Analysis Models. Journal Of Hindawi, Https://Doi.Org/10.1155/2020/6408613.

[25]Shang, Jen & Sueyoshi, Toshiyuki. (1995). A Unified Framework For The Selection Of A Flexible Manufacturing System. European Journal Of Operational Research, 297-315.

[26]Shavazipour, Babooshka. (2014). Measuring Efficiency And Effectiveness For Non-Storable Commodities: A Mixed Separate Data Envelopment Analysis Spproaches With Real And Fuzzy Data. International Journal Of Data Envelopment Analysis And *Operations Research, 1-11.

[27]Singh, Sanjeet. (2018). Intuitionistic Fuzzy Dea/Ar And Its Application To Flexible Manufacturing Systems. Journal Of Rairo Operations Research, 241-257.

[28]Shivanand, H. K., Benal, M. M. & Koti, V. (2006). Flexible Manufacturing System. New Age International Publishers.
[29]Song, Lianlian. & Liu, Fan . (2016). An Improvement In Dea Cross Efficiency Aggregation Based On The Shannon Entropy. Journal Of International Transactions In Operational Research, 1-10.

[30]Talluri, Srinivas., Whiteside, Mary M. & Seipel, Scott J. (2000). A Nonparametric Stochastic Procedure For Fms Evaluation. European Journal Of Operational Research, 529–538.

[31]Toloo, Mehdi & Salahi, Maziar. (2018). A Powerful Discriminative Approach For Selecting The Most Efficient Unit In Dea. Computers & Industrial Engineering, 269-277.

[32]Vaez, E., Najafi, S. E., Hajimolana, S. M., Hosseinzadeh Lotfi, F & Ahadzadeh Namin, M. (2021). Efficiency Evaluation Of A Three-Stage Leader-Follower Model By Data Envelopment Analysis With Double-Frontier View Point. Journal Of Scientia Iranica, 492-515.

[33]Wang, Meiqiang. & Li, Yongjun. (2012). A Fuzzy Dea Model Based On Weighted Average Value Of Fuzzy Numbers. Journal Of Society Systems Science, Https://Www.Researchgate.Net/Publication/264440693.

[34]Wang, Yi-Chi., Chen, Toly., Chiang, Hsiangtsai. & Pan, Hui-Chen. (2016). A Simulation Analysis Of Part Launching And Order Collection Decisions For A Flexible Manufacturing System. Simulation Modelling Practice And Theory, 80-91.

[35]Wang, Ying-Ming. & Chin, Kwai-Sang. (2011). Fuzzy Data Envelopment Analysis: A Fuzzy Expected Value Approach. Expert Systems With Applications, 11678-11685.

[36]Wang, Zhiguo., Pang, Chee Khiang. & Ng, Tsan Sheng. (2019). Robust Scheduling Optimization For Flexible Manufacturing Systems With Replenishment Under Uncertain Machine Failure Disruptions. Control Engineering Practice, Https:// Www.Sciencedirect.Com/Science/Article/Abs/Pii/S096706611930111x?Via%3dihub.

[37]Yadav, Anupma & Jayswal, S. C. (2020). Modelling Of Flexible Manufacturing System: A Review. International Journal Of Production Research, Https:// Doi.Org/10.1080/00207543.2017.1387302.

[38]Zacharia, Paraskevi T. & Xidias, Elias K. (2020). Agv Routing And Motion Planning In A Flexible Manufacturing System Using A Fuzzy-Based Genetic Algorithm. The International Journal Of Advanced Manufacturing Technology, Https://Doi.Org/10.1007/S00170-020-05755-3.

[39]Zohreh, Moghaddas, Babak, Mohamadpour Tosarkani & Samuel, Yousefi. (2022). Resource Reallocation For Improving Sustainable Supply Chain Performance: An Inverse Data Envelopment Analysis. International Journal Of Production Economics, Volume 252, October 2022, 108560.