Using Analytical Hierarchy Process and TOPSIS Approaches in Designing a Finite Element Analysis Automation Program
Sophisticated numerical simulations like finite element analysis (FEA) involve a complicated process from model setup to post-processing tasks that require replication of time-consuming steps. Utilizing FEA automation program simplifies the complexity of the involved steps while minimizing human errors in analysis set up, calculations, and results processing. One of the main challenges in designing FEA automation programs is to identify user requirements and link them to possible design alternatives. This paper presents a decision-making framework to design a Python based FEA automation program for modal analysis, frequency response analysis, and random vibration fatigue (RVF) analysis procedures. Analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) are applied to evaluate design alternatives considering the feedback received from experts and program users.
[1] Joachim Karlsson, An evaluation of methods for prioritizing software requirements. Claes Wohlin, Björn Regnell, Information and Software Technology 39 (1998) 939-947.
[2] Jorge Melegati, Alfredo Goldman, Fabio Kon, Xiaofeng Wang, A model of requirements engineering in software startups. Information and Software Technology, 109 (2019) 92–107.
[3] Mohd. Sadiq, Jawed Ahmed, Mohammad Asim, Aslam Qureshi, R. Suman, More on Elicitation of Software Requirements and Prioritization using AHP. 2010 International Conference on Data Storage and Data Engineering.
[4] W. Scacchi, Understanding the requirements for developing open source software systems. IEE Proceedings—Software, Paper number 29840, Accepted for publication with revisions, December 2001.
[5] Ming-Chyuan Lin, Chen-Cheng Wang, Ming-Shi Chen, C. Alec Chang. Using AHP and TOPSIS approaches in customer-driven product design process. Computers in Industry 59 (2008) 17–31.
[6] A Rama Mohan Reddy, Prof. M M Naidu, Prof. P. Govindarajulu. An Integrated approach of Analytical Hierarchy Process Model and Goal Model (AHP-GP Model) for Selection of Software Architecture. IJCSNS International Journal of Computer Science and Network Security, VOL.7 No.10, October 2007.
[7] Alexander Benlian, Is traditional, open-source, or on-demand first choice? Developing an AHP-based framework for the comparison of different software models in office suites selection. European Journal of Information Systems (2011) 20, 542–559.
[8] Alka Agrawal, Mamdouh Alenezi, Rajeev Kumar, Raees Ahmad Khan. Measuring the Sustainable-Security of Web Applications through a Fuzzy-Based Integrated Approach of AHP and TOPSIS. Received September 21, 2019, accepted October 6, 2019, date of publication October 11, 2019, date of current version November 1, 2019.
[9] Andrew Halfpenny. A frequency domain approach for fatigue life estimation from Finite Element Analysis. International Conference on Damage Assessment of Structures (DAMAS 99) Dublin.
[10] Da Yu, Abdullah Al-Yafawi, Tung T. Nguyen, Seungbae Park, Soonwan Chung, High-cycle fatigue life prediction for Pb-free BGA under random vibration loading. Microelectronics Reliability 51 (2011) 649–656.
[11] Da Yu, Abdullah Al-Yafawi, Seungbae Park, Soonwan Chung, Finite Element Based Fatigue Life Prediction for Electronic Components under Random Vibration Loading. 2010 Electronic Components and Technology Conference.
[12] Y.S. Chen, C.S. Wang, Y.J. Yang, Combining vibration test with finite element analysis for the fatigue life estimation of PBGA components. Microelectronics Reliability 48 (2008) 638–644.
[13] Abdullah Al-Yafawi, Saket Patil, Da Yu, Seungbae Park, James Pitarresi, Random vibration test for electronic assemblies fatigue life estimation. 2010 12th IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems.
[14] Abdullah Al-Yafawi, Da Yu , Seungbae Park, James Pitarresi, Soonwan Chung, Reliability Assessment of Electronic Components under Random Vibration Loading. 2009 Electronic Components and Technology Conference.
[15] Baussaron Julien, Fouchez Bertrand, Yalamas Thierry, Probabilistic Random Vibration Fatigue. Procedia Engineering 66 (2013) 522 – 529. 5th Fatigue Design Conference, Fatigue Design 2013.
[16] https://classes.engineering.wustl.edu/2009/spring/mase5513/abaqus-/docs-/v6.6/books/usb/default.htm?startat=pt03ch06s03at15.html
[1] Joachim Karlsson, An evaluation of methods for prioritizing software requirements. Claes Wohlin, Björn Regnell, Information and Software Technology 39 (1998) 939-947.
[2] Jorge Melegati, Alfredo Goldman, Fabio Kon, Xiaofeng Wang, A model of requirements engineering in software startups. Information and Software Technology, 109 (2019) 92–107.
[3] Mohd. Sadiq, Jawed Ahmed, Mohammad Asim, Aslam Qureshi, R. Suman, More on Elicitation of Software Requirements and Prioritization using AHP. 2010 International Conference on Data Storage and Data Engineering.
[4] W. Scacchi, Understanding the requirements for developing open source software systems. IEE Proceedings—Software, Paper number 29840, Accepted for publication with revisions, December 2001.
[5] Ming-Chyuan Lin, Chen-Cheng Wang, Ming-Shi Chen, C. Alec Chang. Using AHP and TOPSIS approaches in customer-driven product design process. Computers in Industry 59 (2008) 17–31.
[6] A Rama Mohan Reddy, Prof. M M Naidu, Prof. P. Govindarajulu. An Integrated approach of Analytical Hierarchy Process Model and Goal Model (AHP-GP Model) for Selection of Software Architecture. IJCSNS International Journal of Computer Science and Network Security, VOL.7 No.10, October 2007.
[7] Alexander Benlian, Is traditional, open-source, or on-demand first choice? Developing an AHP-based framework for the comparison of different software models in office suites selection. European Journal of Information Systems (2011) 20, 542–559.
[8] Alka Agrawal, Mamdouh Alenezi, Rajeev Kumar, Raees Ahmad Khan. Measuring the Sustainable-Security of Web Applications through a Fuzzy-Based Integrated Approach of AHP and TOPSIS. Received September 21, 2019, accepted October 6, 2019, date of publication October 11, 2019, date of current version November 1, 2019.
[9] Andrew Halfpenny. A frequency domain approach for fatigue life estimation from Finite Element Analysis. International Conference on Damage Assessment of Structures (DAMAS 99) Dublin.
[10] Da Yu, Abdullah Al-Yafawi, Tung T. Nguyen, Seungbae Park, Soonwan Chung, High-cycle fatigue life prediction for Pb-free BGA under random vibration loading. Microelectronics Reliability 51 (2011) 649–656.
[11] Da Yu, Abdullah Al-Yafawi, Seungbae Park, Soonwan Chung, Finite Element Based Fatigue Life Prediction for Electronic Components under Random Vibration Loading. 2010 Electronic Components and Technology Conference.
[12] Y.S. Chen, C.S. Wang, Y.J. Yang, Combining vibration test with finite element analysis for the fatigue life estimation of PBGA components. Microelectronics Reliability 48 (2008) 638–644.
[13] Abdullah Al-Yafawi, Saket Patil, Da Yu, Seungbae Park, James Pitarresi, Random vibration test for electronic assemblies fatigue life estimation. 2010 12th IEEE Intersociety Conference on Thermal and Thermomechanical Phenomena in Electronic Systems.
[14] Abdullah Al-Yafawi, Da Yu , Seungbae Park, James Pitarresi, Soonwan Chung, Reliability Assessment of Electronic Components under Random Vibration Loading. 2009 Electronic Components and Technology Conference.
[15] Baussaron Julien, Fouchez Bertrand, Yalamas Thierry, Probabilistic Random Vibration Fatigue. Procedia Engineering 66 (2013) 522 – 529. 5th Fatigue Design Conference, Fatigue Design 2013.
[16] https://classes.engineering.wustl.edu/2009/spring/mase5513/abaqus-/docs-/v6.6/books/usb/default.htm?startat=pt03ch06s03at15.html
@article{"International Journal of Information, Control and Computer Sciences:80311", author = "Ming Wen and Nasim Nezamoddini", title = "Using Analytical Hierarchy Process and TOPSIS Approaches in Designing a Finite Element Analysis Automation Program", abstract = "Sophisticated numerical simulations like finite element analysis (FEA) involve a complicated process from model setup to post-processing tasks that require replication of time-consuming steps. Utilizing FEA automation program simplifies the complexity of the involved steps while minimizing human errors in analysis set up, calculations, and results processing. One of the main challenges in designing FEA automation programs is to identify user requirements and link them to possible design alternatives. This paper presents a decision-making framework to design a Python based FEA automation program for modal analysis, frequency response analysis, and random vibration fatigue (RVF) analysis procedures. Analytical hierarchy process (AHP) and technique for order preference by similarity to ideal solution (TOPSIS) are applied to evaluate design alternatives considering the feedback received from experts and program users.
", keywords = "FEA, random vibration fatigue, process automation, AHP, TOPSIS, multiple-criteria decision-making, MCDM.", volume = "15", number = "5", pages = "165-9", }
