This content is not included in
your SAE MOBILUS subscription, or you are not logged in.
Fault Identification of Assembly Processes Using Fuzzy Set Theory
Technical Paper
2020-01-0487
ISSN: 0148-7191, e-ISSN: 2688-3627
This content contains downloadable datasets
Annotation ability available
Sector:
Language:
English
Abstract
Effective identification of sources of faults in modern manufacturing systems play a critical role in their performance and productivity. Tracking faults in a typical manufacturing system is inherently an inverse problem which makes it more challenging and difficult to solve. Presented in this article is the development of a new methodology for fault identification and root-cause analysis of complex assembly systems. A combination of a knowledge-based system and fuzzy set theory is used to develop this new technique, which is an intelligent system that mimics the behavior of an expert in the field, and can trace back the source or sources of the fault to the relevant station.
Presented are the concepts of faults, their detection in an assembly line, and their generic characteristics. Study of the fault's fundamental properties reveals that there are certain levels of uncertainty involved in describing them. This has led us to the adoption of fuzzy set theory as a basic tool for development of this new technique. This article reports on recent progress made in this area and outlines some of the preliminary results obtained so far. It is shown that based on the characteristics of the faults and the type of operations, it is possible to relate the faults to the relevant station. Examples from real assembly operations are provided to show the effectiveness of this approach.
Recommended Content
Topic
Citation
Mehrabi, M. and Weaver, J., "Fault Identification of Assembly Processes Using Fuzzy Set Theory," SAE Technical Paper 2020-01-0487, 2020, https://doi.org/10.4271/2020-01-0487.Data Sets - Support Documents
Title | Description | Download |
---|---|---|
Unnamed Dataset 1 | ||
Unnamed Dataset 2 |
Also In
References
- Badiru , A.B. Expert Systems Applications in Engineering and Manufacturing Englewood Cliffs, NJ Prentice Hall 1992
- Barajas , L.G. and Srinivasa , N. Real-Time Diagnostics, Prognostics Health Management for Large-Scale Manufacturing Maintenance Systems ASME International Manufacturing Science and Engineering Conference Evanston, IL 85 94 2008
- Belokar , R.M. , Kumar , H. , Singh , J. , and Belokar , P. Improvement of Quality through Six Sigma: A Case Study Int. J. Eng. , Bus. Enterp. Appl. ( IJEBEA ) 127 131 2014
- Choo , B.Y. , Beling , P.A. , LaViers , A.E. , Marvel , J.A. et al. Adaptive Multi-scale PHM for Robotic Assembly Processes Proc. Annu Conf Progn Health Manag. Soc. 6 037 245 249 2015
- Boothroyd , G. Assembly Automation and Product Design Second New York Florence Marcel Dekker 2005
- Demetgul , M. , Tansel , I. , and Taskin , S. Fault Diagnosis of Pneumatic Systems with Artificial Neural Network Algorithms Expert Syst Appl 36 7 10512 10519 2009
- Ding , Y. , Ceglarek , D. , and Shi , J. Fault Diagnosis of Multistage Manufacturing Processes by Using State Space Approach Journal of Manufacturing Science and Engineering 124 199 313 322 2002
- Great , O.E. and Offiong , A. Productivity Improvement in Breweries through Line Balancing Using Heuristic Method Int. J. Eng. Sci. Technol. 5 3 475 486 2013
- Gröger , F.N. and Mitschang , B. Data Mining-driven Manufacturing Process Optimization Proc. of the World Congress on Engineering 2012 Vol III (WCE) Hong Kong 2012 1475 1481
- Jin , J. and Shi , J. State Space Modeling of Sheet Metal Assembly for Dimensional Control ASME J. Manuf. Sci. Eng. 121 756 762 1999
- Hu , S.J. Stream of Variation Theory for Automotive Body Assembly Annals of the CIRP 46 1 1997
- Huang , Q. , Zhou , N. , and Shi , J. Stream-of-Variation Modeling and Diagnosis of Multi-station Machining Processes Proceedings of the 2000 ASME International Mechanical ASME International Mechanical Engineering Congress and Exposition, MED-11 2000 81 88
- Kalra , A. , Marwah , S. , Srivastava , S. , and Bhatia , R. Productivity Improvement in Assembly Line of Automobile Industry by Reducing Cycle Time of Operations Int. J. Eng. Res. Technol. 5 05 28 31 2016
- Kaufmann , A. and Gupta , M.M. Introduction to Fuzzy Arithmetic New York Van Nostrand Reinhold 1985
- Köksal , G. , Batmaz , İ. , and Testika , M.C. Review of Data Mining Applications for Quality Improvement in Manufacturing Industry Expert Systems with Applications 38 10 13448 13467 2011
- Koton , P.A. Empirical and Model-Based Reasoning in Expert Systems Proc. 9th Intl. Joint Conference on Artificial Intelligence Los Angeles, CA 1985 1308 1316
- Kulkarni , P.P. , Kshire , S.S. , and Chandratre , K.V. Productivity Improvement Through Lean Deployment & Work Study Methods Int. J. Res. Eng. Technol. 03 02 429 434 2014
- Kumar , C. , Naidu , D.N.V.R. , and Ravindranath , D.K. Performance Improvement of Manufacturing Industry by Reducing the Defectives Using Six Sigma Methodologies IOSR J. Eng. 1 1 01 09 2012
- Kumar , S.S. and Kumar , M.P. Cycle Time Reduction of a Truck Body Assembly in an Automobile Industry by Lean Principles Int. Conf. Adv. Manfucturing Mater. Eng. AMME 2014 5 1853 1862 2014
- Kumara , S.R.T. , Kahsyap , R.L. , and Soyster , A.L. Artificial Intelligence: Manufacturing: Theory and Practice Norcross, GA Industrial Engineering and Management Press 1988
- Kusiak , A. Designing Expert Systems for Scheduling of Automated Manufacturing Industrial Engineering 19 7 42 46 1987
- Lyu , J.J. A Single-Run Optimization Algorithm for Stochastic Assembly Line Balancing Problems J. Manuf. Syst. 16 3 204 210 1997
- Mantripragada , R. and Whitney , D.E. Modeling and Controlling Variation Propagation in Mechanical Assemblies Using State Transition Models IEEE Trans. Rob. Autom. 15 124 140 1999
- Mishra , R. Productivity Improvement in Automobile Industry by Using Method Study Int. J. Sci. Eng. Appl. Sci. 1 4 361 363 2015
- Orlovski , S.A. Decision-Making with a Fuzzy Preference Relation Fuzzy Sets and Systems 1 155 167 1978
- Philippot , A. , Marang , P. , Gellot , F. , Ptin , J.F. et al. Fault Tolerant Control for Manufacturing Discrete Systems by Filter and Diagnoser Interactions Annual Conf. of the Prognostics and Health Management Society Fort Worth, TX 2014
- Reddy , A.S.N. , Rao , P.S. , and Rajyalakshmi , G. Productivity Improvement Using Time Study Analysis in a Small Scale Solar Appliances Industry - A Case Study Arpn J. Eng. Appl. Sci. 11 1 666 674 2016
- Riascos , L.M. and Miyagi , P.E. Supervisor System for Detection and Treatment of Failures in Balanced Automation Systems Using Petri Nets Proceedings of the IEEE SMC’2001 International Conference on Systems, Man, and Cybernetics Tucson 2001 2528 2533
- Rohani , J.M. and Zahraee , S.M. Production Line Analysis via Value Stream Mapping: A Lean Manufacturing Process of Color Industry Procedia Manuf. 2 6 10 Feb. 2015
- Schloske , A. and Henke , J. Failure Process Matrix (FPM) - A New Approach for the Optimization of Assembly Lines The 1st CIRP International Seminar on Assembly Systems Stuttgart 2006 257 260
- Sekar , R. , Hsieh , S. , and Wu , Z. Remote Diagnosis Design for a PLC-Based Automated System: Implementation of Three Levels of Architectures Int J Adv Manuf Technol 57 58 683 700 2011
- Shrivastava , R.K. and Sridhar , K. Productivity & Quality Improvement Through Kanban - A Case Study Int. J. Adv. Eng. Res. Stud. 04 02 251 255 2015
- Simmons , R. and Davis , R. Generate, Test and Debug: Combining Associational Rules and Causal Models Proc. 10th International Joint Conference on Artificial Intelligence Milan, Italy 1987 1071 1076
- Terano , T. , Asai , K. , and Sugeno , M. Fuzzy Systems Theory and Its Applications San Diego, CA Academic Press 1991
- Torasso , P. and Console , L. Causal Reasoning in Diagnostic Expert Systems. In: Applications of Artificial Intelligence V Proc SPIE 786 598 605 1987
- Ye , N. , Zhao , B. , and Salvendy , G. Neural-networks-aided fault diagnosis in supervisory control of advanced manufacturing systems The International Journal of Advanced Manufacturing Technology 8 4 200 209 2005
- Zadeh , L.A. Fuzzy Sets Information and Control 8 338 353 1965