Development of Intelligent Assistance System to Support Eco-efficient Planning

Sarfraz Ul Haque Minhas, Ulrich Berger

Abstract

The automotive industry is facing challenges due to high mass customization and consequent decentralization of manufacturing systems. Currently, the evaluation and optimization of eco-efficiency of production processes is complicated due to time consuming LCA simulations and inexperience of production planners to make respective decisions. This paper addresses this issue by developing ontology based intelligent assistance system to support planner in environmental assessment of manufacturing of customized production in decentralized manufacturing networks as well as decision making in production planning.

References

  1. Berger, U., Kretzschmann, R., Arnold, K. P., Minhas, S., 2008, Approach for the Development of a Heuristic Process Planning Tool for Sequencing NC Machining Operations, Applied Computer Science, 4/2:17-41
  2. Cai, J., 2007, Development of a Reference Feature-Based Machining Process Planning Data Model for WebEnabled Exchange in Extended Enterprise, PhD Dissertation, Shaker Verlag, Aachen.
  3. Christensen, T. B., 2009, Integration of Environmental Technology in Modularized Production Systems in the Automotive Industry, in: Proceedings of Joint Action on Climate Changes Conference, Denmark.
  4. Efthymiou, K., Alexopoulos, K., Sipsas, P., Mourtzis, D., Chryssolouris, G., 2011,(a), Knowledge Management Framework, Supporting Manufacturing System Design, Proceedings of 7th International Conference on Digital Enterprise Technology (DET2011), Athens, 28-30 Sep. 2011.
  5. Efthymiou, K., Sipsas, K., Melekos, D., Georgoulias, K., Chryssolouris, G., 2011, (b), A Manufacturing Ontology Following Performance Indicators Approach, Proceedings of 7th International Conference on Digital Enterprise Technology (DET2011), Athens, 28-30 Sep. 2011.
  6. Fjällström, S., Säfsten, K., Harlin, U., Stahre, J., 2009, Information Enabling Production Ramp-Up, Journal of Manufacturing Technology Management. 20/2:178- 196.
  7. Joo, J., 2005, Neural Network-based Dynamic Planning Model for Process Parameter Determination, Proceedings of International Conference on Computational Intelligence for Modelling, Control and Automation and International Conference on Intelligent Agents, Web Technologies and Internet Commerce, Vienna, 28.-30. Nov., 117-122.
  8. Minhas, S., Juzek, C., Berger, U., 2012, Ontology based Intelligent Assistance System to Support Manufacturing Activities in a Distributed Manufacturing Environment, Proceedings of 45th CIRP Conference on Manufacturing Systems, Athens, 16.-18. May, 2012.
  9. Mokhtar, A., Tavakoli-Bina, A, Houshmand, M., 2007, Approaches and Challenges in Machining Feature Based Process Planning, Proceedings of 4th International Conference on Digital Enterprise Technology.
  10. Monostori, L., Viharos, Z. J., Markos, S., 2000, Satisfying Various Requirements in Different Levels and Stages of Machining using One General ANN Based Process Model, Journal of Materials Processing Technology, 107/1-3:228-235.
  11. Tsai, Y. L., You, C. F., Lin, J. Y., Liu, K. Y., 2010, Knowledge-based Engineering for Process Planning and Die Design for Automotive Panels, ComputerAided Design & Applications, 7/1:75-87.
  12. Tu, Y., Chu, X., Yang, W., 2000, Computer-Aided Process Planning in Virtual One-of-a-Kind Production, Journal Computers in Industry, 41:99- 110.
  13. Venkatesan, D., Kannan, K., Saravanan, R., 2009, A Genetic Algorithm-Based Artificial Neural Network Model for the Optimization of Machining Processes, Neural Computing and Applications, 18/2:135-140.
  14. Wu, M., Li, D., Ji, W., 2010, Knowledge-Based Reasoning Assembly Process Planning Approach to Laser Range-Finder, International Conference on Computer Application and System Modeling (ICCASM), Taiyuan, 22.-24. Oct., V2-686-V2-690.
  15. Zhang, D. Z., Anosike, A. I., Lim, M. K., Akanle, O. M., 2006, An Agent-Based Approach for e-Manufacturing and Supply Chain Integration, Journal of Computers and Industrial Engineering, 51/2:343-360.
  16. Zhang, F., Zhang, Y. F., Nee, A. Y. C., 1997, Using Genetic Algorithms in Process Planning for Job Shop Machining, IEEE Transactions on Evolutionary Computation, 1/4:278-289.
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Paper Citation


in Harvard Style

Ul Haque Minhas S. and Berger U. (2012). Development of Intelligent Assistance System to Support Eco-efficient Planning . In Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2012) ISBN 978-989-8565-30-3, pages 331-334. DOI: 10.5220/0004110903310334


in Bibtex Style

@conference{keod12,
author={Sarfraz Ul Haque Minhas and Ulrich Berger},
title={Development of Intelligent Assistance System to Support Eco-efficient Planning},
booktitle={Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2012)},
year={2012},
pages={331-334},
publisher={SciTePress},
organization={INSTICC},
doi={10.5220/0004110903310334},
isbn={978-989-8565-30-3},
}


in EndNote Style

TY - CONF
JO - Proceedings of the International Conference on Knowledge Engineering and Ontology Development - Volume 1: KEOD, (IC3K 2012)
TI - Development of Intelligent Assistance System to Support Eco-efficient Planning
SN - 978-989-8565-30-3
AU - Ul Haque Minhas S.
AU - Berger U.
PY - 2012
SP - 331
EP - 334
DO - 10.5220/0004110903310334