Cognitive optimization of an automotive rear-axle drive production process

• Autorzy: Schmitt R. , Isermann M. , Wagels C. , Matuschek N.
• Języki publikacji: EN

Abstrakty

EN

While optimizing tolerances in tolerance chains only single characteristics or objectives of single process steps are considered, there is no information exchange across all processes. Interdependencies between processes, materials, means of production and individuals acting in this environment as well as their effect on product variations are usually not fully understood. In order to face a dynamisation of process specification, interdependencies have to be identified and integrated in future production. The holistic consideration of the process chain focused on the allocation of tolerances allows detection of correlations and interdependencies in the production process itself. By this, process chain information is traced back to conduct the right optimizations at the right place in the process chain. But therefore intelligent controlling mechanisms are needed to analyze and optimize even complex production systems with multi-level interdependencies. Such a cognitive system is able to form the core of self-optimizing production system. Using this cognitive system, the production process of an automotive rear-axle drive is optimized in order to minimize disturbances created by structure-borne sound emissions. Therefore several cognitive technologies have been evaluated to fulfil specific tasks in process optimization.

Słowa kluczowe

EN

cognitive tolerance; self-optimization; rear-axle-drive

• Wydawca: Wydawnictwo Wrocławskiej Rady FSNT NOT
• Czasopismo: Journal of Machine Engineering
• Rocznik: 2009
• Tom: Vol. 9, No. 4
• Strony: 71--80
• Opis fizyczny: Bibliogr. 8 poz., rys.

Twórcy

autor

Schmitt R.

• Laboratory for Machine Tools and Production Engineering, RWTH Aachen University, Germany

autor

Isermann M.

• Fraunhofer Institute for Production Technology IPT, Aachen, Germany

autor

Wagels C.

• Laboratory for Machine Tools and Production Engineering, RWTH Aachen University, Germany

autor

Matuschek N.

• BMW Group, Dingolfing, Germany

Bibliografia

• 1. TSENG M. 2003 Industry Development Perspectives: Global Distribution of Work and Market, CIRP 53rd General Assembly, Montreal Canada
• 2. SCHMITT R., SCHARRENBERG C., 2007, Planning, Control and Improvement of Cross-site Production Process Chains, Presented at the 2007 CIRP 40th National Seminar on Manufacturing Systems, Liverpool, GB.
• 3. ORILSKI S., SCHUH G., 2007, Roadmapping for Competitiveness of High Wage Countries. Proceedings of the XVIIIISPIM Conference: On Innovation for Growth - the Challenges for East and West, Warsaw.
• 4. SCHMITT R., BEAUJEAN P., 2007, Selbstoptimierende Produktionssysteme, ZWF - Zeitschrift fur wirtschaftlichen Fabrikbetrieb, 102/9, 520-524.
• 5. SCHOLZ-REITER B., HOHNS H., 2007, Selbststeuerung logistischer Prozesse mit Agentensystemen, In: Schuh, G. (ed.): Produktionsplanung und - Steuerung. Third Edition, Springer Verlag, Berlin, Heidelberg.
• 6. FRANK U., GIESE H., KLEIN F., OBERSCHELP O., SCHMIDT A., SCHULZ B., VÖCKING H., WITTING K., 2004, Selbstoptimierende Systeme im Maschinenbau. Definitionen und Konzepte, HNI Verlag, Paderborn.
• 7. SCHMITT R., BEAUJEAN P., KRISTES D., 2008, Entrepreneurial Quality Management - A New Definition of Quality, IEEE International Engineering Management Conference (lEMC-Europe 2008).
• 8. Soar Technology, www.soartech.com