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Case-Based Reasoning zur Kosten- und Kapazitätsbedarfsplanung von neuen Produkten

In der frühen Phase der Produktentwicklung

Case-based Reasoning for Cost and Capacity Demand Planning of New Products in the Early Phase of Product Development
Florian Girkes, Steffen Berghof and Jean Pierre Bergmann

Abstract

Zur Verkürzung der Zeitspanne zwischen der Entwicklung bis zur Auslieferung von neuen Produkten wird am Fachgebiet Fertigungstechnik der TU Ilmenau eine Methode entwickelt, mit der bereits in der Entwicklungsphase Kapazitäten für die Produktion reserviert und die Kostenkalkulation angegangen werden können, damit Unternehmen ihre Liefertermine einhalten und Kosten senken können. Grundlage dieser Methode bilden Typenvertreter, die durch Ähnlichkeiten zu bereits umgesetzten Produkten durch Verfahren des maschinellen Lernens abgeleitet und verbessert werden.

Abstract

In order to reduce the period between the development and delivery of new products, a method is being developed in the Department of Production Engineering at the Ilmenau University of Technology by which production capacity can be reserved in the development phase and the cost calculation undertaken, enabling companies to meet their delivery deadlines and to reduce costs. The basis of this method is formed by type representatives that are derived and refined using machine learning methods based on their similarity to projects already completed.


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Literatur

1 Bronner, A.: Angebots- und Projektkalkulation. Leitfaden für Praktiker (VDI-Buch). Springer-Verlag, Berlin 2008, S. V-2 Search in Google Scholar

2 Germani, M.; Mandolini, M.; Cicconi, P.: Manufacturing Cost Estimation during Early Phases of Machine Design. In: Proceedings of the 18th International Conference on Engineering Design (ICED 11), Impacting Society through Engineering Design, Vol. 5: Design for X / Design to X, Lyngby/Copenhagen, Denmark, 15.-19.08.2011 Search in Google Scholar

3 Helbing, K. W.: Typenvertreter. In: Helbing, K. W. (Hrsg.): Handbuch Fabrikprojektierung. Springer-Verlag, Berlin, Heidelberg 2010, S. 1401–1406 DOI: 10.1007/978-3-642-01618-9_63 Search in Google Scholar

4 Nugrahita, R.; Surjandari, I.: Identify Product Families Using Cluster Analysis: Case Study in Passenger Car Radial (PCR) Tire Product. IOP Conference Series: Materials Science and Engineering 909 (2020) 1, DOI: 10.1088/1757-899X/909/1/012057 Search in Google Scholar

5 Gaida, M.; Günther, U.; Wilsky, P.; Riedel, R.: Bildung von Produktfamilien als Planungsgrundlage auf Basis von Clusteralgorithmen. ZWF 115 (2020) 3, S. 111–114 DOI: 10.3139/104.112254 Search in Google Scholar

6 Wiendahl, H.-P.; Wiendahl, H.-H.: Betriebsorganisation für Ingenieure. Carl Hanser Verlag, München 2020, S. 324–326 DOI: 10.3139/9783446460614 Search in Google Scholar

7 Niazi, A.; Dai, J. S.; Balabani, S.; Seneviratne, L.: Product Cost Estimation: Technique Classification and Methodology Review. Journal of Manufacturing Science and Engineering 128 (2005) 2, S. 563–575 DOI: 10.1115/1.2137750 Search in Google Scholar

8 Martin, P.; Dantan, J.-Y.; Siadat, A.; Houin, X.; Daniel, Q.: Cost Estimation and Conceptual Process Planning. Conference: Digital Enterprise Technology, Springer Information Systems, At: Bath, United Kingdom. Metz, France 2017 Search in Google Scholar

9 Cox, M. T.; Muñoz-Avila, H.; Bergmann, R.: Case-based Planning. The Knowledge Engineering Review 20 (2005) 3, S. 283–287 DOI: 10.1017/S0269888906000592 Search in Google Scholar

10 Aamodt, A.; Plaza, E.: Case-based Reasoning: Foundational Issues, Methodological Variations, and System Approaches. AI Communications 7 (1994) 1, S. 39–59 DOI: 10.3233/AIC-1994-7104 Search in Google Scholar

11 Mourtzis, D.; Boli, N.; Fotia, S.: Knowledgebased Estimation of Maintenance Time for Complex Engineered-to-Order Products Based on KPIs Monitoring: A PSS Approach. Procedia CIRP 63 (2017), S. 236–241 DOI: 10.1016/j.procir.2017.03.317 Search in Google Scholar

12 Rashidi, H. H. et al.: Artificial Intelligence and Machine Learning in Pathology: The Present Landscape of Supervised Methods. Academic Pathology, September 2019, DOI: 10.1177/2374289519873088 Search in Google Scholar

13 Hawer, S.; Ilmer, P.; Reinhart, G.: Klassifizierung unscharfer Planungsdaten in der Fabrikplanung. ZWF 110 (2015) 6, S. 348–351 DOI: 10.3139/104.111339 Search in Google Scholar

Published Online: 2021-09-19
Published in Print: 2021-09-30

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