TU Darmstadt / ULB / TUbiblio

Utility-based Configuration of Learning Factories Using a Multidimensional, Multiple-choice Knapsack Problem

Tisch, Michael and Laudemann, Heiko and Kreß, Antonio and Metternich, Joachim (2017):
Utility-based Configuration of Learning Factories Using a Multidimensional, Multiple-choice Knapsack Problem.
In: Procedia Manufacturing, 7th Conference on Learning Factories, Darmstadt, Elsevier B.V., pp. 25-32, 9, ISSN 2351-9789, DOI: 10.1016/j.promfg.2017.04.017, [Online-Edition: https://doi.org/10.1016/j.promfg.2017.04.017],
[Article]

Abstract

The paper presents a structural approach to configure the technical system of a learning factory by considering learning targets and maximizing the utility. Local scope conditions and intended competencies are used to operationalize requirements. The composition of the module-based technical system can be optimized by maximizing its overall utility. Therefore, an exact and efficient optimization algorithm is developed solving a multidimensional multiple-choice knapsack problem combined with a two-dimensional bin packing problem. Restrictions are the available budget and the useable area of the learning factory. As a result, the configured technical system enables optimal target orientation of the learning factory. This procedure is finally applied on the Process Learning Factory CiP.

Item Type: Article
Erschienen: 2017
Creators: Tisch, Michael and Laudemann, Heiko and Kreß, Antonio and Metternich, Joachim
Title: Utility-based Configuration of Learning Factories Using a Multidimensional, Multiple-choice Knapsack Problem
Language: English
Abstract:

The paper presents a structural approach to configure the technical system of a learning factory by considering learning targets and maximizing the utility. Local scope conditions and intended competencies are used to operationalize requirements. The composition of the module-based technical system can be optimized by maximizing its overall utility. Therefore, an exact and efficient optimization algorithm is developed solving a multidimensional multiple-choice knapsack problem combined with a two-dimensional bin packing problem. Restrictions are the available budget and the useable area of the learning factory. As a result, the configured technical system enables optimal target orientation of the learning factory. This procedure is finally applied on the Process Learning Factory CiP.

Journal or Publication Title: Procedia Manufacturing, 7th Conference on Learning Factories, Darmstadt, Elsevier B.V.
Volume: 9
Uncontrolled Keywords: learning factory, technical system, competency development
Divisions: 16 Department of Mechanical Engineering
16 Department of Mechanical Engineering > Institute of Production Management, Technology and Machine Tools (PTW)
16 Department of Mechanical Engineering > Institute of Production Management, Technology and Machine Tools (PTW) > CiP Center for industrial Productivity
Date Deposited: 01 Sep 2017 11:28
DOI: 10.1016/j.promfg.2017.04.017
Official URL: https://doi.org/10.1016/j.promfg.2017.04.017
Export:

Optionen (nur für Redakteure)

View Item View Item