TY - GEN
T1 - Modeling cyclic interactions within a production environment using transition adaptive recurrent fuzzy systems
AU - Stahl, Benjamin
AU - Diepold, Klaus J.
AU - Pohl, Johannes
AU - Greitemann, Josef
AU - Plehn, Christian
AU - Koch, Jonas
AU - Lohmann, Boris
AU - Reinhart, Gunther
N1 - Funding Information:
The authors thank the German Research Foundation (DFG) for funding this work as part of the collaborative research project ‘Managing cycles in innovation processes -Integrated development of product service systems based on technical products’ (SFB 768). This paper is a result of a cooperation of the subprojects A3, A7, B3, and B4.
PY - 2013
Y1 - 2013
N2 - Numerous dynamic influences affect producing companies and require a continuous adaptation of the production. At present, modeling these influences and their interdependencies is mainly limited to quantitative factors. In this paper, an approach is proposed that allows to model the missing qualitative influences and their interdependencies via recurrent fuzzy systems (RFS), where the transitions between the state variables are additionally weighted (transition adaptation). This allows an easy adaption of a production environment's behavior while maintaining the interpretability of the model and the model-based analysis results. To handle the complexity of the resulting models, a structured way to simplify a large fuzzy rule base, to reduce the number of required weighting coefficients, and to merge the state variable onto a single production effectiveness value is shown. All of this is directly illustrated by exemplarily modeling the influence of some relevant qualitative factors onto a production environment.
AB - Numerous dynamic influences affect producing companies and require a continuous adaptation of the production. At present, modeling these influences and their interdependencies is mainly limited to quantitative factors. In this paper, an approach is proposed that allows to model the missing qualitative influences and their interdependencies via recurrent fuzzy systems (RFS), where the transitions between the state variables are additionally weighted (transition adaptation). This allows an easy adaption of a production environment's behavior while maintaining the interpretability of the model and the model-based analysis results. To handle the complexity of the resulting models, a structured way to simplify a large fuzzy rule base, to reduce the number of required weighting coefficients, and to merge the state variable onto a single production effectiveness value is shown. All of this is directly illustrated by exemplarily modeling the influence of some relevant qualitative factors onto a production environment.
KW - Adaptation
KW - Dynamic behavior
KW - Fuzzy expert systems
KW - Production systems
KW - Recurrent fuzzy systems
UR - http://www.scopus.com/inward/record.url?scp=84884315947&partnerID=8YFLogxK
U2 - 10.3182/20130619-3-RU-3018.00534
DO - 10.3182/20130619-3-RU-3018.00534
M3 - Conference contribution
AN - SCOPUS:84884315947
SN - 9783902823359
T3 - IFAC Proceedings Volumes (IFAC-PapersOnline)
SP - 1979
EP - 1984
BT - 7th IFAC Conference on Manufacturing Modelling, Management, and Control, MIM 2013 - Proceedings
PB - IFAC Secretariat
T2 - 7th IFAC Conference on Manufacturing Modelling, Management, and Control, MIM 2013
Y2 - 19 June 2013 through 21 June 2013
ER -