Authors:
Alexander Diedrich
1
;
Björn Böttcher
1
and
Oliver Niggemann
2
Affiliations:
1
Fraunhofer IOSB-INA, Germany
;
2
Institute for Industrial IT, Germany
Keyword(s):
Constraint Satisfaction, Feature Models, Product Line Engineering, Minimum Correction Subsets.
Related
Ontology
Subjects/Areas/Topics:
Artificial Intelligence
;
Constraint Satisfaction
;
Enterprise Information Systems
;
Human-Computer Interaction
;
Industrial Applications of AI
;
Intelligent User Interfaces
;
Knowledge-Based Systems
;
Soft Computing
;
Symbolic Systems
Abstract:
In recent years, the complexity of production plants and therefore of the underlying automation systems has grown significantly. This makes the manual design of automation systems increasingly difficult. As a result, errors are found only during production, plant modifications are hindered by not maintainable automation solutions and criteria such as energy efficiency or cost are often not optimized. This work shows how utilizing Minimum Correction Subsets (MCS) of a Constraint Satisfaction Problem improves the collaboration of automation system designers and prevents inconsistent requirements and thus subsequent errors in the design. This opens up a new field of application for constraint satisfaction techniques. As a use case, an example from the field of automation system design is presented. To meet the automation industry’s requirement for standardised solutions that assure reliability, the calculation of MCS is formulated in such a way that most constraint solvers can be used w
ithout any extensions. Experimental results with typical problems demonstrate the practicalness concerning runtime and hardware resources.
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