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KoMMDia: Dialogue-Driven Assistance System for Fault Diagnosis and Correction in Cyber-Physical Production Systems

 
: Rahm, Julian; Graube, Markus; Müller, Romy; Klaeger, Tilman; Schegner, Luise; Schult, Andre; Bönsel, Rica; Carsch, Sebastian; Oehm, Lukas; Urbas, Leon

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Institute of Electrical and Electronics Engineers -IEEE-; IEEE Industrial Electronics Society -IES-:
IEEE 23rd International Conference on Emerging Technologies and Factory Automation, ETFA 2018. Proceedings : Politecnico di Torino, Torino, Italy, 04-07 September 2018
Piscataway, NJ: IEEE, 2018
ISBN: 978-1-5386-7108-5
ISBN: 978-1-5386-7107-8
ISBN: 978-1-5386-7109-2
pp.999-1006
International Conference on Emerging Technologies and Factory Automation (ETFA) <23, 2018, Torino>
English
Conference Paper
Fraunhofer IVV ()

Abstract
In complex production systems, the diagnosis and correction of faults requires operators to possess a deep understanding of the specific processes and machines as well as general knowledge about the interactions between different system components. However, in actual work environments operator qualification and experience is quite diverse, which leads to an immense variability in the time required for fault diagnosis and in the quality of corrective actions. Both time and quality of fault diagnosis and correction are vital parameters in the functioning of a plant, because downtimes have severe economic consequences and thus should be kept to a minimum. With the introduction of highly complex and flexible cyber-physical production systems, these problems are aggravated as fault sources vary and diagnosis becomes even more challenging. The paper presents a concept for a self-learning assistance system that supports operators in finding and evaluating solution strategies for complex faults. This concept applies a question-answer approach which allows for an incremental, dialogue-based establishment of common ground between operators and the assistance system.

: http://publica.fraunhofer.de/documents/N-581592.html