Title
Assisted Diagnostics Methodology for Complex High-Tech Applications
Author
Velikova, M.
Ypma, A.
Bratosin, C.
Lemmen, V.
van Wijk, R.J.
Publication year
2019
Abstract
Controlling the operations and resolving product performance issues in today’s high-tech production systems, such as semiconductor fabs, becomes a cumbersome task, even for experienced field engineers. To address the pressing need for assisted diagnostics approaches, in this paper we propose a model-based step-wise methodology, based on domain-specific languages and Bayesian networks, to capture domain knowledge and allow automated and guided reasoning in complex end-to-end diagnostics flow. We illustrate the methodology components and show its applied strength in a real industrial setting of semiconductor production chains.
Subject
Industrial Innovation
Knowledge based diagnostics
Domain-specific language
Model-driven engineering
Probabilistic reasoning
Bayesian network
To reference this document use:
http://resolver.tudelft.nl/uuid:c8cf7dda-fda5-4e87-989d-5eed74b8ad3a
TNO identifier
868461
Publisher
Institute of Electrical and Electronics Engineers Inc.
Source
2019 4th International Conference on System Reliability and Safety (ICSRS)
Bibliographical note
2019 4th International Conference on System Reliability and Safety (ICSRS), 20 - 22 November 2019, Rome, Italy
Document type
conference paper