Bayesian Networks (BN) have in previous literature been recognized as a powerful tool for safety analysis, with several advantages over traditional methods such as fault trees. The construction of BNs for safety analysis is however cumbersome; no easier than construction of fault trees. The paper therefore presents a systematic method for construction of BNs for analysis. It is recognized that a special kind of BNs is required, namely Causal BNs. The basic principle to construct these Causal BNs is to utilize specifications of services, or requirements, and their relationships. The approach is especially attractive in the context of safety standards (e.g. ISO26262) where specification and traceability of requirements is already mandatory. T...
Gun and rifle manufacturing contain various failures in the process of CNC machining, material suppl...
Over the last decade, Bayesian networks (BNs) have become a popular tool for modeling many kinds of ...
This paper provides a comprehensive data-driven diagnosis approach applicable to complex manufacturi...
Bayesian Networks (BN) provide a robust probabilistic method of reasoning under uncertainty. They ha...
This paper presents a methodology for safety analysis at workplace. The methodology incorporates Bay...
This paper presents an extension of Bayesian networks (BN) applied to reliability analysis. We devel...
Idioms are small, reusable Bayesian network (BN) fragments that represent generic types of uncertain...
In this paper, a model for failure analysis using the theory of Bayesian Belief Networks (BBN), will...
Cyber-physical systems have increasingly intricate architectures and failure modes, which is due to ...
Process plants are particularly subjected to major accidental events, whose catastrophic escalations...
Bayesian Networks (BN) provide a robust probabilistic method of reasoning under uncertainty. They ha...
Bayesian Networks (BN) provide robust probabilistic methods of reasoning under uncertainty, but desp...
International audienceThis paper provides a comprehensive data-driven diagnosis approach applicable ...
Because of modern societies' dependence on industrial control systems, adequate response to system f...
Abstract The emphasis of this exploratory paper is on some maintenance related accidents occurred du...
Gun and rifle manufacturing contain various failures in the process of CNC machining, material suppl...
Over the last decade, Bayesian networks (BNs) have become a popular tool for modeling many kinds of ...
This paper provides a comprehensive data-driven diagnosis approach applicable to complex manufacturi...
Bayesian Networks (BN) provide a robust probabilistic method of reasoning under uncertainty. They ha...
This paper presents a methodology for safety analysis at workplace. The methodology incorporates Bay...
This paper presents an extension of Bayesian networks (BN) applied to reliability analysis. We devel...
Idioms are small, reusable Bayesian network (BN) fragments that represent generic types of uncertain...
In this paper, a model for failure analysis using the theory of Bayesian Belief Networks (BBN), will...
Cyber-physical systems have increasingly intricate architectures and failure modes, which is due to ...
Process plants are particularly subjected to major accidental events, whose catastrophic escalations...
Bayesian Networks (BN) provide a robust probabilistic method of reasoning under uncertainty. They ha...
Bayesian Networks (BN) provide robust probabilistic methods of reasoning under uncertainty, but desp...
International audienceThis paper provides a comprehensive data-driven diagnosis approach applicable ...
Because of modern societies' dependence on industrial control systems, adequate response to system f...
Abstract The emphasis of this exploratory paper is on some maintenance related accidents occurred du...
Gun and rifle manufacturing contain various failures in the process of CNC machining, material suppl...
Over the last decade, Bayesian networks (BNs) have become a popular tool for modeling many kinds of ...
This paper provides a comprehensive data-driven diagnosis approach applicable to complex manufacturi...