Knowledge-Centric Systems Engineering is an industrial approach to systems and software engineering that advocates the development and use of knowledge bases that represent system domains. This approach can also exploit artificial intelligence techniques. These means can be used for early V&V (verification and validation) activities, e.g., for system artefact quality analysis and traceability management. This paper presents advances made in these activities with the SES Engineering Studio industrial tool and its underlying methods to meet further early-V& V needs in practice. The methods and the tool have been improved to better address model quality analysis, traceability project management, trace specification, and compliance with standards. For validation, we have initially applied the new features on a medical device. This has also allowed us to study the benefits of the features. The results show that the advances made can lead to wider system artefact analyses, more precise traceability management, better system artefacts, lower V & V effort, and lower issue resolution costs. All in all, the paper presents specific examples of how early- V & V industrial practices and tools can be improved.

Society increasingly depends on electronic systems and components (ECS) whose reliability must be ensured throughout their lifecycle. ECS reliability must be addressed since early development stages and the means used to this end must fit other systems engineering practices. Within this context, we present an industrial approach for model-based reliability-oriented system design. It links model-based systems engineering with Arcadia/Capella and knowledge-centric systems engineering with the Systems Engineering Suite. The approach deals with system modelling, ontology development, structured textual requirements specification, traceability management, and model quality analysis, all of them targeted at ECS reliability. We also present the validation steps taken.