Knowledge Change Management and Analysis in Engineering

Abstract

Knowledge is changing rapidly within the engineering process of Cyber-Physical Production Systems (CPPS) characterized by the collaborative work of engineers from diverse engineering disciplines. Such rapid changes lead to the need for management and analysis of knowledge changes in order to preserve knowledge consistency. Knowledge change management and analysis (KCMA) in Multi-Disciplinary Engineering (MDEng) environments is a challenging task since it involves heterogeneous, versioned, and linked data in a missioncritical fashion, where failure to provide correct data could be costly. Although, there are several available solutions for addressing general issues of KCMA, from fields as diverse as Model Based Engineering (model co-evolution), Databases (database schema evolution), and Semantic Web Technology (ontology versioning), solving KCMA in engineering remains a challenging task. In this chapter, we investigate issues related to KCMA in MDEng environments. We provide a definition of this task and some of its challenges and we overview technologies that can be potentially used for solving KCMA tasks from the three research fields mentioned above. We then define a technology agnostic solution approach inspired by the Ontology-Based Information Integration approach from Semantic Web research as a first step towards a complete KCMA solution and provide an indication of how this solution concept could be implemented using state of the art Semantic Web technologies.