Abstract
ABSTRACT The fourth industrial revolution is increasingly implemented in most fields and categories of industry. The use of several highly developed technologies generates huge amounts of heterogeneous data and knowledge, hence the need to manage it in order to facilitate its reuse. This article proposes a global approach of knowledge management, from the analysis and development of the knowledge base structuring models, to the implementation phase using knowledge engineering tools. This research work is part of a global knowledge-based decision support framework that ensures several axes of decision support, this article deals with the diagnosis axis. It provides analysis and comprehension of the failures occurring during production. The approach has been implemented as a first demonstrator tested in a real case study: the aeronautical mechanical machining industry. This article details the issues of this implementation and its interest for the validation of the approach.
Highlights
Since its appearance, the fourth industrial revolution has not ceased to affect most fields of activity and its implementation presents an interesting research topic in several disciplines
The machine’s computer numerical control (CNC) provides additional information related to the operational context of manufacturing process
These models are strongly linked since they are all based on a common list of industrial objects and components. Among these components were identified four that match well with this project: product, process, context, resources, and people. While these objects represent essential elements for each industry and they are considered fundamental to model the global industrial knowledge base, previous modelling approaches do not cover all of these elements simultaneously
Summary
The fourth industrial revolution has not ceased to affect most fields of activity and its implementation presents an interesting research topic in several disciplines. Among the methods of artificial intelligence, decision support systems (thereafter, DSS) are used to analyse a problematic context and to propose a suitable solution to correct or avoid it (Teti 2015). These techniques have been too widespread for years and their usefulness is increasing with the appearance of new information technologies. The scientific proposal ends with the presentation of the usefulness of the knowledge management approach for the development of the second decision support axis: diagnosis
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