Unveiling Relations in the Industry 4.0 Standards Landscape based on Knowledge Graph Embeddings

Industry~4.0 (I4.0) standards and standardization frameworks have been proposed with the goal of \emph{empowering interoperability} in smart factories. These standards enable the description and interaction of the main components, systems, and processes inside of a smart factory. Due to the growing number of frameworks and standards, there is an increasing need for approaches that automatically analyze the landscape of I4.0 standards. Standardization frameworks classify standards according to their functions into layers and dimensions. However, similar standards can be classified differently across the frameworks, producing, thus, interoperability conflicts among them. Semantic-based approaches that rely on ontologies and knowledge graphs, have been proposed to represent standards, known relations among them, as well as their classification according to existing frameworks. Albeit informative, the structured modeling of the I4.0 landscape only provides the foundations for detecting interoperability issues. Thus, graph-based analytical methods able to exploit knowledge encoded by these approaches, are required to uncover alignments among standards. We study the relatedness among standards and frameworks based on community analysis to discover knowledge that helps to cope with interoperability conflicts between standards. We use knowledge graph embeddings to automatically create these communities exploiting the meaning of the existing relationships. In particular, we focus on the identification of similar standards, i.e., communities of standards, and analyze their properties to detect unknown relations. We empirically evaluate our approach on a knowledge graph of I4.0 standards using the Trans$^*$ family of embedding models for knowledge graph entities. Our results are promising and suggest that relations among standards can be detected accurately.Comment: 15 pages, 7 figures, DEXA2020 Conferenc

An ontology supported risk assessment approach for the intelligent configuration of supply networks

As progress towards globalisation continues, organisations seek ever better ways with which to configure and reconfigure their global production networks so as to better understand and be able to deal with risk. Such networks are complex arrangements of different organisations from potentially diverse and divergent domains and geographical locations. Moreover, greater focus is being put upon global production network systems and how these can be better coordinated, controlled and assessed for risk, so that they are flexible and competitive advantage can be gained from them within the market place. This paper puts forward a reference ontology to support risk assessment for product-service systems applied to the domain of global production networks. The aim behind this is to help accelerate the development of information systems by way of developing a common foundation to improve interoperability and the seamless exchange of information between systems and organisations. A formal common logic based approach has been used to develop the reference ontology, utilising end user information and knowledge from three separate industrial domains. Results are presented which illustrate the ability of the approach, together with areas for further work

Semantic Model-Driven PLM Data Interoperability: An Application for Aircraft Ground Functional Testing with Eco-Design Criteria

Part 4: Product and Asset Life Cycle Management in Smart Factories of Industry 4.0International audienceThe latest developments in Model-Based Systems Engineering (MBSE) and Product Life-Cycle Management (PLM) are playing a role in the evolution of the aeronautical industry. Despite the reluctance of this domain to accept the introduction of technology leaps in the production process - mostly due to safety reasons - aircraft manufacturers are slowly moving to a new digital factory concept. The deployment of a PLM Tool for Aircraft Ground Functional testing with Eco-design criteria can be leveraged to improve both sustainability of the assembly line and efficiency of the Ground System Tests process end to end, however, heterogeneous data interoperability represents one of the major challenges in this framework. The ontology-based solution proposed in this work addresses this challenge, thus, shows how semantics can be exploited to streamline the data pipeline throughout a PLM digital platform

Towards Virtual Confidence - Extended Product Lifecycle Management

Product lifecycle management (PLM) systems maintain amongst others the specifications and designs of product, process and resource artefacts and thus serve as the basis for realizing the concept of Virtual Manufacturing, and play a vital role in shortening the leadtimes for the engineering processes. Design of new products requires numerous experiments and test-runs of new facilities that delays the product release and causes high costs if performed in the real world. Virtualization promises to reduce these costs by simulating the reality. However, the results of the simulation must predict the real results to be useful. This is called virtual confidence. We propose a knowledge base approach to capture and maintain the virtual confidence in simulation results. To do so, the provenance of results of real, experimental and simulated processes are recorded and linked via confirmation objects

Modeling Manufacturing Resources: An Ontological Approach

International audienceResource management is at the core of different manufacturing tasks, which need to be seamlessly integrated to optimize production in manufacturing environments. The development of knowledge-base d systems led to the use of ontologies to systematically organize data. Unfortunately, ontologies for resource knowledge representation lack maturity and often rely on context-dependent modeling choices. As a result, the notion of manufacturing resource is treated in disparate, non-homogeneous ways at the expenses of communication and application systems interoperability. The purpose of the paper is to lay down a conceptual framework on manufacturing resources base d on ontology engineering principles. By the end of the paper we will see how different approaches can be harmonized with the proposed approac