The Impacts of Semantic Technologies on Industrial Systems

The Impacts of Semantic Technologies on Industrial Systems

Vladimír Marík (Rockwell Automation Research Center, Prague, Czech Republic and Technical University in Prague, Czech Republic), Pavel Vrba (Rockwell Automation Research Center, Prague, Czech Republic) and Marek Obitko (Rockwell Automation Research Center, Czech Republic)
DOI: 10.4018/978-1-60566-650-1.ch037
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Abstract

Industrial systems face the challenges of robust and flexible control of industrial processes while satisfying the demand of mass customization and reduced time to market. To meet these requirements, systems need to work in a distributed manner, because the traditional centralized approaches are not sufficient. To achieve automated cooperation and coordination of distributed components at a larger scale, semantic technologies are necessary to enable truly open systems. The authors review state of the art of the research of ontologies, Semantic Web and Semantic Web services, together with advances of usage of semantic technologies in industry. The usage of semantic technologies is illustrated on two applications – semantics in multi-agent manufacturing systems and structural search in industrial data.
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The Impacts Of Semantic Technologies On Industrial Systems

Industrial systems face the challenges of robust and flexible control of industrial processes while satisfying the demand of mass customization and reduced time to market. To meet these requirements, systems need to work in a distributed manner, because the traditional centralized approaches are not sufficient. However, the distributed architectures used in industrial control systems are still tightly coupled from the point of view of system integration. To achieve automated cooperation and coordination of distributed components at a larger scale, semantic technologies are necessary to enable truly open systems that can communicate while the configuration of the system is dynamically changing.

Today, the systems used in manufacturing industry are programmed with the focus on performing particular tasks rather than on interoperability in a dynamic environment. This is understandable, but in order to achieve better integration from the shop floor level up to the level of virtual enterprises, these systems have to use explicit semantics to describe the interpretation of the data they provide. So far, the interoperability has been resolved mainly at the physical and syntactical level. We can see the parallel with the World Wide Web (WWW), where the level of exchanging and interpreting documents is resolved, but the semantical level is being investigated within Semantic Web research. As the networked and distributed industrial systems have been influenced by the traditional WWW, they are apparently going to be influenced by Semantic Web as well.

In this chapter, we review state of the art of the research of ontologies, Semantic Web and Semantic Web services as the most relevant technologies enabling proliferation of semantics in industrial systems. We pay special attention to possible applications in distributed industrial systems and show how semantics can be applied to such systems. We focus on the multi-agent and holonic techniques that provide suitable paradigm for such systems and provide clear modeling framework for introducing semantics. We also review the ongoing efforts to create general purpose reusable ontologies for the industrial domain.

We discuss specific characteristics and requirements of industrial automation domain in contrast to the common issues of Semantic Web. The Web technologies have to handle the problems of semantical heterogeneity, inconsistency and uncontrolled behavior of individual sites. In the industrial domain, this can be avoided to some degree. The impact of discrepancies is also different – for instance inaccurate search result is acceptable, but inaccuracy in industrial domain may lead to potential damage of equipment, unnecessary material consumption, or delays in delivery of the manufactured product. The important difference is that we are dealing directly with the physical components in a real-world environment.

The applications of semantic technologies in industrial domain are illustrated on two research projects of Rockwell Automation: (i) semantics-enhanced agent-based material handling control system and (ii) structural search.

The first project aims at adding semantics to a multi-agent control system for material handling tasks, like for example transportation of materials and semi-products within an assembly line. We show how semantics can be utilized for reasoning in agent’s knowledge base. The choreography and orchestration of Semantic Web services provide important inspiration – in reconfigurable industrial systems, it is needed to discover suitable service providers, negotiate the contract, monitor task execution and resolve potential runtime problems.

The latter project focuses on structural search. One of the core applications of the Semantic Web is semantic search, i.e., search within semantically enriched data. The design, operation and maintenance of a manufacturing system is very knowledge intensive task and involves handling of information stored in different forms – for example function blocks or ladder diagrams describing the real-time control system, SCADA (Supervisory Control And Data Acquisition) and HMI (Human Machine Interface) views, collected historical events, etc. We show the advantages of the usage of Semantic Web technologies for enabling search within structured and integrated data. The result helps humans to express queries that involve not only looking for keywords, but also structural relations between pieces of information.

Another potential application of semantic-based systems in manufacturing is the area of human-machine interfaces. They could serve for visualization and further analysis of information where the direct linkage of the manufacturing-oriented semantic systems with the Semantic Web might be required.

Key Terms in this Chapter

Programmable Logic Controller (PLC): Special computer with extensive input/output arrangements dedicated to industrial control purposes, such as assembly line machinery control

SCADA/HMI: The Supervisory Control And Data Acquisition (SCADA) systems are used to monitor and control automated processes; part of these systems is Human-Machine Interface (HMI) serving for visualization as well as getting feedback from human.

Semantic Web: Extension of the hypertext World Wide Web in which the semantics of information is provided to allow automated searching, understanding and processing of the content.

Ontology: Formal explicit specification of conceptualization, in a form of description of concepts and relations existing in a domain of interest, including restrictions, in form that allows automated processing including reasoning.

Ladder Logic: The ladder logic was originally invented to describe logic made from relays and is still useful in manufacturing area because engineers and technicians can understand and use it without much additional training.

Material Handling: Equipment used for movement and storage of material, parts and products within a facility or warehouse.

Semantic Web Services: Semantic enrichment of current Web Services allowing automated discovery, composition and execution of services.

Semantic Search: Search that uses semantic description of data to disambiguate terms used in queries to return only highly relevant results even for queries that are not stated precisely.

Structural Search: Search that allows utilization of structural relations in data for query building, query evaluation and automated reasoning, but does not offer semantic disambiguation.

Agent-Based Manufacturing Control: Highly distributed and flexible manufacturing control system based on autonomous, intelligent and cooperative entities – agents.

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