Special Session on Industry 4.0

No abstract available

Adaptation of Manufacturing Systems in Dynamic Environment Based on Capability Description Method

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Special Session on Industry 4.0

No abstract available

Cross benefits from cyber-physical systems and intelligent products for future smart industries

The manufacturing industry is facing a technology paradigm change, as also captured in the Industrie 4.0 vision as the fourth industrial revolution. Future smart industries will require to optimize not only their own manufacturing processes but also the use of products and manufacturing resources, their maintenance and their recycling. In this context the strengths and weak nesses of two key concepts, namely Cyber-Physical Systems (CPS) and Intelligent Product (IP) are discussed, and it is suggested that an integration of these two approaches to meet the introduced emergent requirements is beneficial. The integration of CPS and IP is shown via two real-world industrial cases, covering different phases of the product life-cycle, namely the production, use and maintenance phases.Surferl@b is partially funded by ERDF (European Regional Development Fund), and the authors wish to thank the European Union and the Nord-Pas -de-Calais in France region for their support. This work is also (partially) funded by the Operational Program for Competitiveness and Internationalization – COMPETE 2020 and by FCT – Portuguese Foundation for Science and Technology.info:eu-repo/semantics/publishedVersio

Increase the adoption of Agent-based Cyber-Physical Production Systems through the Design of Minimally Invasive Solutions

During the last few years, many approaches were proposed to offer companies the ability to have dynamic and flexible production systems. One of the conventional ap-proaches to solving this problem is the implementation of cyber-physical production sys-tems using multi-agent distributed systems. Although these systems can deal with several challenges faced by companies in this area, they have not been accepted and used in real cases. In this way, the primary objective of the proposed work is to understand the chal-lenges usually found in the adoption of these solutions and to develop a strategy to in-crease their acceptance and implementation. Thus, the document focuses on the design and development of cyber-physical produc-tion systems based on agent approaches, requiring minimal changes in the existing pro-duction systems. This approach aims of reducing the impact and the alterations needed to adopt those new cyber-physical production systems. Clarifying the subject, the author presents a definition of a minimal invasive agent-based cyber-physical production system and, the functional requirements that the designers and developers must respect to imple-ment the new software. From these functional requirements derived a list of design princi-ples that must be fulfilled to design and develop a system with these characteristics. Subsequently, to evaluate solutions that aim to be minimally invasive, an evaluation model based on a fuzzy inference system is proposed, which rank the approaches accord-ing to each of the design principles and globally. In this way, the proposed work presents the functional requirements, design principles and evaluation model of minimally invasive cyber-physical production systems, to increase the adoption of such systems

Capability-based adaptation of production systems in a changing environment

Today’s production systems have to cope with volatile production environments characterized by frequently changing customer requirements, an increasing number of product variants, small batch sizes, short product life-cycles, the rapid emergence of new technical solutions and increasing regulatory requirements aimed at sustainable manufacturing. These constantly changing requirements call for adaptive and rapidly responding production systems that can adjust to the required changes in processing functions, production capacity and the distribution of the orders. This adaptation is required on the physical, logical and parametric levels. Such adaptivity cannot be achieved without intelligent methodologies, information models and tools to facilitate the adaptation planning and reactive adaptation of the systems. In industry it has been recognized that, because of the often expensive and inefficient adaptation process, companies rarely decide to adapt their production lines. This is mainly due to a lack of sufficient information and documentation about the capabilities of the current system and its lifecycle, as well as a lack of detailed methods for planning the adaptation, which makes it impossible to accurately estimate its scale and cost. Currently, the adaptation of production systems is in practice a human driven process, which relies strongly on the expertise and tacit knowledge of the system integrators or the end-user of the system. This thesis develops a capability-based, computer-aided adaptation methodology, which supports both the human-controlled adaptation planning and the dynamic reactive adaptation of production systems. The methodology consists of three main elements. The first element is the adaptation schema, which illustrates the activities and information flows involved in the overall adaptation planning process and the resources used to support the planning. The adaptation schema forms the backbone of the methodology, guiding the use of other developed elements during both the adaptation planning and reactive adaptation. The second element, which is actually the core of the developed methodology, is the formal ontological resource description used to describe the resources based on their capabilities. The overall resource description utilizes a capability model, which divides the capabilities into simple and combined capabilities. The resources are assigned the simple capabilities they possess. When multiple resources are co-operating, their combined capability can be reasoned out based on the associations defined in the capability model. The adaptation methodology is based on the capability-based matching of product requirements and available system capabilities in the context of the adaptation process. Thus, the third main element developed in this thesis is the framework and rules for performing this capability matching. The approach allows automatic information filtering and the generation of system configuration scenarios for the given requirements, thus facilitating the rapid allocation of resources and the adaptation of systems. Human intelligence is used to validate the automatically-generated scenarios and to select the best one, based on the desired criteria. Based on these results, an approach to evaluating the compatibility of an existing production system with different product requirements has been formulated. This approach evaluates the impact any changes in these requirements may have on the production system. The impact of the changes is illustrated in the form of compatibility graphs, which enable comparison between different product scenarios in terms of the effort required to implement the system adaptation, and the extent to which the current system can be utilized to meet the new requirements. It thus aids in making decisions regarding product and production strategies and adaptation

Industrial automation based on cyber-physical systems technologies: Prototype implementations and challenges

Cyber-Physical Systems (CPS) is an emergent approach that focuses on the integration of computational applications with physical devices, being designed as a network of interacting cyber and physical elements. CPS control and monitor real-world physical infrastructures and thus is starting having a high impact in industrial automation. As such design, implementation and operation of CPS and management of the resulting automation infrastructure is of key importance for the industry. In this work, an overview of key aspects of industrial CPS, their technologies and emerging directions, as well as challenges for their implementation is presented. Based on the hands-on experiences gathered from four European innovation projects over the last decade (i.e. SOCRADES, IMC-AESOP, GRACE and ARUM), a key challenges have been identified and a prioritization and timeline are pointed out with the aim to increase Technology Readiness Levels and lead to their usage in industrial automation environments.The authors would like to thank for their support the European Commission, and the partners of the EU FP6 SOCRADES (www.socrades.net), EU FP7 GRACE (www.grace-project.org), EU FP7 IMC-AESOP (www.imc-aesop.eu) and EU FP7 ARUM (www.arum-project.eu) projects, for their fruitful support and discussions.info:eu-repo/semantics/publishedVersio

Standardization in cyber-physical systems: the ARUM case

Cyber-physical systems concept supports the realization of the Industrie 4.0 vision towards the computerization of traditional industries, aiming to achieve intelligent and reconfigurable factories. Standardization assumes a critical role in the industrial adoption of cyber-physical systems, namely in the integration of legacy systems as well as the smooth migration from existing running systems to the new ones. This paper analyses some existing standards in related fields and presents identified limitations and efforts for a wider acceptance of such systems by industry. A special attention is devoted to the efforts to develop a standard-compliant service-oriented multi-agent system solution within the ARUM project.info:eu-repo/semantics/publishedVersio