Intelligent Manufacturing in the Context of Industry 4.0: A Review

Manufacturing industry profoundly impact economic and societal progress. As being a commonly accepted term for research centers and universities, the Industry 4.0 initiative has received a splendid attention of the business and research community. Although the idea is not new and was on the agenda of academic research in many years with different perceptions, the term “Industry 4.0” is just launched and well accepted to some extend not only in academic life but also in the industrial society as well. While academic research focuses on understanding and defining the concept and trying to develop related systems, business models and respective methodologies, industry, on the other hand, focuses its attention on the change of industrial machine suits and intelligent products as well as potential customers on this progress. It is therefore important for the companies to primarily understand the features and content of the Industry 4.0 for potential transformation from machine dominant manufacturing to digital manufacturing. In order to achieve a successful transformation, they should clearly review their positions and respective potentials against basic requirements set forward for Industry 4.0 standard. This will allow them to generate a well-defined road map. There has been several approaches and discussions going on along this line, a several road maps are already proposed. Some of those are reviewed in this paper. However, the literature clearly indicates the lack of respective assessment methodologies. Since the implementation and applications of related theorems and definitions outlined for the 4th industrial revolution is not mature enough for most of the reel life implementations, a systematic approach for making respective assessments and evaluations seems to be urgently required for those who are intending to speed this transformation up. It is now main responsibility of the research community to developed technological infrastructure with physical systems, management models, business models as well as some well-defined Industry 4.0 scenarios in order to make the life for the practitioners easy. It is estimated by the experts that the Industry 4.0 and related progress along this line will have an enormous effect on social life. As outlined in the introduction, some social transformation is also expected. It is assumed that the robots will be more dominant in manufacturing, implanted technologies, cooperating and coordinating machines, self-decision-making systems, autonom problem solvers, learning machines, 3D printing etc. will dominate the production process. Wearable internet, big data analysis, sensor based life, smart city implementations or similar applications will be the main concern of the community. This social transformation will naturally trigger the manufacturing society to improve their manufacturing suits to cope with the customer requirements and sustain competitive advantage. A summary of the potential progress along this line is reviewed in introduction of the paper. It is so obvious that the future manufacturing systems will have a different vision composed of products, intelligence, communications and information network. This will bring about new business models to be dominant in industrial life. Another important issue to take into account is that the time span of this so-called revolution will be so short triggering a continues transformation process to yield some new industrial areas to emerge. This clearly puts a big pressure on manufacturers to learn, understand, design and implement the transformation process. Since the main motivation for finding the best way to follow this transformation, a comprehensive literature review will generate a remarkable support. This paper presents such a review for highlighting the progress and aims to help improve the awareness on the best experiences. It is intended to provide a clear idea for those wishing to generate a road map for digitizing the respective manufacturing suits. By presenting this review it is also intended to provide a hands-on library of Industry 4.0 to both academics as well as industrial practitioners. The top 100 headings, abstracts and key words (i.e. a total of 619 publications of any kind) for each search term were independently analyzed in order to ensure the reliability of the review process. Note that, this exhaustive literature review provides a concrete definition of Industry 4.0 and defines its six design principles such as interoperability, virtualization, local, real-time talent, service orientation and modularity. It seems that these principles have taken the attention of the scientists to carry out more variety of research on the subject and to develop implementable and appropriate scenarios. A comprehensive taxonomy of Industry 4.0 can also be developed through analyzing the results of this review.

Literature review of Industry 4.0 and related technologies

To study the operational behaviour of λ-terms, we will use the denotational (mathematical) approach. A denotational semantics for a language is based on the choice of a space of semantics values, or denotations, where terms are to be interpreted. Choosing a space with nice mathematical properties can help in proving the semantic properties of terms, since to this aim standard mathematical techniques can be used.

λ Δ -Models

Multiagent Systems is the title of a collection of papers dedicated to surveying specific themes of Multiagent Systems (MAS) and Distributed Artificial Intelligence (DAI). All of them authored by leading researchers of this dynamic multidisciplinary field.

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Multiagent systems: a modern approach to distributed artificial intelligence

About the Authors.Preface.Note to the Reader.Acknowledgments.Figures.Tables.Listings.I Basics.1. Computing with Services.2. Basic Standards for Web Services.3. Programming Web Services.4. Enterprise Architectures.5. Principles of Service-Oriented Computing.II Description.6. Modeling and Representation.7. Resource Description Framework.8. Web Ontology Language.9. Ontology Management.III Engagement.10. Execution Models.11. Transaction Concepts.12. Coordination Frameworks for Web Services.13. Process Specifications.14. Formal Specification and Enactment.IV Collaboration.15. Agents.16. Multiagent Systems.17. Organizations.18. Communication.V Solutions.19. Semantic Service Solutions.20. Social Service Selection.21. Economic Service Selection.VI Engineering.22. Building SOC Applications.23. Service Management.24. Security.VII Directions.25. Challenge and Extensions.VIII Appendices.Appendix A: XML and XML Schema.Appendix B: URI, URN, URL and UUID.Appendix C: XML Namespace Abbreviations.Glossary.About the Authors.Bibliography.Index.

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Service-Oriented Computing: Semantics, Processes, Agents

A review of internet-based product information sharing and visualization

The rapidly changing needs and opportunities of today's global market require unprecedented levels of interoperability to integrate diverse information systems to share knowledge and collaborate among organizations. The combination of Web services and software agents provides a promising computing paradigm for efficient service selection and integration of inter-organizational business processes. This paper proposes an agent-based service-oriented integration architecture to leverage manufacturing scheduling services on a network of virtual enterprises. A unique property of this approach is that the scheduling process of an order is orchestrated on the Internet through the negotiation among agent-based Web services. A software prototype system has been implemented for inter-enterprise manufacturing resource sharing. It demonstrates how the proposed service-oriented integration architecture can be used to establish a collaborative environment that provides dynamic resource scheduling services.

An agent-based service-oriented integration architecture for collaborative intelligent manufacturing

The Grid concept has recently emerged as a vision for future network based computing, by enabling seamless integration of computing systems and clusters, data storage, specialized networks and sophisticated analysis and visualization software. Intelligent agents can play an important role in helping achieve the Grid vision. Although agents have been applied to computing load balancing for many years, attempts to apply intelligent agents in realizing the Grid vision have been made by academic researchers during the past few years. Due to the highly heterogeneous and complex computing environments, effective load balancing for Grid computing is a very difficult problem, even though intelligent agents are used. In this paper we attempt to highlight major challenges in managing resources in a Grid computing environment and present some of our recent work on adaptive negotiation strategies for agent-based load balancing and Grid computing. The proposed approach is to implement multiple negotiation models/protocols/strategies that can be selected by the system automatically to adapt to computation needs as well as changing computing resource environment.

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Adaptive Negotiation for Agent-Based Grid Computing

WebBlow: a Web/agent-based multidisciplinary design optimization environment

Localization in Wireless Sensor Networks has become a significant research challenge, attracting many researchers in the past decade. This paper provides a review of basic techniques and the state-of-the-art approaches for wireless sensors localization. The challenges and future research opportunities are discussed in relation to the design of the collaborative workspaces based on cooperative wireless sensor networks.

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Hamada Ghenniwa

Papers

A review of internet-based product information sharing and visualization

An agent-based service-oriented integration architecture for collaborative intelligent manufacturing

Adaptive Negotiation for Agent-Based Grid Computing

WebBlow: a Web/agent-based multidisciplinary design optimization environment

Localization in cooperative Wireless Sensor Networks: A review