Servitized Enterprises for Distributed Collaborative Commerce

Servitized Enterprises for Distributed Collaborative Commerce: 10.4018/jssmet.2010010105: Agility and innovation are essential for survival in today’s business world. Mergers and acquisitions, new regulations, rapidly changing technolog

An ontology-based model management architecture for service innovation

Organizations have indicated renewed interest in service innovation, design and management, given the growth of service sector. Decision support systems (DSS) play an important role in supporting this endeavor, through management of organizational resources such as data and models. Given the global nature of service value chains, there have been ever increasing demands on managing, sharing, and reusing these heterogeneous and distributed resources, both within and across organizational boundaries, through DSS consisting of database management systems (DBMS) and model management systems (MMS). Analogous to DBMS, model management systems focus on the management of decision models, dealing with representation, storage, and retrieval of models as well as a variety of applications such as analysis, reuse, sharing, and composition of models. Recent developments in the areas of semantic web and ontologies have provided a rich tool set for computational reasoning about these resources in an intelligent manner. In this chapter, we leverage these advances and apply service-oriented design principles to propose an ontology-based model management architecture supporting service innovation. The architecture is illustrated with case study scenarios and current state of implementation. The role of potential information technologies in supporting the architecture is also discussed. We then provide a roadmap to make advancements in research in this direction

Industry 4.0 for SMEs

This open access book explores the concept of Industry 4.0, which presents a considerable challenge for the production and service sectors. While digitization initiatives are usually integrated into the central corporate strategy of larger companies, smaller firms often have problems putting Industry 4.0 paradigms into practice. Small and medium-sized enterprises (SMEs) possess neither the human nor financial resources to systematically investigate the potential and risks of introducing Industry 4.0. Addressing this obstacle, the international team of authors focuses on the development of smart manufacturing concepts, logistics solutions and managerial models specifically for SMEs. Aiming to provide methodological frameworks and pilot solutions for SMEs during their digital transformation, this innovative and timely book will be of great use to scholars researching technology management, digitization and small business, as well as practitioners within manufacturing companies

Industry 4.0 for SMEs

This open access book explores the concept of Industry 4.0, which presents a considerable challenge for the production and service sectors. While digitization initiatives are usually integrated into the central corporate strategy of larger companies, smaller firms often have problems putting Industry 4.0 paradigms into practice. Small and medium-sized enterprises (SMEs) possess neither the human nor financial resources to systematically investigate the potential and risks of introducing Industry 4.0. Addressing this obstacle, the international team of authors focuses on the development of smart manufacturing concepts, logistics solutions and managerial models specifically for SMEs. Aiming to provide methodological frameworks and pilot solutions for SMEs during their digital transformation, this innovative and timely book will be of great use to scholars researching technology management, digitization and small business, as well as practitioners within manufacturing companies

Engineering framework for service-oriented automation systems

Tese de doutoramento. Engenharia Informática. Universidade do Porto. Faculdade de Engenharia. 201

Multi Agent Systems in Logistics: A Literature and State-of-the-art Review

Based on a literature survey, we aim to answer our main question: “How should we plan and execute logistics in supply chains that aim to meet today’s requirements, and how can we support such planning and execution using IT?†Today’s requirements in supply chains include inter-organizational collaboration and more responsive and tailored supply to meet specific demand. Enterprise systems fall short in meeting these requirements The focus of planning and execution systems should move towards an inter-enterprise and event-driven mode. Inter-organizational systems may support planning going from supporting information exchange and henceforth enable synchronized planning within the organizations towards the capability to do network planning based on available information throughout the network. We provide a framework for planning systems, constituting a rich landscape of possible configurations, where the centralized and fully decentralized approaches are two extremes. We define and discuss agent based systems and in particular multi agent systems (MAS). We emphasize the issue of the role of MAS coordination architectures, and then explain that transportation is, next to production, an important domain in which MAS can and actually are applied. However, implementation is not widespread and some implementation issues are explored. In this manner, we conclude that planning problems in transportation have characteristics that comply with the specific capabilities of agent systems. In particular, these systems are capable to deal with inter-organizational and event-driven planning settings, hence meeting today’s requirements in supply chain planning and execution.supply chain;MAS;multi agent systems

Implementing Shop Floor IT for Industry 4.0

The fourth industrial revolution, Industry 4.0, is a paradigm shift that is currently changing our society and the way we produce things. The first industrial revolution started at the end of the 18th century and was enabled by mechanisation and steam power. The spread of electricity enabled assembly lines and mass production during the first half of the 20th century, which was the second industrial revolution. Industry 3.0 came with the invention of the computer with an increase of automation such as programmable machines and robots. The fourth revolution is upcoming and is supposed to increase productivity and flexibility to the same extent as the previous three. The idea is to utilise recent advances in information technologies and the Internet to interconnect machines, tools, equipment, sensors, and people into decentralised intelligent systems that can sense and adapt to the environment.The term Industry 4.0 was introduced 2011 by the German government as a national programme to boost research and development of the manufacturing industry. Many countries with, including Sweden, has since then started similar initiatives. The aim is to prevent further outsourcing of production to low-cost countries by improving competitiveness with increased automation and flexibility. However, the implementation is slow and many manufacturing companies have only started to computerise and are far from digitalised. There are many challenges in terms of technology, people, and organisation. Many manufacturing companies do not know how to start the process of digitalisation, they lack the knowledge and the organisation.To implement a production environment according to the Industry 4.0 vision the manufacturing organisation and its view on technologies need to change. Part of this change is to design an information technology architecture that enables interconnection of machines, equipment, tools, and people on the shop floor. The aim of this thesis is to aid decision makers in the manufacturing industry to implement a shop floor IT according to the Industry 4.0 paradigm. This was achieved with the design science approach, which means that the researcher has implemented different artefacts (technologies) that have been evaluated. The work is based on six studies that connect to real problems found in the industry today. These studies are presented and discussed with respect to three research questions: important aspects, technological implementations, and effects. Results include concrete and practical examples of how to implement IT artefacts for the shop floor. Furthermore, it highlights the complexity of the problem and shows the need for a holistic and incremental approach

Distributed manufacturing: scope, challenges and opportunities

This discussion paper aims to set out the key challenges and opportunities emerging from distributed manufacturing (DM). We begin by describing the concept, available definitions and consider its evolution where recent production technology developments (such as additive and continuous production process technologies), digitization together with infrastructural developments (in terms of IoT and big-data) provide new opportunities. To further explore the evolving nature of DM, the authors, each of whom are involved in specific applications of DM research, examine through an expert panel workshop environment emerging DM applications involving new production and supporting infrastructural technologies. This paper presents these generalizable findings on DM challenges and opportunities in terms of products, enabling production technologies, and the impact on the wider production and industrial system. Industry structure and location of activities are examined in terms of the democratizing impact on participating network actors. The paper concludes with a discussion on the changing nature of manufacturing as a result of DM, from the traditional centralized, large scale, long lead-time forecast driven production operations, to a new DM paradigm where manufacturing is a decentralized, autonomous near end-user driven activity. A forward research agenda is proposed that considers the impact of DM on the industrial and urban landscape.The Cambridge–Hamied Visiting Lecture Scheme and UKIERIThis is the author accepted manuscript. The final version is available from Taylor & Francis via https://doi.org/10.1080/00207543.2016.119230

Discrete event simulation and virtual reality use in industry: new opportunities and future trends

This paper reviews the area of combined discrete event simulation (DES) and virtual reality (VR) use within industry. While establishing a state of the art for progress in this area, this paper makes the case for VR DES as the vehicle of choice for complex data analysis through interactive simulation models, highlighting both its advantages and current limitations. This paper reviews active research topics such as VR and DES real-time integration, communication protocols, system design considerations, model validation, and applications of VR and DES. While summarizing future research directions for this technology combination, the case is made for smart factory adoption of VR DES as a new platform for scenario testing and decision making. It is put that in order for VR DES to fully meet the visualization requirements of both Industry 4.0 and Industrial Internet visions of digital manufacturing, further research is required in the areas of lower latency image processing, DES delivery as a service, gesture recognition for VR DES interaction, and linkage of DES to real-time data streams and Big Data sets