Open Innovation: The New Imperative for Creating and Profiting from Technology

Digital Twin is one of the promising digital technologies being developed at present to support digital transformation and decision making in multiple industries. While the concept of a Digital Twin is nearly 20 years old, it continues to evolve as it expands to new industries and use cases. This has resulted in a continually increasing variety of definitions that threatens to dilute the concept and lead to ineffective implementations of the technology. There is a need for a consolidated and generalized definition, with clearly established characteristics to distinguish what constitutes a Digital Twin and what does not. This paper reviews 46 Digital Twin definitions given in the literature over the past ten years to propose a generalized definition that encompasses the breadth of options available and provides a detailed characterization which includes criteria to distinguish the Digital Twin from other digital technologies. Next, a process and considerations for the implementation of Digital Twins is presented through a case study. Digital Twin future needs and opportunities are also outlined.

Digital Twin: Generalization, characterization and implementation

Digital transformation in the maritime transport sector

This paper highlights the development of Digital Twin (DT) technology and its admittance to a variety of applications within the maritime domain in general and surface ships in particular. The conceptual theory behind the evolution of DT is highlighted along with the development of the technology and current progress in practical applications with an exploration of the key milestones in the extension from the electrification of the shipping sector towards the realization of a definitive DT-based system. Existing DT-based applications within the maritime sector are surveyed along with the comprehension of ongoing research work. The development strategy for a formidable DT architecture is discussed, culminating in a proposal of a four-layered DT framework. Considering the importance of DT, an extensive and methodical literature survey has also been carried out, along with a comprehensive scientometric analysis to unveil the methodical footprint of DT in the marine sector, thus leading the way for future work on the design, development and operation of surface vessels using DT applications.

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Digital Twin in the Maritime Domain: A Review and Emerging Trends

This paper aims to present the model of factors which influence the digital transformation in maritime transport sector. The preliminary model is based on a literature review and interviews conducted to identify the relevant factors influencing the digital transformation of stakeholders operating in the maritime transport sector. In order to test the model, the survey was conducted on the sample of Croatian administrative (port authorities, ministry, harbormaster’s offices, etc.) and commercial stakeholders (freight forwarders, agents, terminal operators, etc.) operating in maritime transport sector. The collected data was analyzed using the partial least squares structural equation modeling (PLS-SEM) approach. The research has shown that organizational, technological, and environmental (TOE) factors affect the digitalization of the organizations in the maritime transport sector. As a result of digitalization, changes in business models are visible: organizations in maritime transport sector generate additional revenue from new sources, provide new services, and introduce new sales channels.

/pdf/factors-of-digital-transformation-in-the-maritime-transport-2gspn3s2.pdf

Factors of Digital Transformation in the Maritime Transport Sector

New technologies and possibilities summarized under the keyword Digital Transformation effect massive changes in the organizations’ processes and will lead to tremendous challenges for almost all businesses. Existing business models will be expanded or replaced by digitally driven services. The Industry 4.0 with its autonomous cyber physical production systems and its intelligent products require holistic approaches for and will lead to sustainable changes in the industrial manufacturing. This paper addresses the main fields of Industry 4.0 and Digital Transformation as well as their core concepts. Further the paper describes the key success factors interoperability and the organizations’ ability for innovations. These key success factors are illustrated by three case studies regarding the fields information supply in Facility Management, digital logistics and intrapreneurial behavior as an important source for intraorganizational innovations. Keywords—Digitalization, Digital Transformation, Industry 4.0, Interoperability, Semantic Database, Quality Assurance, Innovation I. CONTEXT OF DIGITALIZATION, DIGITAL TRANSFORMATION AND INDUSTRY 4.0 Digitization has impact on all systems of the global world and on the recent forms of society. There are different ways in which digitization becomes effective. Digital transformation and presentation of information and communication are the classic kind in the core processes of ICT. In addition to it, it includes the digital description and modification of objects, function, processes, services, applications, etc. as components of the digitalized world. The most complex view of digitization is the digital change of systems and subsystems in the whole society. (Fig. 1) Future Technologies Conference (FTC) 2017 2 | P a g e Fig. 1. Selected mainstreams of digitalization The change from the analogue to the digitalized world will already include transformations. Transformation is process of continuous changes initiated by internal or external factors leading to significant quantitative and resulting qualitative new kinds of systems by substitution, elimination or turnaround of whole or parts of former systems or subsystems. Digitization is such a comprehensive key factor inducing transformations so called digital transformations. Different models based on stage theory divide the process of digital transformation into a number of steps. (Fig. 2) Fig. 2. Six stage model for digital transformation [1] The digital transformation has a huge impact on the further development of industry as one of the main fields of application, especially: • Digital transformation offers enormous chances and will place great challenges on industry. • Digital transformation of industry will confront the national economies with tremendous change of structures. • Digital transformation requires because of the huge complexity common and concerted concepts and actions. Four levers for the digital transformation in industry are accentuated and prioritized: Digital data, automation, networking, and digital access to the customers [2]. This transformation is also announced as Industry 4.0. II. CORE CONCEPTS AND MODELS Innovations are inherent for the digital transformation as well as Industry 4.0 because innovation means initiating something new building on the existing and creating a difference to the established ones [3]. The approach is based on the eclecticism because it is not limited to one paradigm or selected assumptions but uses multiple theories and views in order to get complementary insights into a system. Therefore, the digital transformation as complex change should be eclectic, innovative and at the end adaptive and sustainable. Digital transformation is direct related to smart systems, internet of things, industry 4.0 and digital ecosystems lately. Smart Systems are self-sufficient intelligent technical (sub-) systems with advanced functionality, enabled by underlying systems and components, providing heightened functionalities for upgraded and new industrial and consumer products and services [4]. The internet of things is the consistent continuation of the internet of data and information. Because the human-beings are physical and enter information of the physical world into the digital form of communication and computation the internet is primarily a reflection of the world of things more than of ideas [5]. Industry 4.0 will be a new digital stage of organization and control of the whole valueadded chain over the entire product life cycle [6]. The concept of digital ecosystems was based on the idea that ecological, economic and social aspects of collaboration are important for the system development in the real world connected to the virtual world by digitalization. The architecture is swarm-based [7]. There are several approaches which are more or less related to these main themes. Two of the leading reference architectures besides many other approaches are currently the reference architecture model for Industry 4.0, the so called RAMI4.0. (Fig. 3) [8] Fig. 3. Reference architecture model for Industry 4.0 (RAMI4.0) The second one is the Industrial Internet Reference Architecture (II RA) generated by the Industrial Internet Consortium characterized by similar reflections of the digital transformation in industry as the RAMI4.0 approach and focused on the viewpoints of business, usage, functionality, and implementation [9, 10]. Future Technologies Conference (FTC) 2017 3 | P a g e The agreement of the Plattform Industrie 4.0, with its strong roots in the manufacturing industry, and the Industrial Internet Consortium, with its more cross-domain oriented approach, is important for the further development of digital transformation in the field of industrial internet and industry 4.0. Especially, the comparability of the layer structure and contents will improve the common understanding of the forth revolution by digitization in industry and services. The key issue will be realization of the regular technical exchange, the identifying of mappings, differences and enhancements, and the discussion common testing focused on the benefit of interoperability of systems from the different domains [11]. Interoperability of systems and components will be one of the most important innovations, challenges and chances of digital transformations in different fields of R&D as well as domains of applications. III. PIVOTAL ROLE OF INTEROPERABILITY AS A KEY

Digital transformation and industry 4.0 as a complex and eclectic change

One more and more upcoming challenge for IT systems used in the Facility Management domain is the automated acquisition and processing of distributed heterogeneous data. Especially for approval or maintenance processes the mobile access to necessary data constantly gains significance. But because of their limited size particularly mobile devices require new ways for representing the needed amount of information. This conceptual paper discusses new approaches of knowledge acquisition and representation, which enable the efficient support of facility managers in their daily tasks. The underlying research project develops concepts and solutions for the semantic modelling and linking of distributed data as well as its context-based representation on a mobile device via Augmented Reality.

Knowledge Acquisition and Representation in Facility Management: Facility Management with Semantic Technologies and Augmented Reality

For businesses high quality is an extremely important criterion to maintain and improve their competitiveness To ensure the required quality standards for example in the automotive sector, sampling methods are common practice This means taking a number of products out of the production line into a special quality measurement facility at the end of a specified timeframe New 3D measurement approaches use optical systems, consisting of a variable number of stereo camera units, which can be integrated into a production line They allow a highly precise measurement of 3D surfaces in a short time interval and therefore enable companies to check agreed quality of each product within the tact of their production line These measurement systems use stereo photography and photogrammetry to create a 3D model of the scanned product, which can be compared with the belonging predefined standard 3D model If this comparison detects deviations between the compared models the quality management system is able to identify these deviations by utilizing knowledge from a predefined failure catalogue and is thereby enabled to identify the fault's cause as well as its origin In the next step the information about the faults origin is used to inform the relevant positions along the supply chain about the fault and its cause It is furthermore used to supply the maintenance staff with guidelines for the necessary maintenance steps to allow a swift removal of possible defects as well as to trigger intrapreneurial behaviour This paper gives an overview of the measuring system, as well as the concept for an automated failure detection and correction based on the data gained from the optical measurement process and the application of a rule based system

Fault analysis and correction by applying process-integrated measurement in automated production facilities

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Digital transformation and industry 4.0 as a complex and eclectic change

Knowledge Acquisition and Representation in Facility Management: Facility Management with Semantic Technologies and Augmented Reality

Fault analysis and correction by applying process-integrated measurement in automated production facilities