TOWARDS ADAPTIVE ENTERPRISES USING DIGITAL TWINS

Modern enterprises are large complex systems operating in highly dynamic environments thus requiring quick response to a variety of change drivers. Moreover, they are systems of systems wherein understanding is available in localized contexts only and that too is typically partial and uncertain. With the overall system behaviour hard to know a-priori and conventional techniques for system-wide analysis either lacking in rigour or defeated by the scale of the problem, the current practice often exclusively relies on human expertise for monitoring and adaptation. We present an approach that combines ideas from modeling & simulation, reinforcement learning and control theory to make enterprises adaptive. The approach hinges on the concept of Digital Twin - a set of relevant models that are amenable to analysis and simulation. The paper describes illustration of approach in two real world use cases

Using the Process Digital Twin as a tool for companies to evaluate the Return on Investment of manufacturing automation

The fourth industrial revolution is gaining momentum, but still lacks full realization. Several studies suggest that many companies around the world have begun the digital transformation undertaking, but most are still far from full adoption and yet fail to see the full economic potential, being stuck in what has been called "pilot purgatory”. Digitalization is largely recognized as an accelerator and enabler for full automation in manufacturing, but companies are still struggling to assess the return on investment and the impact on operational performance indicators. Therefore, companies, especially SMEs characterized by dynamic, high-value, high-mix, and low-volume contexts, are reluctant to invest further. By incorporating simulation, data analytics and behavioral models, digital twins may also be used to support automation solutions ramp-up, demonstrate their impact evaluation, usage scenarios, eliminating the need for physical prototypes, reducing development time, and improving quality. Few forward-thinking companies are pursuing the digital transformation path, while the majority are clipping the wings of a transformation that is essential for a sustainable manufacturing. This paper describes a theoretical approach to exploit the digital twin technology to gather insights towards a realistic economical assessment of full automation solutions, to back and encourage investments to realize the potential of the digital manufacturing transformation. The approach is being tested under the European Union’s Horizon 2020 research and innovation program under grant agreement No. 958363, which provides an opportunity to assess how the various components of the method are constructed, how complex they are, and what level of effort is required, using a practical example

Using the Process Digital Twin as a tool for companies to evaluate the Return on Investment of manufacturing automation

The fourth industrial revolution is gaining momentum, but still lacks full realization. Several studies suggest that many companies around the world have begun the digital transformation undertaking, but most are still far from full adoption and yet fail to see the full economic potential, being stuck in what has been called "pilot purgatory”. Digitalization is largely recognized as an accelerator and enabler for full automation in manufacturing, but companies are still struggling to assess the return on investment and the impact on operational performance indicators. Therefore, companies, especially SMEs characterized by dynamic, high-value, high-mix, and low-volume contexts, are reluctant to invest further. By incorporating simulation, data analytics and behavioral models, digital twins may also be used to support automation solutions ramp-up, demonstrate their impact evaluation, usage scenarios, eliminating the need for physical prototypes, reducing development time, and improving quality. Few forward-thinking companies are pursuing the digital transformation path, while the majority are clipping the wings of a transformation that is essential for a sustainable manufacturing. This paper describes a theoretical approach to exploit the digital twin technology to gather insights towards a realistic economical assessment of full automation solutions, to back and encourage investments to realize the potential of the digital manufacturing transformation. The approach is being tested under the European Union’s Horizon 2020 research and innovation program under grant agreement No. 958363, which provides an opportunity to assess how the various components of the method are constructed, how complex they are, and what level of effort is required, using a practical example.publishedVersio

A tool for holistic assessment of digitalization capabilities in manufacturing SMEs

In a constantly evolving global market, manufacturing companies need to be flexible and adaptive to survive. Digital twins of production systems have been proposed as one part of the solution, however this comes with multiple challenges. Manufacturing SMEs have limited resources and need to direct their efforts in this area wisely. This paper presents a tool for holistic assessment of an SME manufacturer\u27s level of digitalization, in order to visualize current gaps and guide digitalization efforts over a production system\u27s life cycle. The tool was empirically developed together with Manufacturing SMEs and has strengthened their digitalization awareness and capabilities

Review and Position

Publisher Copyright: © 2022, IFIP International Federation for Information Processing.Strategic decision-making still struggles to cope with the interference of people in its proposed plans, creating a gap between idealised and real-world versions. Even when the existence of humans is considered, models and abstractions tend to be simplistic and lacking in complex human traits (e. g. creativity, sentiment). We analyse the current scientific landscape in the dimensions that overlap in the field of strategic decision making and posit that to provide means to a more informed and robust decision-making, humans should not only be seen as elements that need to accept and adopt decisions, but also as actors that affect their outcomes. Humans should be understood as central pieces and the strategic decision-making process should thus consider their importance both in techniques that foster co-creation, and also in developing dynamic models that demonstrate their influence and impact. In this article, we describe this problem-space and outline an approach integrating Decision Intelligence, Enterprise Architecture, Design Thinking, and architectural principles to achieve a human-centric, adaptive strategic design. We also discuss the influence of information presentation and visuals for meaningful participation in strategic decision-making processes.authorsversionpublishe

Generic Design Methodology for Smart Manufacturing Systems From a Practical Perspective. Part II—Systematic Designs of Smart Manufacturing Systems

In a traditional system paradigm, an enterprise reference model provides the guide for practitioners to select manufacturing elements, configure elements into a manufacturing system, and model system options for evaluation and comparison of system solutions against given performance metrics. However, a smart manufacturing system aims to reconfigure different systems in achieving high-level smartness in its system lifecycle; moreover, each smart system is customized in terms of the constraints of manufacturing resources and the prioritized performance metrics to achieve system smartness. Few works were found on the development of systematic methodologies for the design of smart manufacturing systems. The novel contributions of the presented work are at two aspects: (1) unified definitions of digital functional elements and manufacturing systems have been proposed; they are generalized to have all digitized characteristics and they are customizable to any manufacturing system with specified manufacturing resources and goals of smartness and (2) a systematic design methodology has been proposed; it can serve as the guide for designs of smart manufacturing systems in specified applications. The presented work consists of two separated parts. In the first part of paper, a simplified definition of smart manufacturing (SM) is proposed to unify the diversified expectations and a newly developed concept digital triad (DT-II) is adopted to define a generic reference model to represent essential features of smart manufacturing systems. In the second part of the paper, the axiomatic design theory (ADT) is adopted and expanded as the generic design methodology for design, analysis, and assessment of smart manufacturing systems. Three case studies are reviewed to illustrate the applications of the proposed methodology, and the future research directions towards smart manufacturing are discussed as a summary in the second part

Challenges and Potentials of Digital Twins and Industry 4.0 in Product Design and Production for High Performance Products

Digital twins offer great opportunities in various domains of the product engineering process. However, current approaches to the use of digital twins only focus on different separated disciplines. In contrast to that, it is expected that the holistic use of digital twin models in product development and production will dominate future product generations, because they allow to create high-performance products competitively. This paper explores important challenges and future potentials of digital twins and Industry 4.0 for the seamless integration of product specification and production. In this regard, approaches of linking digital twins to other domains open up new possibilities in tolerance allocation and production integration. Thereby, the most efficient product specifications in technical and economic terms are achieved for the manufacturer. In addition, the connectivity of Industry 4.0 broadens the scope and enables the evaluation of alternative approaches in production planning and control. Approaches at the organizational level, product functions with specifications beyond the technological limits and production control strategies (e.g. order dispatching) ensure high performance operations. Simulations with a digital production twin with integrated digital product twin allow early estimations even before the actual ramp-up of the product. The future challenge addressed in this paper is to define a consistent framework for the holistic use of digital twins in the entire product development process, which requires the integration of product designers and production planner concepts

Closing the Implementation Gap of Digital Twins

Since the manufacturing industry is facing increasingly advancing digitalization, digital twins (DT) have become a popular means for integrating various actors\u27 value creation using a smart product. DTs are information systems that connect the physical and virtual worlds. The design of DTs is time-consuming, expensive, and lacks appropriate prescriptive design knowledge for its development. Design principles (DP) represent a mechanism to codify design knowledge into prescriptive knowledge. However, the mostly abstract DPs are often difficult for practitioners to operationalize during software development projects, rendering the design knowledge difficult to access. The paper at hand addresses these issues by providing a reference model for DT development as a semi-abstract artifact. The model has been constructed by drawing on a literature review and empirical cases in the manufacturing industry. The reference model includes multiple adaptation mechanisms to ensure a flexible development of company-specific DTs