Recent technological developments and advances in Artificial Intelligence (AI) have enabled sophisticated capabilities to be a part of Digital Twin (DT), virtually making it possible to introduce automation into all aspects of work processes. Given these possibilities that DT can offer, practitioners are facing increasingly difficult decisions regarding what capabilities to select while deploying a DT in practice. The lack of research in this field has not helped either. It has resulted in the rebranding and reuse of emerging technological capabilities like prediction, simulation, AI, and Machine Learning (ML) as necessary constituents of DT. Inappropriate selection of capabilities in a DT can result in missed opportunities, strategic misalignments, inflated expectations, and risk of it being rejected as just hype by the practitioners. To alleviate this challenge, this paper proposes the digitalization framework, designed and developed by following a Design Science Research (DSR) methodology over a period of 18 months. The framework can help practitioners select an appropriate level of sophistication in a DT by weighing

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Digital Twin: From Concept to Practice

The seemingly simple step of molding a cholesteric liquid crystal into spherical shape, yielding a Cholesteric Spherical Reflector (CSR), has profound optical consequences that open a range of opportunities for potentially transformative technologies. The chiral Bragg diffraction resulting from the helical self-assembly of cholesterics becomes omnidirectional in CSRs. This turns them into selective retroreflectors that are exceptionally easy to distinguish-regardless of background-by simple and low-cost machine vision, while at the same time they can be made largely imperceptible to human vision. This allows them to be distributed in human-populated environments, laid out in the form of QR-code-like markers that help robots and Augmented Reality (AR) devices to operate reliably, and to identify items in their surroundings. At the scale of individual CSRs, unpredictable features within each marker turn them into Physical Unclonable Functions (PUFs), of great value for secure authentication. Via the machines reading them, CSR markers can thus act as trustworthy yet unobtrusive links between the physical world (buildings, vehicles, packaging,…) and its digital twin computer representation. This opens opportunities to address pressing challenges in logistics and supply chain management, recycling and the circular economy, sustainable construction of the built environment, and many other fields of individual, societal and commercial importance. 

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Unclonable human-invisible machine vision markers leveraging the omnidirectional chiral Bragg diffraction of cholesteric spherical reflectors

Digitalised circular construction supply chain: An integrated BIM-Blockchain solution

This research considers the problem of digital twin engineering in organizational and technical systems. The theoretical and methodological basis is a fundamental scientific work in the field of digital twins engineering and applied models. We use methods of a system approach, statistical analysis, operational research and artificial intelligence. The study proposes a comprehensive technology (methodological approach) for digital twin design in order to accelerate its engineering. This technology consists of design steps, methods and models, and provides systems synthesis of digital twins for a complex system (object or process) operating under uncertainty and that is able to reconfigure in response to internal faults or environment changes and perform preventive maintenance. In the technology structure, we develop a simulation model using situational “what-if” analysis and based on fuzzy logic methods. We apply this technology to develop the digital twin prototype for a device at the creation life cycle stage in order to reduce the consequences of unpredicted and undesirable states. We study possible unforeseen problems and device faults during its further operation. The model identifies a situation as a combination of failure factors of the internal and external environment and provides an appropriate decision about actions with the device. The practical significance of the research is the developed decision support model, which is the basis for control systems to solve problems related to monitoring the current state of technical devices (instruments, equipment) and to support adequate decisions to eliminate their dysfunctions.

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Design Technology and AI-Based Decision Making Model for Digital Twin Engineering

Digital Twin: Where do humans fit in?

Based on an ethnographic action research study for a Digital Twin (DT) deployment on an automated highway maintenance project, this paper reports some of the stumbling blocks that practitioners face while deploying a DT in practice. At the outset, the scope of the case study was broadly defined in terms of digitalization, and software development and deployment, which later pivoted towards the concept of Digital Twin during the collective reflection sessions between the project participants. Through an iterative learning cycle via discussions among the various project stakeholders, the case study led to uncovering the roadblocks in practice faced by the Architecture, Engineering, and Construction (AEC) practitioners. This research finds that the practitioners are facing difficulty in: (1) Creating a shared understanding due to the lack of consensus on the Digital Twin concept, (2) Adapting and investing in Digital Twin due to inability to exhaustively evaluate and select the appropriate capabilities in a Digital Twin, and (3) Allocation of resources for Digital Twin development due to the inability to assess the impact of DT on the organizational conditions and processes.

Digital Twin in Practice: Emergent Insights from an ethnographic-action research study

Production metrics (PM) are important yardsticks for AEC (Architecture, Engineering, and Construction) teams to determine whether their projects are on track. This paper reports on research that looked for empirical evidence of the use of PM from the literature (PML) in practice. Specifically, this research classified PM reported by 279 VDC (Virtual Design and Construction) professionals in Scandinavia and Latin America into 17 PML. About 3 PML (detailed schedule conformance, stakeholder involvement, and meeting efficiency) were found to be reported by more than 40% of the professionals while 7 PML (decision latency, detailed cost conformance, field material delivery, meeting agenda appropriateness, client satisfaction, safety, and visualization) were reported by fewer than 10% of the professionals. The biggest differences in the use of PML were in measuring meeting efficiency (Scandinavia: 44%, and Latin America: 78%), meeting effectiveness (Scandinavia: 40%, and Latin America: 3%), and BIM coordination consistency (Scandinavia: 23%, and Latin America: 40%). This study not only finds empirical evidence for commonly used PML, but also finds PML that seem theoretically useful are not used in practice, suggesting further research in metrics-driven management of AEC projects. 

A Comparative Analysis of Production Metrics across VDC Implementations

Despite the Digital Twin (DT) concept being in the industry for a long time, it remains ambiguous, unable to differentiate itself from information models, general computing, and simulation technologies. Part of this confusion stems from previous studies overlooking the DT’s bidirectional nature, that enables the shift of agency (delegating control) from humans to physical elements, something that was not possible with earlier technologies. Thus, we present DTs in a new light by viewing them as a means of imparting intelligence and agency to entities, emphasizing that DTs are not just expert-centric tools but are active systems that extend the capabilities of the entities being twinned. This new perspective on DTs can help reduce confusion and humanize the concept by starting discussions about how intelligent a DT should be, and its roles and responsibilities, as well as setting a long-term direction for DTs.

Martin Fischer

Papers

Digital Twin: From Concept to Practice

Digital Twin in Practice: Emergent Insights from an ethnographic-action research study

A Comparative Analysis of Production Metrics across VDC Implementations

Digital Twin: Where do humans fit in?

A New Perspective on Digital Twins: Imparting Intelligence and Agency to Entities