Digital Thread Research Articles

Digital thread weaves reality in a closed-loop AI system for zero-defect hybrid production

Digital thread weaves reality in a closed-loop AI system for zero-defect hybrid production

Innovation Ecosystem Dynamics, Value and Learning I: What Can Hamilton Tell Us?

ABSTRACTHeld in Dublin, Ireland, IS2024 invites us to refresh understanding of contributions to systems engineering by Ireland's greatest mathematician— Sir William Rowan Hamilton (1805–1865), professor of astronomy at Trinity College Dublin and royal astronomer of Ireland. His profound contributions to science, technology, engineering, and math (STEM) deserve greater systems community attention. Supporting theory and practice, they intersect foundations and applications streams of INCOSE's future of systems engineering (FuSE) program. Strikingly, key aspects apply to systems of all types, including socio‐technical and information systems. Hamilton abstracted the energy‐like generator of dynamics for all systems, while also generalizing momentum. Applied to the INCOSE innovation ecosystem pattern as dynamics of learning, development, and life cycle management, this suggests an architecture for integration of the digital thread and machine learning in innovation enterprises, along with foundations of systems engineering as a dynamical system.

The use of digital thread for reconstruction of local fiber orientation in a compression molded pin bracket via deep learning

A deep convolutional neural network (DCNN) was used for microstructure reconstruction using artificial intelligence (MR-AI) by predicting local average fiber orientation distributions (FOD) in a 3D prepreg platelet molded composite (PPMC) pin bracket. To train the MR-AI model, surface strain fields from residual stresses simulated in PPMC plates were used as the input to the DCNN. A training dataset included PPMC plates with various degrees of global fiber alignment, based on the information obtained from high-fidelity flow simulation of a pin bracket. The MR-AI model was then deployed to analyze FOD in the 3D pin bracket by conducting thermo-elastic residual stress analysis. Initially, the MR-AI model was established entirely on the synthetic simulation data. Then, a μCT scan of a physically molded pin bracket was used to create a finite element model that provided data for additional validation of the DCNN model. For the μCT scan finite element pin bracket the MR-AI model predicted the distribution of fiber orientation tensor components with MAE of 0.10 indicating a global prediction error of 10 %. For the flow simulated pin bracket, the MR-AI model predicted the distribution of fiber orientation tensor components with a global prediction error of 11 %. The MR-AI model showed the ability to predict regions of varying alignment in the base and flange of the pin bracket. The proposed MR-AI methodology allows for rapid prediction of FOD in geometrically complex parts and offers a promising path to detecting unique fiber orientation states in molded components.

Unravelling the Digital Thread: How Access, Protection, and Adoption Drive Technological Entrepreneurship

This study explores the relationship between digital access, protection, and adoption in supporting technological entrepreneurship within national digital ecosystems. The study utilised PROCESS regression analysis on the Global Entrepreneurship Development Institute (GEDI)’s Digital Development Economy (DPE) Index 2020 dataset to examine selected digital factors’ direct and indirect effects on entrepreneurial activity across 116 countries. While the relationship between digital access, adoption, protection, and technological entrepreneurship has been established in previous research, this study provides global evidence to reinforce this connection. However, digital protection did not significantly moderate the effect of digital access. Notably, digital adoption emerged as a significant mediator, influencing the impacts of both access and protection on entrepreneurial outcomes. This study emphasises the importance of understanding the complex relationships between digital factors in cultivating a thriving entrepreneurial ecosystem, offering valuable insights for policymakers and practitioners seeking to stimulate technological innovation and economic growth.

Information exchange and knowledge discovery for additive manufacturing digital thread: a comprehensive literature review

ABSTRACT With the information integration and intelligent embedding of Additive Manufacturing (AM) in intelligent industrial system applications, the information interoperability and knowledge discovery are becoming an infrangible trend that provide efficient data and knowledge-driven approaches for intelligent AM supports. STEP-NC standards in the specific AM digital thread are recognized as a potential means that can be used to explore multi-source data and knowledge analysis to support AM information exchange and knowledge discovery. As a comprehensive review of the related literatures, AM digital thread has deeply been discussed to analyse the information exchange and knowledge discovery for STEP-NC implementations. Furthermore, the STEP-NC for CNC has been reviewed to extend the possibility of STEP-NC for AM with ontology-based knowledge discovery by loads of literatures. In order to deeply explore the integration of STEP-compliant data transfer and knowledge discovery, ontology-based modelling approach and STEP-NC data transfer can be further discussed by combining the application of OntoSTEP-NC to review the literatures of data and knowledge-driven AM supports.

Design & Development of smart scrap management system for a manufacturing organisation

Scrap management is handled through manual processes in many manufacturing organizationsleading to poor efficiencies. This paper discusses design, development, and deployment of a suitable scrap management system leveraging Industry 4.0 in a lean manner with traceability using ANPR technologyand digital weighbridge setup aided by logistics trucks, digital handshake, and virtual stores in SAP. The complete processes are digitally photographed leaving behind a digital thread for future forensics

THE DIGITAL ENGINEERING FACTORY: CONSIDERATIONS, CURRENT STATUS, AND LESSONS LEARNED

AbstractIn industry, the advancement of digital engineering and the digital thread aims to reduce the impact of knowledge ‘siloes’ by providing a way to integrate data across the entire system lifecycle and across multiple domains. In a typical engineering curriculum, however, courses are still treated as ‘siloes’, and students often do not have the opportunity to experience this industrially relevant approach to engineering. The Digital Engineering Factory (DEF) is a digital engineering environment under development at the University of Arizona to support engineering students. The DEF supports students by providing access to multiple engineering tools and is structured using a ‘hub‐and‐spoke’ approach to consolidate data from these tools. Through this connected architecture, students can transfer data generated in a particular course to tools for use in other courses. Connecting course activities in this way enables students to experience a complete end‐to‐end system lifecycle. At its ‘hub’, the DEF uses Violet to integrate data from multiple sources, create a digital thread, and generate a graph representation of the dataset. This knowledge graph, written in the Ontological Modeling Language (OML), can be viewed in OML Rosetta and is structured according to the University of Arizona Ontology Stack (UAOS). The use of the UAOS and OML Rosetta allows instructors to leverage semantic web technologies to support teaching activities such as grading. In this paper, the authors review the objectives of the DEF, discuss the status of the project, and highlight current limitations and lessons learned with regards to its deployment. These may be useful to inform similar developments in industrial settings.

Innovation Ecosystem Dynamics, Value and Learning I: What Can Hamilton Tell Us?

AbstractHeld in Dublin, Ireland, IS2024 invites us to refresh understanding of contributions to systems engineering by Ireland's greatest mathematician–Sir William Rowan Hamilton (1805 ‐ 1865), Professor of Astronomy at Trinity College Dublin and Royal Astronomer of Ireland. His profound contributions to STEM deserve greater systems community attention. Supporting theory and practice, they intersect Foundations and Applications streams of INCOSE's Future of Systems Engineering (FuSE) program. Strikingly, key aspects apply to systems of all types, including socio‐technical and information systems. Hamilton abstracted the energy‐like generator of dynamics for all systems, while also generalizing momentum. Applied to the INCOSE Innovation Ecosystem Pattern as dynamics of learning, development, and life cycle management, this suggests an architecture for integration of the digital thread and machine learning in innovation enterprises, along with foundations of systems engineering as a dynamical system.

Digital Test and Evaluation

The Department of Defense (DoD) is undergoing a Digital Transformation (DT), which will affect all acquisition processes in some way. As documents are replaced with digital models, the existing processes will be required to facilitate emerging concepts like the Rapid Acquisition Process (RAP) and Test and Evaluation as a Continuum (TEaaC). Traditional Test and Evaluation (T&E) will be augmented by automated digital testing in all program lifecycle phases. Digital testing will rely on many forms of digital models, including Model-Based Systems Engineering (MBSE), linked together via a digital thread and an Authoritative Source of Truth (ASOT). Validation of such digital artifacts will be paramount in assuring system developers and test engineers use accurate and credible models for decisions. This paper proposes a model-based validation technique, details a proof-of-concept, and describes how it may enable future acquisition.

Digital thread-driven cloud-fog-edge collaborative disturbance mitigation mechanism for adaptive production in digital twin discrete manufacturing workshop

The collaborative capacity among various computing layers within a digital twin workshop directly impacts the handling of disturbances in discrete manufacturing processes. However, the intricate nature of the cross-space (physical and virtual space) and cross-layer (cloud, fog, and edge) interactions within a digital twin system poses challenges to construct a comprehensive data model and interoperable data flow, leading to a fragmented state of computing layers. To tackle these challenges, this study presents a digital thread-driven theory and method for cloud-fog-edge collaboration in digital twin discrete manufacturing workshops. Firstly, the five-dimensions production information that cross spaces and layers is concatenated and integrated by constructing digital thread models. Subsequently, a disturbance response model is conducted based on these digital thread models to detect, track, and evaluate disturbances. Furthermore, corresponding cloud-fog-edge collaboration strategies are devised for different types and severity of disturbances, facilitating the dynamic production tasks adjustments. Finally, a case study to discuss the performance of the proposed method regarding the maturity of the digital thread model, disturbance response capability, and production self-adaptive adjustment capability. The results demonstrate that the proposed method effectively mitigates makespan and machine idle time under gradual and abrupt disturbances, and saves 46.22% of computing processing time.

Data management of X bill of material of missile and rocket products based on digital thread

The X bill of material (XBOM) of a missile and rocket product is a comprehensive and basic support document produced by a multi-stakeholder that considers structural composition, data information and interactional processes in different life stages. The XBOM data management of missile and rocket products coordinates the data organization and control in the whole life cycle, eliminates the interactional disconnection and one-way transmission between related parties, business and data in different life stages and provides effective data source support for the full digital model supply. To meet the requirements of organic integration and multi-party collaboration, this paper proposes the XBOM data management method based on digital thread. Firstly, the digital thread framework is analyzed, and the XBOM data management architecture based on the digital thread is proposed and established. Secondly, guided by the hierarchy of "data-interaction-modeling-application", the XBOM data management method for the missile and rocket product are developed, including data organization, data relational analysis, data modeling and data application. Finally, the structural system of a certain model of carrier rocket is studied, and the XBOM data management system based on digital thread is developed and its application is validated.

Seeing a Sea of Ships - Exploring the Ship Design Space in the Digital Domain

We tackle in this work aspects of the ship design space in the digital domain, with an overview of the current status and opportunities to shift from fixed arrangements towards open technologies, proposing a mix of open and proprietary databases. The discussion is focused on the visual domain and digital thread in ship design. Literature examples from the Brazilian case and the visualization of the ocean space are presented (Numerical Offshore Tank - TPN), followed by the Japanese services to design and optimize hull for specific missions (NMRI), and lastly the current open ship design library developed in Norway (Vessel.js, NTNU). We present the argument that seeing a sea of ships, that is, visualizing the behavior of many options is already a reality, accessible from a portable device, without the need a large cluster as in the past, exemplified by web-based cases. Our conclusion is that computer graphics approaches to Ship Design should be considered open and exchangeable. Naval architects should focus on what they do best: creating, analyzing, refining, storing and populating the database of the know-how from the institution (e.g. university, research institute or company).

The digital thread for system lifecycle management with a native graph database in a polyglot architecture

AbstractThe Digital Thread is a system that connects different phases of the product lifecycle and the related data across one or more companies in the supply chain. This work aims to develop a graph data model of the Digital Thread, in the context of the vision of polyglot persistence, that interconnects the different phases of the lifecycle and their corresponding data models, processes, and IT systems. This work proposes a Digital Thread Graph that integrates a Digital Model and a derived Digital Twin, using object and relation attributes for view creation and filtering while minimizing redundancy.

Supporting the digital thread through the principles of complementarity

AbstractTo establish a coherent Digital Thread, encompassing diverse information obtained during the design process, it is imperative to ensure the traceability of information particularly between engineering and manufacturing teams. A challenge lies in maintaining links between data, particularly in the context of configuration management. Through the principles of complementarity, we explore links between the Engineering and the Manufacturing definitions through a major structural element. We forsee the principles of complementarity as a support for Digital Thread throughout the product lifecycle.

Conceptualizing the digital thread for smart manufacturing: a systematic literature review

AbstractBusiness operations and supporting data analysis initiatives are impeded by the silos of data present within departments, systems, and business units. Consequently, the ability of managers and engineers to harness data for operational management and informed decision-making is curtailed. The rapid advancements in technology have revolutionized various aspects of product development, manufacturing, operations, and end-of-life treatment. One such transformative concept, the digital thread, has emerged as an important paradigm. It orchestrates the integration of information and data along the entire product lifecycle, spanning from initial design and engineering through production, maintenance, use, and eventual end of life. While the digital thread has garnered increasing attention within both the research community and industrial enterprises, there remains a notable lack of standardization concerning its utilization and applications. This comprehensive literature review aims to explore the role of the digital thread in manufacturing within the context of the product lifecycle. As a result, this review synthesizes insights into the technologies, roles, and functions of the digital thread throughout the product lifecycle. Furthermore, it proposes a structured framework designed to impart a standardized perspective of the digital thread’s relevance within the manufacturing product lifecycle. Ultimately, this framework is poised to serve as a guiding resource for practitioners and researchers in designing and implementing digital threads.

An activity theory analysis of digital innovation orchestration in Industry 4.0

PurposeThis paper explores the orchestration of digital innovation in Industry 4.0 organisations.Design/methodology/approachThe study applies the activity theory to explorative multiple case studies. Observations of innovation activities in five business cases take place at two large international organisations.FindingsThe results underline five logics of action that drive digital innovation: (1) digital transformation, (2) technology translation, (3) catalyst agents, (4) digital thread and (5) empowerment. Further, the case study organisations highlight the importance of developing a sustainable culture capable of continuously adopting new technologies, processes and infrastructure that will allow the management of digital innovations.Originality/valueThe study empirically shows the motivations and challenges in orchestrating digital innovation in Industry 4.0 organisations.

Optimizing extreme manufacturing framework: a secure and efficient 3D printing integration framework

This study presents a comprehensive framework for extended manufacturing with integrated 3D printing technologies, exemplifying a paradigm shift in the manufacturing landscape. The Digital Thread Integration establishes a dynamic foundation, enabling real-time collaboration and data flow throughout the product lifecycle. Leveraging advanced AI-driven optimization, Digital Design Platforms streamline designs, processing 1,000 iterations per hour, and recommending materials based on component requirements. On-Demand Manufacturing Hubs strategically placed globally achieve substantial reductions in lead times (48 h) and material waste (15%). The Cybersecurity Infrastructure ensures the sanctity of the digital environment, employing secure communication protocols and an Intrusion Detection System (IDS) responding to threats in milliseconds. The Data Analytics Hub contributes to continual improvement by analysing 100 GB of 3D printing data daily, generating 50 actionable insights weekly. User Interface and Accessibility initiatives empower the workforce through intuitive training modules and responsive help desks. In conclusion, this framework exemplifies secure, efficient, and data-driven extended manufacturing, positioning the industry at the forefront of technological advancement.

WITHDRAWN: Digital twin-driven machining process for multi-process irregular-shaped parts manufacturing

With the advancement of high-end manufacturing industries, certain critical parts exhibit peculiar shapes and characteristics of multi-process manufacturing, which intensify milling difficulties and give rise to error propagation effects during the machining process. This necessitates machining systems to be adaptive to different working conditions and capable of real-time error analysis and optimization. Digital twin technology can create virtual replicas of physical entities to observe, analyze, and optimize the machining process. Therefore, this paper proposes a framework for digital twin-driven machining of multi-process irregular-shaped parts, consisting of preparation, processing, and optimization stages. In the preparation stage, a mapping relationship between the workpiece and machine tool motion coordinates is established to create a twin simulation environment consistent with actual operational parameters. In the processing stage, the digital thread dynamically updates the digital twin workpiece and machine tool status in real-time, analyzing the machining errors for each process to assess the finished quality. In the optimization stage, a cloud-based machining knowledge graph is constructed to enhance the precision of machining optimization decisions under different error sources and causes in the digital twin system. Finally, a case study of a typical multi-process irregular-shaped part machining task validates the reliability and superiority of the digital twin-driven method. The case study demonstrates that in a total of 260 machining processes, the digital twin-driven method improves machining accuracy by 40%, saves 34.9% of machining time, and alleviates 70% of machining downtime compared to existing machining methods.

Unleashing the potential of digital twins: a new era with aeronautics 4.0

Abstract* Introduction The aerospace value chain consists of several processes, and digitizing it first requires an assessment of these processes and their ability to be transferred to the fully integrated digital thread perspective of smart factories. A digital thread refers to the continuous flow of data and information related to a product throughout its life cycle, integrating and connecting all aspects of a product’s journey. Within this framework, digital twin technology, an essential element of Industry 4.0, comprises the implementation of a virtual presentation of a physical object, system, or process. It brings together the digital replica not only of the physical attributes but also of the behavioral performance of the physical twin. Methods To achieve a digital thread perspective for aeronautics, a research agenda is proposed, including all breakpoints in the current value chain through a PESTLE Analysis, which defines the value-added areas targeted by this transition to digital technology. An aeronautics 4.0 model Digital Thread Twin Smart Aeronautics D2TSAero is proposed, which provides a new perspective in the aeronautics field by integrating its main ecosystems into an interconnected model made possible by the integration of digital twin agent instances. Proof of Concept A use case that deals with the dependability management of an aircraft fuel distribution system is presented. Based on these results, we can see that the proposed twin model can help in reducing real system parts down time, and it can also improve the management of maintenance across the system life cycle by offering a single source of trust for all stakeholders involved in the digital thread cycle of the real twin. Conclusion A forward-looking perspective on the future of aeronautics with this integrated approach is presented, summarizing all the discussed points and the importance of digital twins in supporting the digitalization of the field.

AI Revolution: Safeguarding Tomorrow’s Frontiers - Transforming Cybersecurity Across Industries (A Short Approach)

The article explores the revolutionary effects of artificial Intelligence (AI) on cybersecurity in various industries, emphasizing how important it is to protect sensitive data and strengthen vital infrastructure. Using AI-driven cybersecurity solutions signifies a paradigm change away from reactive, defensive tactics and toward proactive, adaptive, and predictive defense systems. The article illustrates how artificial Intelligence (AI) improves threat detection, guards against fraudulent activity, secure patient data, and strengthens the digital thread in manufacturing and supply chain operations. It focuses on essential industries such as nuclear energy, finance, healthcare, and manufacturing. The convergence of AI and cybersecurity becomes a strategic necessity as sectors negotiate the challenges of a globalized world, providing light on the way to a more inventive, safe, and resilient future.