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As the engineering design process becomes increasingly complex, multidisciplinary teams need to work together, integrating diverse expertise across a range of disciplinary models. Where changes arise, these design teams often find it difficult to handle these design changes due to the complexity and interdependencies inherent in engineering systems. This paper aims to develop an innovative approach to clarifying system interdependencies and predicting the design change propagation at the asset level in complex engineering systems based on the digital-twin-driven design structure matrix (DSM).

The paper first defines the digital-twin-driven DSM in terms of elements and interdependencies, where the authors have defined three types of interdependency, namely, geospatial, physical and logical, at the asset level. The digital twin model was then used to generate the large-scale DSMs of complex engineering systems. The cluster analysis was further conducted based on the improved Idicula–Gutierrez–Thebeau algorithm (IGTA-Plus) to decompose such DSMs into modules for the convenience and efficiency of predicting design change propagation. Finally, a design change propagation prediction method based on the digital-twin-driven DSM has been developed by integrating the change prediction method (CPM), a load-capacity model and fuzzy linguistics. A section of an infrastructure mega-project in London was selected as a case study to illustrate and validate the developed approach.

The digital-twin-driven DSM has been formally defined by the spatial algebra and Industry Foundation Classes (IFC) schema. Based on the definitions, an innovative approach has been further developed to (1) automatically generate a digital-twin-driven DSM through the use of IFC files, (2) to decompose these large-scale DSMs into modules through the use of IGTA-Plus and (3) predict the design change propagation by integrating a digital-twin-driven DSM, CPM, a load-capacity model and fuzzy linguistics. From the case study, the results showed that the developed approach can help designers to predict and manage design changes quantitatively and conveniently.

This research contributes to a new perspective of the DSM and digital twin for design change management and can be beneficial to assist designers in making reasonable decisions when changing the designs of complex engineering systems.

This paper seeks to explore new complex venture approaches needed because the classical twentieth century system engineering model does not accommodate the complexities of twenty‐first century ventures, especially those with significant knowledge management components.

A complexity literature review was performed to identify the attributes of complex ventures. Then the fundamental differences in defining, developing, and implementing complicated traditional systems and complex ventures were explored. The resultant complex venture model builds on the insights derived from chaos and complexity theories; observations of several acquisition successes and failures; and doctoral research on agile enterprise decision support.

Successful traditional systems engineering complicated systems models' built‐in assumptions do not scale to the needed twenty‐first century complex solutions. It is necessary to develop a complex venture model that guides the engineering solutions that: describe complex ventures as flows of intelligence, energy and matter provide value in a dynamic co‐evolving context; provide leadership, not control, with clear and consistent venture‐wide vision that guides empowered individual agent decision making; institute tiered situationally‐aware decision making in both time and place; address factors (material and non‐material) contributing to solution success; provide for rapidly changing context and the co‐evolutionary ventures, including unexpected users, uses, and implementations.

A complex venture conceptual model informs the architecting and systems engineering acquisition practices for this new solution category.

Strategic trends towards service operations have been widely reported in the recent literature, but organisational capabilities to support such service-centred strategies are less well understood. The purpose of this paper is to identify key organisational issues in managing complex engineering service operations throughout the lifecycle.

Using instruments developed from the product lifecycle management technologies and the network configuration concept, key organisational issues for engineering service operations were identified through case studies focusing on complex engineering products and services systems across a variety of industrial sectors.

The case studies demonstrated different organisational features and strategic priorities of engineering service operations along the whole lifecycle. A generic trend has been observed for engineering systems to move from being design, development and manufacturing focused to embracing support and end-of-life recycling matters.

This paper provides an overall framework for integrating key organisational issues in engineering service operations. It contributes to the service literature by highlighting the need of developing appropriate organisational capabilities to support service-centred strategies with engineering cases. It also provides guidance for companies to manage their engineering network operations throughout the whole lifecycle of complex products and services systems.

For decades now, industrial manufacturers’ complex product development (CPD) activities have seen various improvement approaches as well as product development (PD) support processes all in the quest to achieve shorter PD lead-times and higher return on investments. CPD process improvements, in terms of complex engineering design and delivery, still lack a lot more variance to be addressed on the “better, faster and cheaper” paradigm for efficient communication and information exchange flow processes. The paper aims to discuss these issues.

This paper presents employing social network theory analysis and statistical Pearson (r) correlation analysis in a triangulation approach to a proposed optimum conceptual information technology systems’ architecture and a “best practice” information flow process toward enhancing an industrial sustainable competitive advantage. Closed-end questionnaires were used to collect data for the scale or level of communication network from a sample size of eight Ship Power supply chain network complex engineering design and delivery systems-design teams with at least five members from each team.

Two extremely interesting findings and observations were identified from the analysis carried out (isolates and close-harmonic analysis) as well as the findings from the hypotheses’ testing. These essential analyses of the engineering systems-design teams were conducted by using the triangulation or mixed-method described in the abstract methodology identified above.

Effective and efficient real-time communication is seen as the vehicle for effective organization management. Although there may be some studies on effective technical communication in organizational and enterprise supply chain management settings, this research identifies a new robust and extensive analysis and feasible solutions to most of the communication bottlenecks and inefficient socio-industrial information flow processes, which need enhancement for industrial competitive advantage. Furthermore, the contribution of this paper further enhances the level 4 implementation aspect of the supply chain operation reference model in a replicable industry-specific perspective.

The Times for 29th May 1867 carried on its correspondence pages letters from Earl Granville and Lord Taunton warning of the decline of British manufacturing industry and the need to establish industrial (technical) education along the lines of the Grandes Ecoles already established in France and on the Continent generally. Lord Taunton also called for the Government of the day to hold an official inquiry into industrial education on the Continent and wrote that it “should tell the people of England authoritatively what are the means by which the great States are attaining an intellectual preeminence among the industrial classes and how they are making this bear on the rapid progress of their national industries.”

This paper aims to discuss how the theory of complex thinking can be considered an interesting element in engineering education, especially in the context in which challenges toward sustainable development are multidisciplinary.

This viewpoint synthesizes the main reflections and discussions generated during a process of debate, research and creation of a proposal for an undergraduate engineering course at a higher education institution in Brazil. The literature on engineering education, sustainability and complexity was considered in an integrated way. Debates were conducted considering the authors’ knowledge and experience as professors of engineering courses and researchers in the field of sustainability. A qualitative and reflexive approach was used to organize the main discussions.

The prevailing classical engineering paradigm trains professionals to think from a Cartesian, reductionist perspective, appropriate for solving well-structured problems with known solution paths and convergent answers. However, addressing sustainability challenges requires a different kind of thinking capable of dealing with situations characterized by uncertainty, emergence and incompleteness of knowledge. Complexity thinking can be useful for this purpose as it provides a broad system approach to deal with ill-defined, ill-structured and unpredictable problems. This study can be understood as a call to researchers and professionals to consider the value and importance of complexity thinking to advance engineering education for sustainability.

The need to overcome the limits of the classical engineering paradigm is emphasized in the context of sustainability. Complex thinking is considered as a path toward a paradigm shift in engineering education for sustainability. It can contribute to the training of professionals to face pressing challenges now and in the future. This viewpoint provides some insights to enhance debates on education engineering.

Digital twin (DT) is an emerging technology that enables sophisticated interaction between physical objects and their virtual replicas. Although DT has recently gained significant attraction in both industry and academia, there is no systematic understanding of DT from its development history to its different concepts and applications in disparate disciplines. The majority of DT literature focuses on the conceptual development of DT frameworks for a specific implementation area. Hence, this paper provides a state-of-the-art review of DT history, different definitions and models, and six types of key enabling technologies. The review also provides a comprehensive survey of DT applications from two perspectives: (1) applications in four product-lifecycle phases, i.e. product design, manufacturing, operation and maintenance, and recycling and (2) applications in four categorized engineering fields, including aerospace engineering, tunneling and underground engineering, wind engineering and Internet of things (IoT) applications. DT frameworks, characteristic components, key technologies and specific applications are extracted for each DT category in this paper. A comprehensive survey of the DT references reveals the following findings: (1) The majority of existing DT models only involve one-way data transfer from physical entities to virtual models and (2) There is a lack of consideration of the environmental coupling, which results in the inaccurate representation of the virtual components in existing DT models. Thus, this paper highlights the role of environmental factor in DT enabling technologies and in categorized engineering applications. In addition, the review discusses the key challenges and provides future work for constructing DTs of complex engineering systems.

This paper attempts to apply complex theory in futures studies and addresses prediction challenges when the system is complex. The purpose of the research is to design a framework to engineer the futures in complex systems where components are divers and inter-related. Relations cannot be interpreted by cause and effect concept.

First, the authors shaped a conceptual framework based on engineering, complex theory and uncertainty. To extract tacit knowledge of experts, an online questionnaire was developed. To validate the proposed framework, a workshop method was adapted with NetLogo simulation.

Opinion of participants in the workshop which is collected through quantitative questionnaire shows that the framework helps us in understanding and shaping scenarios. Harnessing the complexity in developing the futures was the main objective of this paper with the proposed framework which has been realized based on the experience gained from the workshop.

Iterative processes are very important to harness the complexity in systems with uncertainty. The novelty of the research is a combination of engineering achievements in terms of computation, simulation and applying tools with futures studies methods.

In the evolution process of building construction accidents, there are key nodes of risk change. This paper aims to quickly identify the key nodes and quantitatively assess the node risk. Furthermore, it is essential to propose risk accumulation assessment method of building construction.

Authors analyzed 419 accidents investigation reports on building construction. In total, 39 risk factors were identified by accidents analysis. These risk factors were combined with 245 risk evolution chains. Based on those, Gephi software was used to draw the risk evolution network model for building construction. Topological parameters were applied to interpret the risk evolution network characteristic.

Combining complex network with risk matrix, the standard of quantitative classification of node risk level is formulated. After quantitative analysis of node risk, 7 items of medium-risk node, 3 items of high-risk node and 2 items of higher-risk nodes are determined. The application results show that the system risk of the project is 44.67%, which is the high risk level. It can reflect the actual safety conditions of the project in a more comprehensive way.

This paper determined the level of node risk only using the node degree and risk matrix. In future research, more node topological parameters that could be applied to node risk, such as clustering coefficients, mesoscopic numbers, centrality, PageRank, etc.

This article can quantitatively assess the risk accumulation of building construction. It would help safety managers could clarify the system risk status. Moreover, it also contributes to reveal the correspondence between risk accumulation and accident evolution.

This study comprehensively considers the likelihood, consequences and correlation to assess node risk. Based on this, single-node risk and system risk assessment methods of building construction systems were proposed. It provided a promising method and idea for the risk accumulation assessment method of building construction. Moreover, evolution process of node risk is explained from the perspective of risk accumulation.

In the era of industry 4.0, managing the design is a challenging mission. Within a dynamic environment, several disciplines have adopted the complex adaptive system (CAS) perspective. Therefore, this paper aims to explore how we may deepen our understanding of the design process as a CAS. In this respect, the key complexity drivers of the design process are discussed and an organizational decomposition for the simulation of the design process as CAS is conducted.

The proposed methodology comprises three steps. First, the complexity drivers of the design process are presented and are matched with those of CAS. Second, an analysis of over 111 selected papers is presented to choose the appropriate model for the design process from the CAS theory. Third, the paper provides methodological guidelines to develop an organizational decision support system that supports the complexity of the design process.

An analysis of the key drivers of design process complexity shows the need to adopt the CAS theory. In addition to that, a comparative analysis between all the organizational methodologies developed in the literature leads the authors to conclude that agent-oriented Software Process for engineering complex System is the appropriate methodology for simulating the design process. In this respect, a system requirements phase of the decision support system is conducted.

The originality of this paper lies in the fact of analysing the complexity of the design process as a CAS. In doing so, all the richness of the CAS theory can be used to meet the challenges of those already existing in the theory of the design.