Automatic generation of design structure matrices through the evolution of product models

Dealing with component interactions and dependencies remains a core and fundamental aspect of engineering, where conflicts and constraints are solved on an almost daily basis. Failure to consider these interactions and dependencies can lead to costly overruns, failure to meet requirements, and lengthy redesigns. Thus, the management and monitoring of these dependencies remains a crucial activity in engineering projects and is becoming ever more challenging with the increase in the number of components, component interactions, and component dependencies, in both a structural and a functional sense. For these reasons, tools and methods to support the identification and monitoring of component interactions and dependencies continues to be an active area of research. In particular, design structure matrices (DSMs) have been extensively applied to identify and visualize product and organizational architectures across a number of engineering disciplines. However, the process of generating these DSMs has primarily used surveys, structured interviews, and/or meetings with engineers. As a consequence, there is a high cost associated with engineers' time alongside the requirement to continually update the DSM structure as a product develops. It follows that the proposition of this paper is to investigate whether an automated and continuously evolving DSM can be generated by monitoring the changes in the digital models that represent the product. This includes models that are generated from computer-aided design, finite element analysis, and computational fluid dynamics systems. The paper shows that a DSM generated from the changes in the product models corroborates with the product architecture as defined by the engineers and results from previous DSM studies. In addition, further levels of product architecture dependency were also identified. A particular affordance of automatically generating DSMs is the ability to continually generate DSMs throughout the project. This paper demonstrates the opportunity for project managers to monitor emerging product dependencies alongside changes in modes of working between the engineers. The application of this technique could be used to support existing product life cycle change management solutions, cross-company product development, and small to medium enterprises who do not have a product life cycle management solution.<br/

Automatic generation of design structure matrices through the evolution of product models

AbstractDealing with component interactions and dependencies remains a core and fundamental aspect of engineering, where conflicts and constraints are solved on an almost daily basis. Failure to consider these interactions and dependencies can lead to costly overruns, failure to meet requirements, and lengthy redesigns. Thus, the management and monitoring of these dependencies remains a crucial activity in engineering projects and is becoming ever more challenging with the increase in the number of components, component interactions, and component dependencies, in both a structural and a functional sense. For these reasons, tools and methods to support the identification and monitoring of component interactions and dependencies continues to be an active area of research. In particular, design structure matrices (DSMs) have been extensively applied to identify and visualize product and organizational architectures across a number of engineering disciplines. However, the process of generating these DSMs has primarily used surveys, structured interviews, and/or meetings with engineers. As a consequence, there is a high cost associated with engineers' time alongside the requirement to continually update the DSM structure as a product develops. It follows that the proposition of this paper is to investigate whether an automated and continuously evolving DSM can be generated by monitoring the changes in the digital models that represent the product. This includes models that are generated from computer-aided design, finite element analysis, and computational fluid dynamics systems. The paper shows that a DSM generated from the changes in the product models corroborates with the product architecture as defined by the engineers and results from previous DSM studies. In addition, further levels of product architecture dependency were also identified. A particular affordance of automatically generating DSMs is the ability to continually generate DSMs throughout the project. This paper demonstrates the opportunity for project managers to monitor emerging product dependencies alongside changes in modes of working between the engineers. The application of this technique could be used to support existing product life cycle change management solutions, cross-company product development, and small to medium enterprises who do not have a product life cycle management solution.</jats:p

Identifying the influences on performance of engineering design and development projects

Performance of engineering design and development projects depends on myriad factors, creating challenges in implementation and management. These are compounded by potential for high variation across contexts. This work investigates influencers upon performance and contextual variation through relationship between real industry issues and factors that influence project performance. Through survey, interview, and network analysis, issue-causing groups of features in each specific case are identified and compared. The results find a majority of issues arising from person-centric sources. They also identify both discrete groups of issues with narrow source and influence, and with broad ties across the project context; forms which may stem from conditions of the scenario. Finally, they show similarity in the influences on performance across contexts with a caveat that, while the influential area remains, the structure to be taken within may vary. General analysis clarifies performance in engineering and highlights those areas in which support-system development is of most use, and specific analysis gives areas in which industry managers should focus for best benefit to the project

Investigating the Evolving Knowledge Structures in New Technology Development

Part 8: Knowledge Management and Information SharingInternational audienceThe development of new technology has been identified as one of the key enablers to support business and economic growth in developed countries. For example, the United Kingdom (UK) has invested £968 Million into the creation of Catapult centres to provide ‘pull through’ of low Technology Readiness Level (TRL) research and science. While these Catapults have been instrumental in developing new technologies, the uptake of new technology within industry remains a considerable challenge.One of the reasons for this is that of skills and competencies, and in particular, defining the new skills and competencies necessary to effectively apply and operate the new technology within the context of the business. Addressing this issue is non-trivial because the skills and competencies cannot be defined a priori and will evolve with the maturity of the technology. Therefore, there is a need to create methods that enable the elicitation and definition of skills and competencies that co-evolve with new technology development, and what are referred to herein as knowledge structures.To meet this challenge, this paper reports the results from a dynamic co-word network analysis of the technical documentation from New Technology Development (NTD) programmes at the National Composites Centre (NCC). Through this analysis, emerging knowledge structures can be identified and monitored, and be used to inform industry on the skills & competencies required for a technology

The emergent structures in digital engineering work:what can we learn from dynamic DSMs of near-identical systems design projects?

Design structure matrices (DSMs) are widely known for their ability to support engineers in the management of dependencies across product and organisational architectures. Recent work in the field has exploited product lifecycle management systems to generate DSMs via the co-occurrence of edits to engineering files. These are referred to as dynamic DSMs and results have demonstrated both the efficacy and accuracy of dynamic DSMs in representing engineering work and emergent product architectures. The wide-ranging applicability of the theoretical model and associated analytical process to generate dynamic DSMs enables investigations into the evolving structures within digital engineering work. This paper uses this new capability and presents the results of the world's first comparison of dynamic DSMs from a set of near-identical systems design projects. Through comparison of the dynamic DSMs' end-of-project state, change propagation characteristics and evolutionary behaviour, 10 emergent structures are elicited. These emergent structures are considered in the context of team performance and design intent in order to explain and code the identified structures. The significance of these structures for the management of future systems design projects in terms of productivity and efficacy is also described.</p

Managing complex engineering projects:What can we learn from the evolving digital footprint?

The challenges of managing large complex engineering projects, such as those involving the design of infrastructure, aerospace and industrial systems; are widely acknowledged. While there exists a mature set of project management tools and methods, many of today's projects overrun in terms of both time and cost. Existing literature attributes these overruns to factors such as: unforeseen dependencies, a lack of understanding, late changes, poor communication, limited resource availability (inc. personnel), incomplete data and aspects of culture and planning. Fundamental to overcoming these factors belies the challenge of how management information relating to them can be provided, and done so in a cost eff; ective manner. Motivated by this challenge, recent research has demonstrated how management information can be automatically generated from the evolving digital footprint of an engineering project, which encompasses a broad range of data types and sources. In contrast to existing work that reports the generation, verification and application of methods for generating management information, this paper reviews all the reported methods to appraise the scope of management information that can be automatically generated from the digital footprint. In so doing, the paper presents a reference model for the generation of managerial information from the digital footprint, an appraisal of 27 methods, and a critical reflection of the scope and generalisability of data-driven project management methods. Key findings from the appraisal include the role of email in providing insights into potential issues, the role of computer models in automatically eliciting process and product dependencies, and the role of project documentation in assessing project norms. The critical reflection also raises issues such as privacy, highlights the enabling technologies, and presents opportunities for new Business Intelligence tools that are based on real-time monitoring and analysis of digital footprints.</p

Analysing Systems Interdependencies Using a Digital Twin

This work provides a first step towards next-generation systems engineering by demonstrating the feasibility of using a digital twin to generate new insight into systems relationships and interdependencies. This step required substantial interdisciplinary work and industry collaboration in order to examine the potential to combine a set of relevant analytical methods (e.g. BIM query, network analyses and multi-modelling). We assembled an experienced team (Imperial College London, University of Sheffield, Newcastle University), and worked closely with and used empirical data from a major project (Thames Tideway Tunnel). This first step delivers fundamental theoretical understanding that will support the use of the digital twin for systems analyses, and a practical contribution to the identification, prioritisation and management of interdependencies. The long-term ambition is to build the tools that decision makers need in order to understand infrastructure system interdependencies within and across project boundaries