2015 International Conference on Engineering Design (ICED ’15) Milan, Italy

The 20th International Conference on Engineering Design took place 27-30th July 2015 in Milan. The LOCM team presented five papers across a range of topics:

Gopsill J., Jones S., Snider C., Shi L., Hicks B. The Evolution of Terminology within a Large Distributed Engineering Project.

Abstract: Communication features in many engineering activities within an engineering project. It is the main form by which information & knowledge is shared, and facilitates the generation of a shared understanding between engineers. While there exists extant literature relating to the role of communication, much of the research has been through qualitative studies using techniques such as surveys, interviews and observation. Given the prevalence of computer-mediated communication and the development of techniques to analyse such datasets, there is now the opportunity to provide quantitative metrics that can characterise engineering communication. Therefore, this paper examines this opportunity through the co-word analysis of the subject line terms of an engineering project e-mail corpus comprising of 10,628 e-mails, featuring 1,045 individuals and spanning over a 4 year period. More specifically, the analysis has focused on the evolution, use/re-use and centrality of terms across the various project stages. The results provide interesting insights in the evolution of engineering terminology, which leads onto a discussion on how these metrics may provide indicators of project ‘normality’.

Jones SL., Payne, SJ., Hicks BJ., Gopsill JA. and Snider, C. Subject Lines as Sensors: Co-word Analysis of Email to Support the Management of Collaborative Engineering Work.

Abstract: This paper presents a topic-based analysis of email subject line data from a large-scale engineering project and explores its utility for supporting the management of collaborative work. The main contributions of the paper are a novel interpretation of the co-word network analysis method for application within an engineering project management context, and the appraisal of the method for finding patterns within subject line data. Our findings suggest that the approach has the potential to contribute to monitoring work complexity, tracking progress, recognizing synergy and divergence, detecting scope creep, and supporting knowledge capture.

Shi L., Newnes L. and Culley S.J. Identifying and Visualising KPIs for Collaborative Engineering Projects: a Knowledge Based Approach.

Abstract: Nowadays manufacturing involves high volume of complex operational processes, distributed resources and international/intersectional collaborations, which cause the evaluation of performance for related engineering projects to become a challenge. The performance of project is a key factor that determines the quality of output, and its temporal changes could reflect the status of project execution at current time, as well as indicate the potential issues for the near future. As a result, monitoring the change of performance is an essential approach to ensure the project execution is on track. It could raise awareness of project participants upon any issue occurs, and enable them to make appropriate decisions on a real-time basis. To facilitate the evaluation of project performance in collaborative environments, this research aims to propose an automatic approach to extracting key performance indicators (KPIs) from project related data, and also to demonstrate how the domain knowledge can facilitate the process of KPIs identification and visualisation.

Snider, C., McAlpine, H., Hicks, B., Gopsill, J. A., Jones, S. It’s Not Personal: Can Logbooks Provide Insights into Engineering Projects?

Abstract: Modern engineering projects are often large, complex, high-value, high-risk, and distributed. As a result, it is both vital to monitor and understand what is happening within each as it progresses, and highly challenging to do so. Without detailed and comprehensive understanding, management becomes difficult and falls back upon generic high-level principles that are not always appropriate for each project context. To approach this issue, this paper studies the written logbooks of three engineers, and explores how the marks within can be analysed to generate project-level understanding, particularly that which can inform engineering project management. This occurs through the study of three engineering logbooks using two detailed coding schemas, one classifying content and the other activity, creativity and novelty. By this analysis, this paper aims to understand and assess efficacy of studying logbooks given their time-consuming and difficult-to-code nature. From the results, feasibility is demonstrated of developing detailed understanding of typical project progress, and the identification of specific events within a project upon which a manager may act. The efficacy of the study of logbooks for this purpose is then assessed.

Snider, C., Hicks, B., Gopsill, J. A., Jones, S. Understanding Engineering Projects: An Integrated Vehicle Health Management Approach to Engineering Project Monitoring.

Abstract: Due to heterogeneity in engineering projects and the contexts in which they occur, it is challenging to develop and apply generic methods for monitoring and management. Particularly in large projects, high complexity, scale, and distribution creates difficulty in identifying what performance metrics should even be applied to each, aside from assessment method. To address this issue this paper presents a new approach to project monitoring based on Integrated Vehicle Health Management (IVHM), a widely utilised monitoring method for machine maintenance. By focusing on wide capture of low-level data, in this case Digital Objects produced during everyday work, an IVHM approach uses many analysis techniques simultaneously, automatically creating a high-level description of the state of the project, which a manager can use for assessment and intervention. To allow IVHM to be applied to engineering projects this paper presents 70 features captured from interview, each present in all engineering projects, whose state influences performance. Feasibility of the IVHM approach in engineering project management is then shown through three real-data examples, in which higher level project understanding is inferred directly from low level data.

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