Quarter 12 update – November 2016

During this quarter our research efforts have been focused on four areas:

  1. Eliciting user needs for a Formula Student team project health monitoring dashboard and consolidation / grouping of analytical techniques (proxies) to meet FS user needs.
  2. Preparing industry-facing summaries of the proxies that we have developed.
  3. Creating a real-time skills and competency mapping dashboard with one of our industrial partners.
  4. The preparation of a joint research proposal with another of our industrial partners to exploit the findings and techniques developed in this project.

Formula Student Dashboards

On the first point, in order to understand how the Formula Student team could benefit from our project’s techniques, a series of user-interviews were conducted. Academic staff supervisors and student project managers from Universities of Bath, Bristol and UWE took part in semi-structured interviews. Interviews were coded using thematic analysis, which identified 85 unique user requirements. Further axial coding and affinity diagramming showed user insights focused on four core areas of activity within the project: 1) planning and monitoring project progress, 2) CAD based design process, 3) communication and team dynamics, and 4) team competencies.

For each requirement, we discussed and agreed which were outside the scope of project management support and, in line with wider project aims, were not automatable. For the remaining 36 unique in-scope requirements, researchers tagged each with one or more of the nine developed proxies that could be applied to support that user-requirement. A hierarchical cluster analysis method was used to group user insights that could be addressed by similar sets of analytics/proxies. The outcome of this analysis was the generation 10 design scenarios. These design scenarios provide narrative descriptions which envision how users may interact with a dashboard. They both enable researchers to anchor envisioned proxy applications to the users’ requirements, work practices and context; and also provided a clear and simple means to support communication with users in the evaluation and the iterative design process of creating dashboards tailored to support Formula Student:



Accelerating our Impact with Airbus

A joint EPSRC-funded Impact Acceleration Account (IAA) project titled “Big-data: improving aircraft performance” has been funded to exploit the findings and methods we’ve developed in the Airbus In-Service department.

This six-month long project led by Dr Lei Shi and Prof. Linda Newnes aims to embed the approaches created within the project, including big-data analytics, trend analysis and autonomic computing, to interrogate and categorise aircraft wing In-Service projects.  The research at the University of Bath has demonstrated that it is possible to automatically predict the complexity, duration and cost of such repair cases. This has been achieved through interrogating 10,000+ historical projects to create and validate the proposed approaches. Initial tests have been completed to ascertain whether the approaches can be used on the ‘live’ data from the Airbus In-Service workflow system.

Our overall aims are to develop the processes through on-site development and testing, to make the approaches self-sustaining, and to assist the in-service teams with their decision-making.

Do you face similar challenges?  Let us know in the comments below…

Engaging with Formula Student in user-centred design


Recently we’ve been continuing our work with Formula Student (FS) as we move forward towards developing an FS dashboard. The LOCM project has been working with project data (e.g. CAD files, reports, documents, communication) generated by FS teams in the development and refinement of data analytic approaches.

Over the past few weeks, we have been conducting interviews with student project managers and academic supervisors involved in FS across three universities to gain insights into key areas of project activity, goals and issues that could be supported by project dashboards. This work has enabled us to develop user-driven design scenarios and requirements, and importantly, will help guide how we apply the data analytics that have been developed in the creation of visualisations and dashboards that are both usable and add value to FS project activity.