Due to heterogeneity in engineering projects and the contexts in which they occur, it is challenging to develop 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, aside from how to assess. To address this issue this paper presents a new approach to project monitoring based on Integrated Vehicle Health Management (IVHM), a widely used monitoring method for machine maintenance. By focusing on wide capture of low-level data, in this case digital files 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 influence performance. Feasibility of the IVHM approach in engineering management is shown through three data examples, in which higher level project understanding is inferred directly from low level data.
|Publication status||Published - 27 Jul 2015|