@inproceedings{scholars2281,
            year = {2011},
           pages = {957--965},
       publisher = {British Institute of Non-Destructive Testing},
         journal = {8th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies 2011, CM 2011/MFPT 2011},
            note = {cited By 0; Conference of 8th International Conference on Condition Monitoring and Machinery Failure Prevention Technologies 2011, CM 2011/MFPT 2011 ; Conference Date: 20 June 2011 Through 22 June 2011; Conference Code:106866},
          volume = {2},
         address = {Cardiff},
           title = {The EUCAMS gear partnership-a model of industry/academic collaboration},
          author = {Starr, A. and Khan, M. and Allen, B. and Marshall, M. and Phang, A. and Badi, N. and Chen, Y. K. and Edwards, R. and Sinha, J. and Rzeszucinski, P. and Jones, R. and Mao, K. and Shepherd, D. and Curran, A.},
            isbn = {9781618390141},
             url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-84905756068&partnerID=40&md5=d2409eeccc55fdb50ed0e57517a1e14d},
        keywords = {Condition monitoring; Human resource management; Machinery; Project management; Signal processing, Finite element modelling; Integrated project; Maintenance systems; Mechanical failures, Mergers and acquisitions},
        abstract = {Challenges in maintenance systems can pose multi-faceted problems, which are difficult to resolve alone. Over a four year period, a partnership evolved a vision for tackling the understanding of fundamentally difficult mechanical failures and their detection, with potential for practical exploitation of the solutions. The partnership assembled a team of researchers and far-sighted project management, to undertake a study of gearbox failures, including finite element modelling, gear testing, and signal analysis. The partnership trained a series of doctoral and postdoctoral staff in running an integrated project, coping with changes in staffing and locations. The final stages of the work will validate the models and signal processing.}
}