Abstract
Engineering projects are often highly complex, unique and safety critical, which can lead to the complex engineering processes requiring various resources and bring challenges on decision making. To ensure the success of the project products, the related project has to comply with stringent regulations and company processes before the work can commence. In addition, the increasing in-service lifespan of products has led to many projects, such as design or maintenance projects, being run concurrently in a highly time-constrained and high-pressured environment, so that the generation of detailed activity plans becomes a challenge for most engineering companies. These plans are typically achieved through the ability of the project managers to use their knowledge, experience and constant contact with the engineers to provide insights into the sequence of engineering activity. However, the viability of the current method to manually generate and evaluate the activity plan is becoming an issue, e.g. there are increasing numbers of concurrent projects with increasingly distributed resources and higher level of complexity.
As regulatory and/or company process demands, the project related data is archived within this context and thus, provides a wealth of potentially useful information that could be utilised in the management of current projects. Therefore, this research investigates the potential value provided by the automatic construction of past project activity sequences, and proposes analytical methods to represent the normality of the projects based on the extracted patterns from their sequences. The evaluation applies industrial data, and shows that the results generated by the proposed approach can accurately reflect the process similarity and normality of the projects.
As regulatory and/or company process demands, the project related data is archived within this context and thus, provides a wealth of potentially useful information that could be utilised in the management of current projects. Therefore, this research investigates the potential value provided by the automatic construction of past project activity sequences, and proposes analytical methods to represent the normality of the projects based on the extracted patterns from their sequences. The evaluation applies industrial data, and shows that the results generated by the proposed approach can accurately reflect the process similarity and normality of the projects.
Original language | English |
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Publication status | Published - 2014 |
Event | ICTAI 2014 : 26th IEEE International Conference on Tools with Artificial Intelligence - Limassol, Cyprus Duration: 10 Nov 2014 → 12 Nov 2014 |
Conference
Conference | ICTAI 2014 : 26th IEEE International Conference on Tools with Artificial Intelligence |
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Country/Territory | Cyprus |
City | Limassol |
Period | 10/11/14 → 12/11/14 |