{"id":{"repo_id":"cambridge","oai_identifier":"oai:www.repository.cam.ac.uk:1810/244879"},"canonical_url":"https://search.dev.ndltd.org/etd/cambridge/oai:www.repository.cam.ac.uk:1810/244879","repository":{"repo_id":"cambridge","name":"Cambridge University","base_url":"https://api.repository.cam.ac.uk/server/oai/request"},"display":{"title":"Supporting design planning through process model simulation","abstract":"Modelling and analysis of design processes is non-trivial and predicting the behaviour of such systems is especially challenging. Nonetheless, the effective planning of design projects is critical for many engineering companies. Based on the findings from a thorough literature review and an extensive industrial case study, this thesis identified four themes on which subsequent process analyses focused: modelling and representation; scale and connectivity; rework, and the product-process link. The case study also provided a deeper understanding of the practical challenges of planning in industry. In order to meet these challenges, both the Signposting modelling framework and simulation tool were enhanced to provide increased functionality for process modelling, representation and analysis. Further, novel approaches for process analysis - the use of hypothetical models and confidence profiles that link product and process information - were proposed. A software tool was developed to automatically generate such hypothetical models. Simulation analyses were performed on both hypothetical and real-world models. The results elucidated the effects of structural variations in terms of scale and connectivity on project performance. They also showed how task reordering due to rework can lead to major process delays, even when the time taken to rework failed tasks is extremely short. Further, the simulation analyses demonstrated how confidence profiles could be used to identify rework early in the process and reduce the resulting project schedule impact. The results from the simulation analyses were evaluated against historical data from the case study company and heuristics for design planning were defined. Overall, this research demonstrated how simulation analysis of both real-world and hypothetical models, using the enhanced Signposting tool, can provide useful insights into design process planning.","abstract_html":"Modelling and analysis of design processes is non-trivial and predicting the behaviour of such systems is especially challenging. Nonetheless, the effective planning of design projects is critical for many engineering companies. Based on the findings from a thorough literature review and an extensive industrial case study, this thesis identified four themes on which subsequent process analyses focused: modelling and representation; scale and connectivity; rework, and the product-process link. The case study also provided a deeper understanding of the practical challenges of planning in industry. In order to meet these challenges, both the Signposting modelling framework and simulation tool were enhanced to provide increased functionality for process modelling, representation and analysis. Further, novel approaches for process analysis - the use of hypothetical models and confidence profiles that link product and process information - were proposed. A software tool was developed to automatically generate such hypothetical models. Simulation analyses were performed on both hypothetical and real-world models. The results elucidated the effects of structural variations in terms of scale and connectivity on project performance. They also showed how task reordering due to rework can lead to major process delays, even when the time taken to rework failed tasks is extremely short. Further, the simulation analyses demonstrated how confidence profiles could be used to identify rework early in the process and reduce the resulting project schedule impact. The results from the simulation analyses were evaluated against historical data from the case study company and heuristics for design planning were defined. 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