Product development projects, especially in the aerospace industry, still suffer from significant cost overruns. The failure to meet planned cost and schedule is one of the most critical issue in this industry. Many researchers and scientists focused first on process and tools to shorten the time and reduce the cost of new product development projects. The results were far from resolving this issue and the overruns persist. Thus, the focus was reoriented towards enhancing the accuracy of estimates that rapidly was point out as the main cause of these overruns. In fact, if the cost and time are estimated within a reasonable degree of accuracy, the ability to schedule, forecast, and conduct trade-offs, among others, will become much easier (Salam & Bhuiyan, 2016). Otherwise, poor estimations could even lead, in some cases, to severe difficulties due to wrong financial decisions made about engagement and partners’ relationship management. Thus, one of the most important questions that confront the project manager in the planning phase of new product development is "how to get the right estimates of cost and time?" Different approaches, methods, and models were developed for this purpose and a large number of research papers were published regarding effort estimation in new product development. Most of them are modeling based on the use
of some specific drivers for estimation matter.
Despite the number of research and refinement about cost estimating during last decades and the diversity of approaches, models and tools developed for this matter, the aerospace product development projects still suffer from severe cost and schedule overruns. In fact, the final costs of US space programs continue to exceed initial cost estimates by an average of more than 45% (Keller et al., 2014). Considering the complexity of product development systems especially the high level of uncertainty at the early stage of product development planning, achieving high degree of cost estimates accuracy is very questionable with conventional models.
Parametric estimation remains the most common technique for effort estimation and modeling in aerospace industry; But why these parametric models suffer from severe performance deviation and fail to provide accurate estimates? To address this issue, one need to ask some fundamental questions. Are these models using the right set of drivers or input parameters in gender and number? Are the statistical foundations of regression techniques appropriate to models the dynamic and interactions among effort drivers in the aerospace industry? If the answer is no, thereby, it is not time to throw away these conventional regression models and explore the potential of newer techniques?
This research project aims to deal with the problem of overruns with an integrated and dynamic approach. It seeks to identify and overcome the main issues with current cost estimation models in aerospace product development and proposes new models and approach to deal with the issue of cost overruns in aerospace product development. These models will consider personalized elements of product development in the aerospace industry and integrate the effects of main concepts in effort modeling. These models are also based on new techniques with robust statistical foundations and more appropriate to complex environments. Besides effort modeling and estimation this research project proposes a new approach to control overruns through the estimation of the overrun level during preliminary phases of project execution.
| Date | 18 Dec 2020 |
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| Original language | French |
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| Awarding Institution | - École de technologie supérieure
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| Supervisor | Yvan Beauregard (Supervisor) & Nadia Bhuiyan (Co-supervisor) |
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Jaifer, R. (Author),
Beauregard (Supervisor) & Bhuiyan (Co-supervisor),
18 Dec 2020Student thesis: Doctoral thesis › Doctorate in Engineering: Engineering