A cost-benefit forecasting framework for assessment of advanced manufacturing technology development
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Abstract
Development of new Advanced Manufacturing Technology (AMT) for the aerospace industry is critical to enhance the manufacture and assembly of aerospace products. These novel AMTs require high development cost, specialist resource capabilities, have long development periods, high technological risks and lengthy payback durations. This forms an industry reluctance to fund the initial AMT development stages, impacting on their success within an ever increasingly competitive environment. Selection of suitable AMTs for development is typically performed by managers who make little reference to estimating the non-recurring development effort in resources and hardware cost. In addition, the performance at the conceptual stage is predicted using expert opinion, consisting of subjective and inaccurate outputs. AMTs selected are then submerged into development research and heavily invested in, with incorrect selections having a detrimental impact on the business. A detailed study of the UK aerospace manufacturing industry corroborated these findings and revealed a requirement for a new process map to resolve the problem of managing AMT developments at the conceptual stages. This process map defined the final research protocol, forming the requirement for a Cost-Benefit Forecasting Framework. The framework improves the decision making process to select the most suitable AMTs for development, from concept to full scale demonstration. Cost is the first element and is capable of estimating the AMT development effort in person-hours and cost of hardware using two parametric cost models. Benefit is the second element and forecasts the AMT tangible and intangible performance. The framework plots these quantified cost-benefit parameters and is capable of presenting development value advice for a diverse range of AMTs with varied applications. A detailed case study is presented evaluating a total of 23 novel aerospace AMTs verifying the capability and high accuracy of the framework within a large aerospace manufacturing organisation. Further validation is provided by quantifying the responses from 10 AMT development experts, after utilising the methodology within an industrial setting. The results show that quantifying the cost-benefit parameters provides manufacturing research and technology with the ability to select AMTs that provide the best value to a business.