Fuzzy forecasting of workload for aircraft design projects

The aim of this thesis is to constitute a valid, accurate and simply applicable model for predicting aircraft design workload in system environment that have lack of data set or uncertainty. Design cycle of an aircraft is described with three concepts. These are concept design, preliminary design and detail or critical design. In concept design phase, rough sketchs are determined. Also, characteristics about aircraft such as performance, size and systems architecture are settled on. Preliminary design phase is interested in more detailed design requirements. Some technical calculations, aerodynamics, propulsion and other system design features are extended. Detail design is the final phase that notified all product characteristics meet desired necessities in terms of aircraft components. During this stage, aircraft parts are tried to be fabricated and prototype of a real aircraft is manufactured and tested. As it is seen, product development, especially for aircraft design loop, has troublesome and complicated progression. In all phases, it requires continues iterations to reach exact match. There can be numerous activities from the beginning to the end of the design cycle and each activity can contain uncertainty by nature of design. Therefore, it is probable that prediction of any activity is also uncertain. In previous studies, there are lots of methods for forecasting and generally titled as cost estimation methods. These methods are splitted into two categories as qualitative and quantitative cost estimation techniques. While qualitative cost estimation methods are often used prior to design in product development, providing an inference based on the intuitive similarities of the past product or project, quantitative cost estimation techniques are applied using a detailed mathematical analysis, mostly due to the existence of an adequate set of data in a more mature project or product phase. In this study, fuzzy logic, which is a qualitative estimation method, is used because it is easy to respond to the uncertain system environment in the proposed model. The data set has been analyzed for different types of aircraft obtained from the literature, and some performance and size characteristics of the aircraft have been determined as input variables. It has been observed that the prediction of the workload estimation of the future aircraft design projects with the model formed by the triangular fuzzy membership function, which is frequently used in the fuzzy logic methodology, can give the appropriate results according to the similarity variables.