Engineering change modelling using a function-behaviour-structure scheme

Some of the work contained in this dissertation has been published and presented as below: - B.Hamraz, N.H.M.Caldwell, D.C.Wynn, and P.J.Clarkson, (2013): Requirements-based Development of an Improved Engineering Change Management Method. Journal of Engineering Design, online first, DOI: 10.1080/09544828.2013.834039. - B.Hamraz, N.H.M.Caldwell, and P.J.Clarkson, (2013): A Holistic Framework for Categorisation of Literature in Engineering Change Management. Systems Engineering 16 (4). - B.Hamraz, O.Hisarciklilar, K.Rahmani, D.C.Wynn, V.Thomson, and P.J.Clarkson, (2013): Change Prediction Using Interface Data. Concurrent Engineering 21 (2), pp. 139-154. - B.Hamraz, N.H.M.Caldwell, and P.J.Clarkson, (2012): A Multi-domain Engineering Change Propagation Model to Support Uncertainty Reduction and Risk Management in Design. Journal of Mechanical Design 134 (10), pp. 100905.01-14. - B.Hamraz, N.H.M.Caldwell, and P.J.Clarkson, (2012): A Matrix-calculation-based Algorithm for Numerical Change Propagation Analysis. Transactions on Engineering Management 60 (1), pp. 186-198. - B.Hamraz, N.H.M.Caldwell, and P.J.Clarkson, (2012): FBS Linkage Model – Towards an Integrated Engineering Change Prediction and Analysis Method. Proceedings of the International Design Conference (DESIGN'10), Dubrovnik, Croatia, pp. 901-910.Engineering changes are unavoidable and occur throughout the lifecycle of products. Due to the high interconnectivity of engineering products, a single change to one component usually has knock-on effects on other components causing further changes. This change propagation significantly affects the success of a product in the market by increasing development cost and time-to-market. As such engineering change management is essential to companies, but it is a complex task for managers and researchers alike. To address this challenge, the thesis at hand investigates the state-of-the-art of research in engineering change management and develops a method to support engineering change propagation analysis, termed FBS Linkage. This method integrates functional reasoning with change prediction. A product is modelled as a network of its functional, behavioural, and structural attributes. Change propagation is then described as spread between the elements along the links of this network. The FBS Linkage concept is designed based on a comprehensive set of requirements derived from both the literature and industry practices as well as a comparative assessment of existing change methods and functional reasoning schemes. A step-by-step technique of building and using an FBS Linkage model is demonstrated. The method’s potential benefits are discussed. Finally, the application of the method to two industrial case studies involving a diesel engine and a scanning electron microscope is presented. The method evaluation indicates that the benefits of the method outweigh its application effort and pinpoints areas for further refinement.This work was supported partly by the Engineering and Physical Sciences Research Council (EPSRC) and partly by the Transatlantic Partnership for Excellence in Engineering (TEE)

Engineering Change Protocols for Behavioral and System Synthesis

Rapid prototyping and development of in-circuit and FPGA-based emulators as key accelerators for fast time-to-market has resulted in a need for efficient error correction mechanisms. Fabricated or emulated prototypes upon error diagnosis require an effective engineering change (EC). We introduce a novel design methodology which consists of pre- and post-processing techniques that enable EC with minimal perturbation. Initially, in a synthesis preprocessing step, the original design specification is augmented with additional design constraints which ensure flexibility for future correction. Upon alteration of the initial design, a new post-processing technique achieves the desired functionality with near-minimal perturbation of the initially optimized design. The key contribution is a constraint manipulation technique which enables the reduction of an arbitrary EC problem into its corresponding classical synthesis problem. As a result, in both preand post- processing for EC, classical synthesis algorithms can be used to enable flexibility and perform the correction process. We demonstrate the developed EC methodology on a set of behavioral and system synthesis tasks