2 research outputs found
Research on the integrated management and mapping method of BOM multi-view for complex products
The bill of materials (BOM) runs through all stages of the life cycle of manufacturing products, which is the core of manufacturing enterprises. With increasing complexity of modern manufacturing engineering and widespread using of intelligent manufacturing technology, the BOM data keeps rising and transformation process is increasingly frequent and complicated. In order to improve efficiency of BOM management and ensure the diversity, accuracy and consistency of BOM in the product development, the BOM multi-view integrated management and mapping method for complex products were researched. First, a complex product BOM integrated management framework and the evolution model based on multiple views were established which described the BOM integrated management mechanism and transformation relationship among different BOMs. Subsequently, process of BOM transformation was analyzed, and a BOM transformation model was proposed. Moreover, a rule-based BOM multi-view mapping algorithm was proposed. With the rule definition and mathematical modelling for key components, the complex mapping principle was elaborated. Finally, the BOM multi-view transformation cases and the prototype system were illustrated and discussed, which verified the feasibility and versatility of model and method
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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)