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Uncertain systems: Models, methods and applications, Part 1
Edited by Sifeng Liu, Jeffrey Forrest, Yingie Yangjie, Ke Zhang, Chuanmin Mi and Naiming Xie
1 Introduction
As a product of the modern science and technologies, complex equipments with a lot of new characteristics, such as high knowledge intensity, high technical contents, high input costs and so on. And its R&D process refers to a wide range of technologies and subjects. As the embedded technologies diffuse in a wide scope with a high rate, the overflow effect of technological innovation is very significant, which can lead to the birth of similar products and promote the national competition capability. However, it is a huge challenge to holistically develop the methods, tools and platforms to manage the R&D process of complex equipments because that those previous system analysis methods cannot describe the relationships between systems, which is caused by the ambiguous structures and boundaries of complex equipments.
There are a lot of models deal with R&D process management of complex equipments. [1] Xue et al. (2007) put forward an integrated multilayer PUSH-PULL production plan management system based on critical path method (CPM), and constructed a production plan control model based on the realization methods of dynamic process management of multilayer production plan and resources optimization. These measures guarantee the veracity of activity planning and modification consistency of production planning. According to large-scale intermittent manufacturing of complex equipment has the production characteristics of design-to-order products, one-of-a-kind or low volume, etc. [2] Xue et al. (2006) gave the hierarchical structure, key technologies and application solution of the integrated production system for complex equipment were implemented. According to the long R&D cycle, high investment costs and high risk, [4] Chen (2008), [5] Liu and Lian (2009) and [6] Zhu (2006) presented a cost control structure of large-scaled complex equipment development. At the same time the method of knowledge representation and inference engine were given based on this structure. [7] Wang and Zhang (2010) developed system design, considering complex product as a systematic whole. The system of detection and control about R&D process of complex product was proposed, which is consistent with five principles and five information types. [8] Chen et al. (2009) analyzed the development procedure and characteristic of complex aircraft...