Readiness And Satisfaction Assessment Approaches For Technology System Of Systems

To better meet the challenges in the new military reformation and the requirements in collaborational warfare, the Technology Systsm of Systems(TSo S) related research is of great importance in both the development of defense technologies and constructing the Weapon System of Systems(WSo S). TSo S is also a key factor in improving the WSo S combatant capabilities within the framework of information systems.TSo S is the integrateion of multiple technologies which are of a hierarchical structure and show system of systems characteristics. The basic elements in TSo S are the technologies and the correlations among different technologies. The objective of TSo S is to meet the capabilities/systems requirements which are derived from WSo S. Of all TSo S related studies, the TSo S satisfaction study answers this essential problem while the TSo S readiness assessment provides a more comprehensive persprctive on the readiness level of the technology group. The TSo S readiness/satisfaction assessment could be executed based on existed WSo S related studies. However, the technologies are more abstract than the elements from WSo S, such as the capabilities and systems. There involves substantial participation of experts’ knowledge, and most of all, multiple types of information under uncertainty need to be handled. Therefore, a series of studies are conducted in this thesis, including the generation and description approaches/framework, the readiness and satisfaction assessment approaches.Main contributions of this thesis are:(1) The TSo S generation and description approaches are proposed.First, the WSo S capabilities and systems requirements characteristics are analyzed, and based on which the TSo S related concepts are explored and the TSo S generation approach is proposed.The correlations among the elements in TSo S are analyzed. Using the multi-view theory from Do D Architecture Framework(Do DAF), a six-view classification scheme is proposed as the TSo S description framework.(2) The TSo S readiness assessment approach is proposed using the evidential reasoning algorithm.Based on the concepts of Technology Readiness Level(TRL), Integration Readiness Level(IRL) and System Readiness Level(SRL), a TSo S readiness assessment approach is proposed. The proposed approach uses the evidential reasoning algorithm to handle different types of information under uncertainty, especially the inadequate information which can not be handled using traditional approaches. Besides, an “integration-centric” perspective is applied by the proposed approach which could significantly reduce the computational complexity.(3) A Belief Rule Base(BRB) structure learning approach is proposed to handle the subjective TSo S satisfaction assessment problem.When dealing with subjective information in the TSo S satisfaction assessment, the main problem is that there is a lot of experts’ participation and therefore a lot of qualitative information. This problem is transformed into a multiple attributes decision analysis model. However, there is a combinatorial explosion problem when using the BRB expert system to model this problem. Therefore, three dimensionality reduction techniques are used to select the most representative attributes. Case studies result show that Principle Component Analysis(PCA) shows the best performance.(4) A BRB parameter learning approach is proposed to handle the objective TSo S satisfaction assessment problem.When dealing with objective information in the TSo S satisfaction assessment, the assessment is focused on the technical indices which represent the technologies in specific capabilities and systems. This problem is transformed into an optimization problem which includes the referenced values of the attributes as the parameters to be estimated. This parameter learning approach uses the Differential Evolutionary(DE) algorithm as the optimization engine, which is validated by case studies results.