Papers by Author: Nan Zhao

Abstract: Facing the condition of scattered and disorder design knowledge and insufficient innovative capacity of Small and Medium Enterprises (SMEs) in Cloud Manufacturing environment, making for the design of knowledge assembled into orderly combination of knowledge resources, this paper presents the service capacity of evaluation model of knowledge resources and programming knowledge resources in the assembly sequence the mathematical model of the planning and design to solve the model of quantum harmony search algorithm (QHS). QHS algorithm bases on the Latin hypercube (LH), and improves the global search capability through the introduction of quantum coding and quantum gate transformation. Taking mold design knowledge of SMEs resources planning issues as example, according to the mathematical model, QHS algorithm aims to solve the knowledge resources assembly sequence of the optimal design in the cost and quality constraints, and verifies the feasibility and practicality of the method. This paper has practical significance to improve the overall SMEs innovation and design capabilities and make the reuse of the design knowledge more efficiency in the Cloud Manufacturing environment.

Abstract: It is valuable for supply chain management to analyze and evaluate the operation performance of supply chain, and use timely and accurate operation state feedback to adjust the system to keep smooth running. Aiming at the complexity and uncertainty of supply chain, this thesis put forward a heterogeneous selective ensemble principle component analysis (PCA) algorithm based on fuzzy integral via Bagging ensemble learning. Besides, by using dimension reduction on high-dimensional data set, it realizes to extract the key factors of supply chain performance and breaks the bottleneck that problems in supply chain management cannot be recognized rapidly or analyzed by traditional performance evaluation method. According to the empirical research on survey data of supply chain performance at C Group, the algorithm is proved be effective.

Abstract: According to the current situations of the unorganized and disorderly design knowledge as well as the weak innovation capability for SMEs under cloud manufacturing environment, and aiming at combining the design knowledge into ordered knowledge resource series, the service ability assessment model of knowledge resource was eventually proposed, and moreover, the Projection Pursuit-Principal Component Analysis (PP-PCA) algorithm for service ability assessment was further designed. The study in this paper would contribute to the realization of the effectiveness and accuracy of the knowledge push service, which exhibited a significant importance for improving the reuse efficiency of knowledge resources and knowledge service satisfaction under the cloud manufacturing environment.

Abstract: Aimed at the complexity and uncertainty of the diagnosis analysis of supply chain performance, this paper proposes a kind of diagnosis method of supply chain performance based on Bayesian network (BN). Based on the self-adaptive fuzzy interpretive structural model proposed in this paper, effective information could be provided to the structural learning of BN to enhance the modeling precision and reliability. Finally, according to investigating supply chain performance data of C Group, BN diagnosis model of supply chain operational cost is established. The consistent empirical analytical result and management practice prove the validity and feasibility of the method in this paper.

Abstract: For explicating the underlying linking mechanism between IT investment and firm performance, this paper develops a framework to examine the influence factors of IT payoff efficiency. From a process-oriented perspective, the study measured the IT investment efficiency using continuous data from 485 Chinese enterprises in 2006-2008. The result shows that only 11.03% of total samples are effective based on data envelopment analysis(DEA). So it suggests that a majority of firms can achieve differential performance over competitors by improving the organization’s capacity to absorb IT. And then some main factors that affect technical efficiency were identified using classification and regression trees(CART) method. The results indicate the influence factors including enterprises’ scale, strategic IT planning and density of trade’s fund. The interaction of information system application and training density positive influences IT investment efficiency. Possibility for future research can keep on in these areas.

Abstract: The IT performance evaluation is a complex analysis system. Some key factors that can reflect the essential characteristics and be easy to acquire, should be extracted to help us to clarify evaluation, analysis and diagnoses. In this paper for the uncertainty of IT performance data, an algorithm of IT performance key factors extraction based on selective ensemble of principal component analysis (PCA) is proposed. Unlike the traditional PCA algorithm, PCA selective ensemble increase the difference degree between the main component and the others. Moreover it expands the selective ensemble in the application of unsupervised algorithm. The validity of the algorithm is verified through the analysis of the actual data.

Abstract: Based on systematic engineering theory and method, interpretative structural model of ceramic grindability system was set up. Property parameters, grinding parameters and grindability indexes were selected as system elements. The adjacency matrix between system elements was constructed. The reachability matrix was calculated according to adjacency matrix. By calculation of reachability matrix and classification, interpretative structural model of the ceramic grindability system was obtained. The system model could describe the relationship between the ceramic grindability and system elements. The grindability system model also provides a fundamental theoretical reference for the research on the grindability of ceramic materials. The weight of each influencing factor of ceramic grindability can be calculated by applying the system model. The grindability of ceramic materials can be evaluated objectively and comprehensively.

Abstract: Data envelopment analysis (DEA) evaluation system of metal materials was established. Evaluated metal materials were regarded as decision making units (DMUs). Property parameters of metal materials were selected as inputs of DMUs, and machining process parameters were selected as outputs of DMUs. Input and output data sequences could be obtained through data processing operations. Mathematics programming model was founded and optimal values of all the evaluated materials were calculated based on the model. Machinabilities of metal materials could be evaluated by comparing the optimal values. Taken 1Cr18Ni9Ti, GCr15, Q235, 45# and LY11 for example, machinabilities of five metal materials were ranked. Research results suggest that DEA method can synthetically consider the relationship between property parameters and machining process parameters. DEA is proved to be a reasonable and available method to evaluate metal material machinability.