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The satisfaction of customer requirements (CRs) is the objective of product configuration. A methodology Based on the Kano's model was proposed to explore customers' stated needs and unstated desires and to resolve them into different categories which have different impacts on customer satisfactions (CSs). The customer satisfactions are classified into group satisfaction and individual satisfaction, and each of them has three types with Kano theory. Group requirements items were selected frequently by the same kind of customers. Individual requirements were specified by the customer himself. Based on a combination of group satisfactions and individual satisfactions, the integrated satisfaction was determined. A case study is provided to illustrate the effectiveness of the presented method.

This paper is focused on the human factors and assessment methods at workplace firstly. Then the human factors are analysed and evaluated to quantized by Analytic Hierarchy Process and Entropy method. On that basis, the multicriteria quantizing model is build, at last the human factors at piston production line as an example is given. According to the result of model, it provides a scientific evidence to make the human factors in difference processes perfect: improving operating efficiency, optimizing working posture.

In this paper, combining quantitative human factors load with production line balance (PLB), a set of systematic methodology is developed. Firstly, after analyzed the importance of human factors, the evaluation of those is briefly introduced. Then, a model of PLB considering human factors is developed, whose objectives are to minimize the workers number and smooth the human factors load in one cell/worker. Finally, a piston production line as an example is to optimize and simulate by Quest. The optimizing and simulating results indicate that considering human factor load of each process/task can make workers’ workload more balance and more practical significance than only time.

For the completeness and accuracy of customers' requirements information in the mass customization paradigm, a method of ontology-driven personal requirements elicitation based on scenario was proposed. Firstly, customer scenario model and product requirements model based on ontology theory were constructed respectively. Association rules were mined with Apriori algorithm using the method of metarule. Scenario ontology was mapped to requirement ontology completely. Then, customers' personal requirements information was elicited completely and accurately. Finally, industrial case study has been performed to demonstrate the practicality and effectiveness of the proposed approach.