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Cellular manufacturing has become an integral part of lean manufacturing systems; more and more attentions have been paid to cellular manufacturing. Although the quality and productivity of cell production systems depends largely on operators skill and other human factors, it is still insufficient to investigate how human factors affect manufacturing cells. Here, we apply structural equation modeling to analyze the impact of human factors on productivity of cellular manufacturing. We design a laboratory experiment of cellular manufacturing to measure the efficiency of the operators in manufacturing cells and meanwhile, conduct a questionnaire to grasp the operators aptitude. A covariance structure model is constructed based on the experiment data and the questionnaire s answers, the potential causal dependencies between the productivity and human factors can be showed graphically and quantitatively through the pass diagram. Our results have showed that operators aptitude has significant effects on cell s efficiency and the impact of operators aptitude is largely stronger than the learning effect.

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This paper deals with the vehicle routing problem involved with fuzzy/imprecise vehicle travel times and customer service times, these fuzzy/imprecise times are represented as fuzzy numbers and interpreted as possibility distributions. According to the same consideration as the stochastic programming with recourse, we treate the influence of the fuzziness of travel times and service times as recourse cost. and solve the fuzzy vehicle routing problem through twostage decisions. As the result, a two-stage possibilistic programming model is formulated. By choosing an appropriate definition of fuzzy mean, we can show that the proposed model is equivalent to an ordinary crisp programming problem. Furthermore, We propose a solution method based on Ant Colony System (ACS) to obttain the best solution of the problem. Finally, some examples are given to illustrate the two-stage model and the solution algorithm.