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The paper presents theoretical modeling and an experimental investigation of the variation of oil effective bulk modulus (βe) with pressure in hydraulic systems. A pressure sensitive model of βe and its several simplified forms have been derived. In addition, a method for parameter identification has been formulated. In an actual hydraulic system, values for βe at different load pressures were obtained, model parameters identified and modelling errors evaluated.

Knowledge‐based timed colored object‐oriented Petri net (KTCOPN) is presented as a modelling method for a reconfigurable assembly system (RAS) in this paper. Compared to the conventional flexible assembly systems, the configuration of a RAS will allow flexibility not only in assembling a variety of products, but also in changing the system itself. Combining knowledge and object‐oriented methods into timed colored Petri net, allow the characteristic of RAS to be fully expressed. With object‐oriented methods, the whole system can be decomposed into concrete objects explicitly, and their relationship is constructed according to the system assembly requirements. Finally, a simple assembly system modeled by the KTCOPN is given.

Scheduling problems are difficult combinatorial problems because of the extremely large search space of possible solutions and the large number of local optima that arise. A multiobjective genetic algorithm is presented as an intelligent algorithm for scheduling of the mixed-model assembly line in this paper. The Pareto ranking method and distance-dispersed approach are employed to evaluate the fitness of the individuals. The computational results show that the proposed multiobjective genetic algorithm is quite effective.