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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.

The purpose of this paper is to develop a computationally efficient and generally applicable measure for a pipe routing problem which decides the pipe paths and affects the pipe assembly feasibility. By imitating human thinking in pipe assembly planning, human's experience and intuition are quantified and applied in the pipe routing algorithm.

Human's imaginal thinking is simulated with procedures of knowledge representation, pattern recognition, and logical deduction; the algorithm transforms the physical obstacles and constraints into 3D pipe routing space and then into 2D planar projection, by using convex hull algorithm onto the projection, the shortest pipe route is found efficiently.

A novel pipe assembly planning algorithm by imitating human imaginal thinking is presented, which effectively solved the problem of conceiving the shortest pipe route in 3D space with obstacles and constraints.

The application of the algorithm in assembly planning of an aircraft engine pipe system is demonstrated. The algorithm can also be used in similar pipe planning problems such as industrial plant pipe planning and submarine pipe system design.

Human's imaginal thinking is introduced into pipe routing algorithm for the first time. By using graphics as the media to transfer the pipe routing information, human's experience and intuition in pipe assembly planning are quantified and computationally applicable.