Manual assembly planning methodologies have been in the center of industrial and academic research for many decades, since the manual assembly costs may often account for even half of the total manufacturing expenses. The existing and emerging manufacturing trends, such as mass customization and personalization, require fast responses when it comes to the conception and realization of the relevant manufacturing systems. Even though, work methodologies, such as concurrent engineering, have been proposed and applied, gaps still exist among product development, configuration and manufacturing. The Current Product Lifecycle (PLM) systems focus on the coordination of activities among engineers of different disciplines. However, they are unable to provide actual decision support functionality to decision makers. Moreover, solutions for the different phases of assembly planning have been proposed, without nevertheless taking into account the holistic nature of assembly planning that spans the different engineering phases.

The study presented in this paper is based on a methodology that integrates three distinct steps, regarding assembly planning; the generation of assembly related information, from the Computer Aided Design (CAD) files of an assembly, the calculation of the relevant process times from functions, generated through empirical measurements and the assembly line balancing of a line, based on the information gathered. The innovative aspect of this approach relies on the advancement of the relevant technologies as well as on their integration into a common working practice. The methodology enables the estimation of production related values in the later phases of product design or in the early phases of manufacturing planning. The generation of assembly precedence diagrams is made in an automatic way through the extraction of information on collision detection and the parts’ relations. This application is developed in the form of an add-on to a commercial CAD software suite. It utilizes features that are available in a wide range of such systems. The second step relies on the identification of specific features of parts, such as dimensions and mass. This information is then used as input in the functions already proposed in the academic literature for the estimation of the relevant process times for each part. Finally, the assembly line balancing is performed through the generation of the precedence diagram and the estimated process times, via a web-based service, which makes use of advanced optimization techniques.

In order for this methodology to be evaluated, a case study is presented by using the CAD file of an automotive sub-assembly. The case study demonstrates each step separately, beginning with the generation of the precedence diagram down to the balancing of the assembly line.

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