Additive manufacturing offers completely new possibilities for the manufacturing of parts. The advantages of flexibility and convenience of additive manufacturing have had a significant impact on many industries, and optimizing part quality is crucial for expanding its utilization. This research aims to determine the sources of imprecision in fused deposition modeling (FDM). Process errors in terms of surface quality, accuracy and precision are identified and quantified, and an error-budget approach is used to characterize errors of the machine tool. It was determined that accuracy and precision in the y direction (0.08-0.30 mm) are generally greater than in the x direction (0.12-0.62 mm) and the z direction (0.21-0.57 mm). Furthermore, accuracy and precision tend to decrease at increasing axis positions. The results of this work can be used to identify possible process improvements in the design and control of FDM technology.

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Due to higher degrees of individualization, shorter product life cycles, and volatile selling markets, fulfilling customer demands -- the main task of automotive companies -- has become very complex. In order to tackle this complexity, new concepts that enable the decentralization of decision-making within the production process have become promising solutions. The advancement towards self-organized production requires novel approaches in the field of production program planning. This work introduces the concept of thevolume cycleas a new design factor in program planning. Additionally, a novel method to identify flexibility potentials in production sequences based on ,flexibility graphsis proposed, and the method is validated through a case study considering a segment of the assembly process for an automobile. Suitable visualization techniques for flexibility graphs are also discussed. Furthermore, in order to allow automatic analysis and evaluation of the flexibility potentials, methods of graph mining are introduced and the application possibilities of these techniques in terms of analyzing flexibility graphs are clarified. The results obtained from the case study illustrate that routing flexibility is not leveraged in today’s production lines, thus revealing a potential optimization domain.