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Open AccessArticle

Octree-Based Generation and Variation Analysis of Skin Model Shapes

Production Engineering, Royal Institute of Technology (KTH), Brinellvägen 68, 114 28 Stockholm, Sweden
LEAX Falun AB, Främbyvägen 30, 791 52 Falun, Sweden
Author to whom correspondence should be addressed.
J. Manuf. Mater. Process. 2018, 2(3), 52;
Received: 8 July 2018 / Revised: 1 August 2018 / Accepted: 8 August 2018 / Published: 12 August 2018
(This article belongs to the Special Issue Smart Manufacturing Processes in the Context of Industry 4.0)
PDF [8275 KB, uploaded 12 August 2018]


The concept of Skin Model Shape has been introduced as a method for a close representation of manufactured parts using a discrete geometry representation scheme. However, discretized surfaces make irregular polyhedra, which are computationally demanding to model and process using the traditional implicit surface and boundary representation techniques. Moreover, there are still some research challenges related to the geometrical variation modelling of manufactured products; specifically, methods for geometrical data processing, the mapping of manufacturing variation sources to a geometric model, and the improvement of variation visualization techniques. To provide steps towards addressing these challenges this work uses Octree, a 3D space partitioning technique, as an aid for geometrical data processing, variation visualization, variation modelling and propagation, and tolerance analysis. Further, Skin Model Shapes are generated either by manufacturing a simulation using a non-ideal toolpath on solid models of Skin Model Shapes that are assembled to non-ideal fixtures or from measurement data. Octrees are then used in a variation envelope extraction from the simulated or measurement data, which becomes a basis for further simulation and tolerance analysis. To illustrate the method, an industrial two-stage truck component manufacturing line was studied. Simulation results show that the predicted Skin Model Shapes closely match to the measurement data from the manufacturing line, which could also be used to map to manufacturing error sources. This approach contributes towards the application of Octrees in many Skin Model Shape related operations and processes. View Full-Text
Keywords: manufacturing simulation; model prediction; variation propagation; error source identification; tolerance analysis manufacturing simulation; model prediction; variation propagation; error source identification; tolerance analysis

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Yacob, F.; Semere, D.; Nordgren, E. Octree-Based Generation and Variation Analysis of Skin Model Shapes. J. Manuf. Mater. Process. 2018, 2, 52.

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