DEVELOPMENT OF A DEVIATION-DRIVEN FRAMEWORK FOR SELECTIVE MESH CORRECTION IN ADDITIVE MANUFACTURING

Mircea H. MUNTEAN, Vlad I. BOCANET, Adrian C. POPESCU

Abstract


Additive manufacturing has gained prominence for producing complex geometries with minimal lead time, yet systematic geometric deviations remain a persistent challenge. The current study presents a framework for targeted mesh morphing based on consistent deviation mapping to selectively compensate for systematic geometric errors. The framework uses stereoscopic scanner data to precisely determine surface deviations. Surface deviations are quantified by comparing multiple parts printed under similar conditions to the original CAD model. Deviation vectors are computed for each vertex in two sections, across multiple parts and systematic errors are identified by analyzing the statistical distribution of deviations. Only vertices exhibiting consistent deviations, defined as those with a standard deviation below a defined threshold and a mean deviation exceeding a minimum magnitude, are selected for compensation. Targeted morphing is done by applying corrective adjustments exclusively to the selected regions. This prevents over-compensation while minimizing computational overhead. A validation module re-scans the compensated part to assess the reduction in deviation magnitude, forming a feedback loop to refine morphing parameters. This approach has the potential to enhance precision targeting of systematic errors, reduce computational complexity, and adaptive parameter optimization. It can improve geometric accuracy and preserve surface integrity, which makes it a cost-effective solution for enhancing dimensional fidelity in additive manufacturing processes.

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References


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