Speaker
Description
Additive Manufacturing Service Providers (AMSPs) have rapidly emerged with the increasing demand for mass-customized products. Evolving in a highly competitive market, AMSPs must provide accurate quotes, including price and delivery time, within a few minutes. Often receiving incomplete product manufacturing information (PMI), AMSPs face significant challenges in anticipating deviations between estimated and actual production costs.
This study investigates the correlation of a novel PMI quality assessment tool, the Formal Quality Level (FQL), with the related key performance indicator, KPIlevel, defined as the relative deviation between estimated and actual production costs. The analysis is conducted with real industrial data in the context of metal parts manufactured by Powder Bed Fusion with Laser Beam (PBF-LB).
Building on an original cost calculation modeling that integrates the advantage of process-map for high-quality PBF-LB production, our results demonstrate a strong correlation between the FQM and cost estimation accuracy: High-quality PMI is associated with low KPIlevel values of 1.3%, whereas low-quality level, characterized by incomplete or ambiguous PMI, leads to significantly higher deviations (exceeding 7.5%).
These findings support the use of FQL to mitigate the economic risks associated with automated quote generation. It can therefore provide valuable support for PBF-LB service providers in anticipating cost deviations and adjusting pricing strategies accordingly. Furthermore, this work contributes to the development of robust cost calculation methodologies for industrial AM by combining modeled process maps with the well-established process-based cost method.
| Speaker Country | Switzerland |
|---|---|
| Would you like to publish your paper in the special issue of BHM "Berg- und Hüttenmännische Monatshefte" | Yes |