Abstract
Single Point Incremental Forming (SPIF) is a relatively new process that has been recently used to manufacture medical grade titanium sheets for implant devices. However, one limitation of the SPIF process may be characterized by dimensional inaccuracies of the final part as compared with the original designed part model. Elimination of these inaccuracies is critical to forming medical implants to meet required tolerances. In this study, a set of basic geometric shapes were formed using SPIF to characterize the dimensional inaccuracies of grade 1 titanium sheet parts. Response surface functions are then generated to model the deviations at individual vertices of the STL model of the part as a function of geometric shape parameters such as curvature, depth, wall angle, etc. The generated response functions are further used to predict dimensional deviations in a specific clinical implant case. The predicted deviations show a reasonable match with the actual formed shape and are used to generate optimized tool paths for minimized shape and dimensional inaccuracy. Further, an implant part is then made using the accuracy characterization functions for improved accuracy. The results show an improvement in shape and dimensional accuracy of incrementally formed titanium medical implants.
Highlights
Titanium is the material of choice in Class III medical implants due to its biological inertness, strength, lightweight nature, bio-compatibility and low cost production [1]
Some accuracy characterization techniques are available. These include the use of Multivariate Adaptive Regression Splines (MARS) within a feature based framework for predicting the behavior of simple features and feature interactions [9] and a local geometry matrix to predict springback [10]
To overcome the limitations of the current accuracy characterization techniques, an effort is made in this work to generate accuracy response surfaces for freeform shapes. This is done by studying the accuracy behavior of ellipsoidal shapes formed using Single Point Incremental Forming (SPIF)
Summary
Titanium is the material of choice in Class III medical implants due to its biological inertness, strength, lightweight nature, bio-compatibility and low cost production [1]. These include the use of Multivariate Adaptive Regression Splines (MARS) within a feature based framework for predicting the behavior of simple features and feature interactions [9] and a local geometry matrix to predict springback [10]. These works did not provide any methods for predicting inaccuracy in freeform implant shapes. To overcome the limitations of the current accuracy characterization techniques, an effort is made in this work to generate accuracy response surfaces for freeform shapes This is done by studying the accuracy behavior of ellipsoidal shapes formed using SPIF. These models are used to predict accuracy behavior of new implant geometries and the predicted behavior is used to compensate the parts
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