الفهرس 
IntroductionOnly 14 pages are availabe for public view
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Abstract
SUMMARY UMMARY UMMARY
his study was conducted to evaluate the accuracy of different CAM techniques (additive and subtractive) for digitally designed removable partial denture frameworks.
An educational maxillary model with missing second premolars and first molars bilaterally was used for this study. After rest seat preparations were done a silicone index was made to be used to produce identical cast used for the two groups.
Scanning of the cast and designing of each component of the framework was done using the partial denture module in 3shape software to produce an STL file.
In the first group, the STL file was used to mill the design in the form of castable resin, which was sprued, invested and casted by lost wax technique into CoCr metal framework. In the second group, the STL file was used to print the design in the form of castable resin, which was casted by the same manner into CoCr frameworks. These steps were repeated to produce twelve frameworks, six in each group.
Comparative 3D analysis was used to measure the accuracy of the fabricated frameworks. Frameworks of each group were scanned using the 3Shape desktop scanner, then an STL file for each framework was generated. The STL files were imported into the Geomagic Control X software to be superimposed with the initial design to measure the deviation from it.
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Summary
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The results obtained from this study revealed higher accuracy of the subtractive manufacturing methods, and this difference was statistically significant.
Conclusion
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CONCLUSION ONCLUSION ONCLUSION
Conclusion:
Within the limitations of this study, it could be concluded that:
Additive and subtractive manufacturing are both reliable techniques for construction of highly accurate removable partial denture frameworks.
However, Subtractive manufacturing creates more accurate RPD frameworks.
Recommendation:
Further future research is required to explore the validity of different manufacturing techniques for removable prostheses.