Abstract

Machining process modeling requires cutter/workpiece engagement geometry in order to predict cutting forces. The calculation of these engagements is challenging due to the complicated and changing intersection geometry that occurs between the cutter and the in-process workpiece. Solid modelers can be used to perform these calculations by executing intersection operations between cutter and workpiece surfaces at successive cutter locations. These operations utilize parametric surface/surface intersection (SSI) algorithms. For the large number of engagements that can occur in machining a complicated workpiece this can be a time-consuming and sometimes unreliable process. In this paper, in-process machining features are introduced into machining process modeling for 2 1/2 D end milling, and a feature based approach is presented for addressing the computational complexity and robustness issues in the cutter/workpiece engagement calculations. Geometric Invariant (giF) and Form Invariant Machining Features (fiF) are modeled to help represent engagement conditions analytically. Volume decomposition and composition algorithms are described that extract these two types of machining features from the removal volumes generated at each tool pass. Cutter/workpiece engagements can be analytically extracted from giFs and fiFs without applying repetitive SSI operations. This paper presents one part of ongoing collaborative research into developing Virtual Machining Systems. The engagement conditions that are found are inputs to machining process models that identify cutting forces, predict stability and that optimize the process.

Full Text
Paper version not known

Talk to us

Join us for a 30 min session where you can share your feedback and ask us any queries you have

Schedule a call

Disclaimer: All third-party content on this website/platform is and will remain the property of their respective owners and is provided on "as is" basis without any warranties, express or implied. Use of third-party content does not indicate any affiliation, sponsorship with or endorsement by them. Any references to third-party content is to identify the corresponding services and shall be considered fair use under The CopyrightLaw.