An Integrated Approach for Precision Machining of Freeform Surfaces

atmire.migration.oldid1788
dc.contributor.advisorXue, Deyi
dc.contributor.advisorGu, Peihua
dc.contributor.authorLasemi, Ali
dc.date.accessioned2014-01-18T01:20:18Z
dc.date.available2014-03-15T07:00:18Z
dc.date.issued2014-01-17
dc.date.submitted2014en
dc.description.abstractFreeform surfaces, also called sculptured surfaces, have been increasingly used in different industries such as automotive, aerospace, and die and mold manufacturing. Increasing precision requirements for products with freeform surfaces have led to significant challenges for manufacturing companies. Multi-axis CNC machining is the primary method to manufacture these freeform surfaces. Prediction of machining errors with different geometric shapes under varying machining conditions is the key to improve quality in freeform surface manufacturing. An integrated approach for precision machining of freeform surfaces has been developed in this research. In the first step of this approach, geometric errors of machine tool and process-related errors are identified and compensated. Geometric errors of machine tool are identified through a newly developed offline identification method using the kinematic modeling of machine tool and magnetic double ball bar measurement of the machine's volumetric errors. Process-related errors are modeled as functions of machining process and freeform surface parameters, and measured using on-machine inspection in a multi-layer machining method. These identified error sources are then compensated through tool path re-planning using the mirror approach. In the second step of the integrated approach, the machined surface is inspected to identify and remove any residual errors on the surface. Since comparison between manufactured surface and design surface is conducted by aligning the two surfaces in different coordinate systems, an optimization method is introduced to identify the best alignment with minimum area of the error regions to reduce the re-machining efforts. When error regions on the manufactured surface are identified, CNC machining tool paths need to be generated to remove these errors. Since various tool path generation methods may be used for the identified error islands on the surface, mapping between the error islands and the tool path generation methods needs to be studied. In this research, the mapping is conducted by analyzing the geometric characteristics of each error island and the capabilities of the tool path generation algorithms. The results obtained through different evaluation methods, such as simulations, measurement of machine tool's volumetric accuracy, and machining experiments, reveal significant improvement in the accuracy and efficiency of freeform surface machining process.en_US
dc.identifier.citationLasemi, A. (2014). An Integrated Approach for Precision Machining of Freeform Surfaces (Doctoral thesis, University of Calgary, Calgary, Canada). Retrieved from https://prism.ucalgary.ca. doi:10.11575/PRISM/24904en_US
dc.identifier.doihttp://dx.doi.org/10.11575/PRISM/24904
dc.identifier.urihttp://hdl.handle.net/11023/1267
dc.language.isoeng
dc.publisher.facultyGraduate Studies
dc.publisher.institutionUniversity of Calgaryen
dc.publisher.placeCalgaryen
dc.rightsUniversity of Calgary graduate students retain copyright ownership and moral rights for their thesis. You may use this material in any way that is permitted by the Copyright Act or through licensing that has been assigned to the document. For uses that are not allowable under copyright legislation or licensing, you are required to seek permission.
dc.subjectEngineering--Mechanical
dc.subject.classificationFreeform Surfacesen_US
dc.subject.classificationCNC Machiningen_US
dc.subject.classificationFreeform Surface Inspectionen_US
dc.subject.classificationError Compensationen_US
dc.subject.classificationMachine Toolen_US
dc.titleAn Integrated Approach for Precision Machining of Freeform Surfaces
dc.typedoctoral thesis
thesis.degree.disciplineMechanical and Manufacturing Engineering
thesis.degree.grantorUniversity of Calgary
thesis.degree.nameDoctor of Philosophy (PhD)
ucalgary.item.requestcopytrue
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