The development of novel CAD/CAM strategies for high efficiency machining

View/ open
Author
Dotcheva, Mariana
Date
2006Type
Thesis
Publisher
Cardiff Metropolitan University
Metadata
Show full item recordAbstract
End milling is a widely used cutting process involved in different types of finishing profile machining, where the geometry is complex, the tolerances are small and the cost of the operations is high. Despite tremendous developments in CAM software, cutting tool technology and machine tool technology, end-milling results still depend to a large extent on the knowledge inherent within manufacturing staff.
The work presented in this thesis is a CAD/CAM-related strategy that promotes high efficiency machining by taking into consideration the process geometry, the cutting forces, and surface accuracy requirements of a particular part. The study is focused on cutting process geometry identification, milling operation modelling and machining parameters optimisation. A hybrid model of the end-milling process has been developed, which incorporates several models, based on different approaches in order to reflect the specifics of the complex milling process.
This research has developed an optimisation strategy, which is a tool for defining optimum cutting conditions. The cutting tool deviation reflects the action of the cutting forces and is the dominant parameter in the machining error equation, consequently it takes the major role in the optimisation process. A mechanistic-force model and two-stage cantilever model of the cutting tool are the basis of the end-milling simulation. The optimisation strategy generates variable feed rate which is constrained by the machining errors, tolerances and surface roughness requirements.
The presented machining error synthesis converts the general optimisation approach to the particular machining process, taking into consideration the geometrical error of a specific machine tool, the accuracy of the cutting tool and the CAM tool path tolerance.
This research enhances the identification of cutting-force coefficients by developing a new methodology based on the experimentally obtained cutting-tool deviation. The new methodology provides the simulation process with instantaneous cutting-force coefficients, which are independent of the cutting operation geometry. It can be applied to any end-milling configuration if the workpiece material and cutting tool are the same.
The experimental results verify the theoretical findings and confirm that the proposed optimisation approach creates a more efficient operation-planning environment. The optimised tool paths achieve the required surface accuracy and surface roughness, and performed the cutting operations at shorter machining times, compared with the same operations cut with constant cutting conditions. The experimental programme also includes a comparison between up- and down-milling.
Description
PhD
Collections
Related items
Showing items related by title, author, subject and abstract.
-
iCUS: Intelligent CU Size Selection for HEVC Inter Prediction
Erabadda, Buddhiprabha; Mallikarachchi, Thanuja; Kulupana, Gosala; Fernando, Anil (IEEE, 2020-08-03)The hierarchical quadtree partitioning of Coding Tree Units (CTU) is one of the striking features in HEVC that contributes towards its superior coding performance over its predecessors. However, the brute force evaluation ... -
PREDICTION OF GENEOME SEQUENCE USING MACHINE LEARNING ALGORITHMS
Alshahrany, Yazeed (CARDIFF METROPOLITAN UNIVERSITY, 2018-07)Machine learning is logically designed and invented to enable computers to assist humans in predicting the behaviour of systems and making sense of large, complex datasets. This technology uses experimental data to optimize ... -
Generating Optimal Code Using Answer Set Programming
Crick, Tom; Brain, Martin; De Vos, Marina; Fitch, John (SpringerCardiff School of Management, 2009)This paper presents the Total Optimisation using Answer Set Technology (TOAST) system, which can be used to generate optimal code sequences for machine architectures via a technique known as superoptimisation. Answer set ...