Abstract
This paper presents a systematic method to compensate for dimensional errors of workpieces machined in computer numerical control (CNC) batch grinding process. The dimensional error precompensation scheme includes a fractional order compensator, automatic dimensional measuring device, and a comparator. A practical fractional order differential plus low-pass iterative learning approach is used to update the compensation for the next workpiece. An incremental order updating law is proposed for the fractional system order identification, which plays a fundamental role to optimize the performance of grinding process. Then the error compensated numerical control (NC) program is fed to the machine tool for subsequent grinding. Several illustrated results show the effectiveness of the above strategy.
Highlights
The role of batch processing is ever-increasing in today’s diversified manufacturing environment
Besides the fine or specialty chemicals, computer numerical control (CNC) precision grinding occupies an important position in batch production
This paper proposes an intelligent dimensional error compensation method using fractional order iterative learning strategy
Summary
The role of batch processing is ever-increasing in today’s diversified manufacturing environment. The authors in [13] proposed an intelligent dimensional error precompensation scheme for entire process without identifying any component In view of this idea and avoiding the difficulties of custom methods, a fractional order iterative learning compensator is put forward for dimension accuracy enhancement in this paper. This paper proposes a fractional order Dα plus low-pass iterative learning approach to identify the system order and compensate for dimensional errors in CNC batch grinding process. To obtain precise and accurate machined parts, the preprocessing scheme, which starts from analyzing initial NC program and results in error compensated NC code, is implemented By using this method, no sensor or model is needed. In this way, the dimensional precision of workpiece will be improved continuously
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