CNC spindle signal investigation for the prediction of cutting tool health
CNC spindle signal investigation for the prediction of cutting tool health
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发表时间：
2018-07
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通讯作者：
Jacob L. Hill;P. Prickett;R. Grosvenor;Gareth Hankins
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作者：
Jacob L. Hill;P. Prickett;R. Grosvenor;Gareth Hankins
刀具的劣化在减法制造的进程中起着重要的作用，并对加工零件的质量产生很大影响。认识到这一点，大多数组织都实施了传统的工具管理方法。这减少了与时间相关和随机的刀具磨损相关的经济损失，并限制了刀具在使用寿命结束时造成的损坏。然而，仍有大量成本有待解决，更多地向工具和过程预测发展是可取的。作为回应，这项工作通过采集和处理选定的机器信号来调查工艺恶化。它利用了一个数控立式加工中心的内部处理器，并考虑了这种方法在预测刀具和过程健康方面的可能应用。本文考虑了工具和工艺条件的预测，并讨论了这些方法的假设、优点和局限性。此外，使用零件精度的离线测量和工艺变化的主动测量之间的相关性来测试该方法的有效性。
The deterioration of cutting tools plays a significant role in the progression of subtractive manufacturing and substantially affects the quality of machined parts. Recognising this most organisations have implemented conventional methods for tool management. These reduce the economic loss associated with time-dependent and stochastic tool wear, and limit the damage arising from tools at end-of life. However, significant costs still remain to be addressed and more development towards tool and process prognostics is desirable. In response, this work investigates process deterioration through the acquisition and processing of selected machine signals. This utilises the internal processor of a CNC Vertical Machining Centre and considers the possible applications of such an approach for the prediction of tool and process health. This paper considers the prediction of tool and process condition with a discussion of the assumptions, benefits, and limitations of such approaches. Furthermore, the efficacy of the approach is tested using the correlation between an offline measurement of part accuracy and an active measure of process variation.