Networked real-time monitoring-oriented numerically-controlled machine tool machining process parameter acquiring method

Abstract

The invention relates to a networked real-time monitoring-oriented numerically-controlled machine tool machining process parameter acquiring method. According to the method, networked real-time monitoring of the machining states of multiple numerically-controlled machine tools with different control system types and different communication interface modes is achieved based on one server, real-time acquisition and recording of technological process parameters of FANUC, SIEMENS, HEIDENHAIN system machine tools can be achieved based on program names of NC programs and rules with a specific postprocessing format, and automatic transmission, storage and reusing of technological process parameters are achieved. The method is characterized in real-time performance, visibility, integrity, accuracy and the like. Real-time monitoring of the states of the numerically-controlled machine tools, full display of alarm number-based automatch alarm information and automatic transmission, storage and reusing of technological process parameters are achieved based on the spacecraft product numerically-controlled processing flow and the normalized numerically-controlled program format, and integrated application of a digital workshop information system is achieved on the basis.

Description

technical field [0001] The invention relates to a method for collecting parameters in the machining process of a numerically controlled machine tool oriented to networked real-time monitoring, and belongs to the technical field of digital manufacturing. Background technique [0002] In today's fierce global competition in the manufacturing industry, how to scientifically arrange production plans and maximize the utilization of manufacturing equipment is becoming more and more important. In addition, the improvement of process technology is often based on the statistical analysis of a large number of primary manufacturing site data in the process database, and the accurate acquisition of these data has always been a bottleneck problem. For a long time, the workshop has lacked an effective monitoring method. It mainly relies on traditional manual methods such as on-site inspections, telephone contact, and manual records to understand the operating conditions of machine tools. ...

AI Technical Summary

Problems solved by technology

[0005] (1) The image acquisition method stores a large amount of collected data, and most of the collected data is surface data, which cannot collect the internal operation information of the controller

[0006] (2) The existing collection methods have poor compatibility, cannot cover all CNC machine tools with different interface types of the control system, and cannot realize comprehensive and standardized management of workshop equipment

[0007] (3) Existing acquisition methods can only judge the running state of the machine tool only on the rotation of the spindle, and the judgment on other states is also relatively limited, and cannot be configured to adapt to different types of machine tool state judgment rules

[0008] (4) The existing acquisition method is based on API to read the alarm information of different machine tools, which is affected by the language environment of the CNC system, API system and operating system, and is prone to irreversible garbled characters

[0009] (5) The existing acquisition method cannot realize the real-time acquisition of the processing status information of the product (product code, program number, tool number, set spindle speed and feed, speed override, feed override and cutting processing time), The completion of the product processing plan cannot be evaluated in real time based on the collected data, and the integration between the collection system and the digital workshop information system is difficult

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