Cutting Fluid Timing Control via Machine Learning
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Solution Overview
Problem
Existing cutting fluid supply systems face delays that result in unnecessary fluid waste and increased power consumption, as they often supply fluid before actual cutting starts, and require additional hardware like check valves for mitigation, increasing costs.
Innovation Solution
A cutting fluid supply timing control device that uses machine learning to estimate and adjust the timing of fluid supply based on operating state data, eliminating the need for pre-programmed delays and reducing power consumption by optimizing motor usage.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If cutting fluid supply instruction is provided sufficiently before the start of cutting or cutting fluid is always supplied, then the delay in supplying cutting fluid is prevented, but cutting fluid is wasted and electric power consumption increases
Solution Approach 1:
The control device calculates the required advance time based on the distance between the cutting fluid supply device and the work position, then issues the supply instruction in advance by that calculated time. This preliminary action ensures the cutting fluid reaches the work position exactly when needed without unnecessary early supply, resolving the contradiction between supply reliability and energy waste.
2Reliability
If a check valve is provided near the injection nozzle to solve the delay in injecting working liquid, then the delay is mitigated to some degree, but the device complexity increases and maintenance cost increases
Solution Approach 1:
The invention replaces the mechanical check valve system with a control-based timing system. The control device calculates the required advance time and issues supply instructions accordingly, eliminating the need for physical check valves near the injection nozzle. This substitution reduces device complexity and maintenance requirements while achieving the same timing reliability.
3Reliability
If cutting fluid supply instruction is provided sufficiently before the start of cutting, then the delay in supplying cutting fluid is prevented, but cutting fluid is wasted before the work actually starts
Solution Approach 1:
The control device calculates the precise advance time required for cutting fluid to travel from the supply device to the work position, then issues the supply instruction exactly that much time before the cutting operation starts. This calculated preliminary action prevents both delay and waste by timing the supply perfectly.
Solution Approach 2:
The system dynamically adjusts the timing of cutting fluid supply based on the calculated distance and flow characteristics. Rather than using a fixed early supply time, the advance time is determined by the specific machine configuration and cutting conditions, optimizing both timing reliability and fluid efficiency.
Data Source
AI summary
A machine learning device included in a cutting fluid supply timing control device observes operating state data regarding an operating state of a cutting fluid supply device as a state variable representing a current environment state, acquires supply timing data indicating a timing of supplying a cutting fluid as label data, and then learns the operating state data and the supply timing data in association with each other by using these state variable and label data.