Adaptive Control for Maintenance Estimation in Mounting Machines
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Solution Overview
Problem
Existing systems struggle to quickly detect and estimate maintenance requirements in control target devices, such as electronic-circuit-component mounting machines, often leading to reduced throughput and potential device failures due to inadequate maintenance timing.
Innovation Solution
An automated system with an adaptive control device that includes a controller, adaptive identifier, adaptive compensator, maintenance requirement detecting section, and portion-requiring-maintenance estimation section, which uses parameter estimation to detect and estimate maintenance needs, thereby enabling timely and precise maintenance.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional abnormality detection systems store past abnormality data and estimate causes based on stored data, then the system can provide maintenance guidance, but the detection speed is slow and cannot quickly identify maintenance requirements
Solution Approach 1:
The system performs preliminary estimation of device state parameters using the adaptive identifier before actual maintenance is needed. By continuously monitoring and estimating parameters like friction force and torque constants in advance, the system prepares maintenance information ahead of time, enabling rapid response when maintenance requirements arise without waiting for abnormality occurrence or manual inspection.
Solution Approach 2:
The invention replaces conventional mechanical abnormality detection methods (sensors, switches, manual inspection) with an information-processing-based adaptive control system. The adaptive identifier uses computational algorithms to estimate device state parameters from control commands and output data, substituting physical detection mechanisms with intelligent software-based parameter estimation, thereby achieving faster and more comprehensive monitoring.
2Reliability
If maintenance is performed frequently to prevent device failures, then reliability is improved, but productivity decreases due to increased downtime
Solution Approach 1:
The system performs preliminary assessment of device state parameters to predict maintenance requirements before actual failures occur. By estimating parameters such as friction force changes and torque constant variations in advance, the system enables proactive maintenance scheduling that prevents failures while minimizing unnecessary maintenance interruptions, thus balancing reliability and productivity.
Solution Approach 2:
The adaptive control system continuously monitors device operation by comparing actual output with expected performance, using feedback to update parameter estimates in real-time. This continuous feedback mechanism allows the system to detect gradual parameter changes indicating degradation, enabling maintenance to be performed precisely when needed rather than on fixed schedules, thereby optimizing the balance between reliability and productivity.
3Measurement precision
If the adaptive control system continuously monitors parameter changes to detect maintenance requirements, then detection accuracy is improved, but computational complexity and system complexity increase
Solution Approach 1:
The adaptive identifier performs multiple functions simultaneously: it estimates various device state parameters (friction force, torque constants, resonance frequency), monitors their changes over time, detects maintenance requirements, and provides diagnostic information. By consolidating these multiple functions into a single integrated information-processing system rather than separate dedicated systems for each function, the invention reduces overall system complexity while maintaining high detection accuracy.
Solution Approach 2:
The adaptive control system uses its own control commands and output data to estimate device state parameters without requiring external sensors or additional measurement equipment. The system serves itself by leveraging existing control loop information to monitor device health, eliminating the need for complex external monitoring infrastructure and reducing system complexity while maintaining accurate parameter estimation.
Data Source
AI summary
An automated system including a control target device and a control device which controls the control target device, in which it is possible to accurately estimate whether maintenance of the control target device is required and a portion requiring maintenance. The control device is an adaptive control device including a position control system, an adaptive identifier which estimates a parameter indicating a state of a control target device based on a control command and a control target output from the control target device, and an adaptive compensator which, based on the parameter which is estimated by the adaptive identifier, compensates the control command from the position control system to the control target device such that the control target device performs a planned operation regardless of a change in the parameter.