Equipment Operation Mode Control for Wear-Based Lifetime Balancing
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Solution Overview
Problem
Existing working equipment systems suffer from suboptimal performance due to heterogeneity in operating conditions, leading to either underutilization or premature wear of structural parts, resulting in poor return on investment and potential harm to external objects.
Innovation Solution
A system and method that uses data insights to quantify wear and strain on equipment, adjusting motion control parameters to match the specific operation with the expected technical lifetime, optimizing the balance between smoothness and time efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If global or default settings are applied to control equipment movement, then ease of operation is improved, but equipment lifetime is reduced due to high wear from heterogeneous operating conditions
Solution Approach 1:
The system dynamically adjusts motion control parameters based on real-time monitoring of operating conditions and equipment state. The control parameters are not fixed but adapt continuously to match current operational demands and equipment condition, resolving the contradiction between ease of operation and equipment lifetime by making the system responsive to actual conditions rather than relying on static default settings
Solution Approach 2:
The system implements a feedback mechanism where sensor data from the equipment is continuously monitored and fed back to the control unit. This feedback loop enables the system to detect deviations from optimal operating conditions and automatically adjust control parameters to prevent excessive wear, thereby extending equipment lifetime while maintaining ease of operation through automated adaptation
2Duration of action of stationary object
If motion control parameters are optimized for smoothness to reduce wear, then equipment lifetime is improved, but productivity decreases due to slower operations
Solution Approach 1:
The system dynamically optimizes motion control parameters by adjusting smoothness levels in real-time based on equipment condition and operational context. When equipment is in good condition, smoother movements are applied to reduce wear. When productivity demands increase or equipment condition allows, the system can safely increase operation speed, thereby balancing equipment lifetime extension with maintained or improved productivity
Solution Approach 2:
The system changes motion control parameters such as acceleration rates, velocity profiles, and damping coefficients based on monitored equipment state and operational requirements. By dynamically modifying these parameters, the system achieves smooth movements when needed to protect equipment while allowing faster operations when equipment condition and task requirements permit, thus resolving the contradiction between equipment lifetime and productivity
3Device complexity
If default operation modes are used across varying operational settings, then device complexity is reduced, but manufacturing precision deteriorates due to inability to account for heterogeneous conditions
Solution Approach 1:
The system performs self-adjustment of operation modes by automatically monitoring its own state and the operational environment. The equipment self-regulates motion control parameters based on sensor feedback without requiring complex external intervention or manual reconfiguration, thereby maintaining low device complexity while achieving high operational quality through autonomous adaptation to heterogeneous conditions
Solution Approach 2:
The system automatically changes operational parameters such as speed profiles, acceleration rates, and control gains based on monitored conditions including load, environment, and equipment state. This dynamic parameter adjustment enables the system to optimize operational quality for each specific condition without requiring complex pre-programming or manual intervention, resolving the contradiction between device complexity and operational quality
Data Source
AI summary
Working equipment system includes a working equipment, a control unit, a monitoring unit, and a processing unit. The monitoring unit is configured to receive a first data set including predefined equipment data, a second data set including operation data based on sensor signals, a unique identifier for the working equipment, and a time stamp for the second data set. The processing unit is configured to calculate a time series of wear indicator values based on the stored first and second data sets, to estimate a predicted lifetime of the working equipment by extrapolating the indicator values, to compare the predicted lifetime with a target lifetime, and to select an operation mode in dependence of the comparison such that the predicted lifetime corresponds to the target lifetime. The processing unit is configured to transmit the selected operation mode to the control unit that is configured to apply the selected operation mode.