ASRS Condition Monitoring for Predictive Vehicle Maintenance
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Solution Overview
Problem
Existing automated storage and retrieval systems face significant downtime and financial losses when container handling vehicles break down, as the entire system must be shut down for maintenance, affecting operations with hundreds of vehicles.
Innovation Solution
Implement a condition-based maintenance system using sensors and a centralized computer system to monitor and analyze the condition of system components, predicting maintenance needs and adjusting operations to prevent breakdowns, thereby minimizing downtime.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If traditional breakdown maintenance is used, then system complexity is low, but system downtime increases significantly when components fail
Solution Approach 1:
The system performs preliminary maintenance actions by monitoring component conditions and scheduling maintenance before actual breakdown occurs. Sensors continuously track parameters like temperature, vibration, and usage patterns, allowing the system to intervene proactively when degradation trends are detected, preventing complete failure and maintaining system availability.
Solution Approach 2:
The maintenance management system implements continuous feedback loops where sensor data from components is constantly analyzed, and maintenance decisions are adjusted based on real-time condition information. This feedback mechanism enables dynamic optimization of maintenance schedules, ensuring components are serviced at the optimal moment rather than following fixed intervals, thereby improving reliability without excessive complexity.
2Reliability
If the entire system is shut down for maintenance, then all components can be serviced, but productivity is severely reduced
Solution Approach 1:
The maintenance system is segmented to allow independent servicing of individual components or subsystems without requiring complete system shutdown. The monitoring and control functions are divided into modular units that can operate autonomously, enabling targeted maintenance on specific components while other parts of the system continue to function and maintain productivity.
Solution Approach 2:
The maintenance schedule is made dynamic rather than static, allowing the system to adapt maintenance timing based on real-time component conditions and current operational demands. When critical components require attention, the system dynamically adjusts maintenance windows to minimize impact on productivity, rather than enforcing blanket shutdowns that halt all operations.
3Reliability
If frequent maintenance is performed, then component reliability improves, but loss of time for maintenance operations increases
Solution Approach 1:
The system changes the parameters of maintenance frequency from fixed time intervals to condition-based thresholds. Instead of maintaining components on a rigid schedule, maintenance is triggered when specific parameter thresholds are reached (e.g., vibration levels, temperature ranges, cycle counts), allowing components to operate closer to their actual limits without compromising reliability, thereby reducing unnecessary maintenance time.
Solution Approach 2:
The system applies partial maintenance actions only to components that actually need them, rather than performing exhaustive maintenance on all components uniformly. By using condition monitoring to identify which specific components require attention, the system performs targeted partial maintenance instead of comprehensive system-wide maintenance, significantly reducing total maintenance time while maintaining necessary reliability levels.
Data Source
AI summary
A system for condition-based maintenance of an automated storage and retrieval system includes a framework structure with a rail system forming a three-dimensional storage grid structure for storing storage containers for storing items. The grid structure forms vertical storage columns each having a horizontal area defined by the size of an access opening between rails of the rail system that are arranged on the framework structure. The rail system provides available routes for container handling vehicles handling and transferring the storage containers to and from the storage columns. At least one container handling vehicle which has a container handling platform with a set of grippers for handling the storage containers. The grid structure includes one or more ports for extracting containers from the storage grid so that the storage containers can be picked and a service station for performing maintenance on the components of the storage and retrieval system. The system further includes a plurality of sensors configured to be attached to components of the storage and retrieval system for providing condition-based information linked to parts and components of the storage and retrieval system, a service regime manager configured to retrieve condition-based information from the plurality of sensors and create a service regime based on the condition-based information linked to parts and components of the storage and retrieval system and send the service regime to a local service station where condition-based maintenance is performed, and a central computer system. The central computer system is configured to: receive the condition-based information from the plurality of sensors and decide what information is to be sent to a global computer system that is part of the system for condition-based maintenance, and further sending only the information that can be of interest to other storage and retrieval systems. The global computer system is configured to receive the condition-based information from the central computer system and determine trends regarding component servicing or changing of components and further the global computer system transfers the information on the trend to the individual central computer system's service regime manager.