Predictive Maintenance Scheduling for Cost and Downtime Tradeoffs
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Current maintenance scheduling systems fail to optimally minimize costs and prevent premature component replacement, as they do not consider the losses associated with early replacement and the availability of resources during unscheduled maintenance events.
Innovation Solution
A method and system that collect pre-emptive and preventive maintenance data, apply mathematical models to predict component failure times, and analyze this data to determine an optimal time for maintenance events that minimize total costs, considering factors like downtime, part availability, and resource constraints.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If components are replaced at scheduled maintenance intervals, then equipment reliability is maintained, but components may be replaced prematurely sacrificing their remaining useful life
Solution Approach 1:
The system changes the maintenance scheduling parameter from fixed time intervals to dynamic intervals based on predicted failure times. By continuously updating the schedule based on new failure predictions and comparing them with previously scheduled maintenance times, the system adjusts maintenance timing to occur just before actual failures, thereby maximizing component utilization while maintaining reliability.
2Loss of time
If multiple maintenance tasks are batched together during unscheduled maintenance, then downtime costs are reduced, but components may be replaced prematurely and resource availability may be compromised
Solution Approach 1:
The system introduces dynamic scheduling that adapts to changing conditions. Instead of static batching decisions, the system continuously evaluates new failure predictions against the current maintenance schedule and resource availability. This dynamic approach allows the schedule to be optimized in real-time, batching tasks only when it truly minimizes downtime without causing premature replacement, thereby resolving the contradiction between reducing downtime and preserving component value.
3Ease of operation
If maintenance is performed at fixed scheduled intervals, then planning is simplified, but unscheduled maintenance issues may increase costs by requiring additional equipment outages
Solution Approach 1:
The system implements a feedback mechanism where failure predictions are continuously monitored and fed back into the maintenance schedule. The system compares newly predicted failure times with previously scheduled maintenance times and adjusts the schedule accordingly. This feedback loop allows the system to maintain simplicity by automatically updating schedules based on actual component conditions, preventing additional unscheduled outages while keeping the planning process manageable through automated adjustments.
Data Source
AI summary
Systems and methods for scheduling maintenance of equipment include collecting pre-emptive maintenance data associated with a pre-emptive maintenance task associated with a component of equipment, collecting preventive maintenance data associated with a scheduled preventive maintenance task associated with the component or another component, applying a model to predict a failure time value associated with a future failure of the component, analyzing the data and the time value to determine an optimal time to perform a maintenance event, and using that optimal time to schedule the next maintenance event. Determining the optimal time includes minimizing a total cost of the maintenance.