Per-Station Start Time Scheduler for Manufacturing Equipment Unavailability
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Solution Overview
Problem
Current scheduling methods, particularly in manufacturing, fail to effectively update search variables to reflect equipment unavailability due to changes in setup or status, limiting their capability in modeling complex situations where equipment is configured for one task type but needs to perform a different task.
Innovation Solution
The introduction of a station time constraint and a null-allowed search variable (NASV) to monitor and update the availability of manufacturing equipment, identifying which stations are unavailable to perform a task and the specific time intervals during which they are unavailable, allowing for dynamic scheduling adjustments.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If typical two search variables (equipment and start time) are used for each task, then the scheduling model is simple, but the capability to model equipment unavailability and configuration constraints is limited
Solution Approach 1:
The patent segments the scheduling model by introducing per-station start time variables for each station capable of performing a task. This breaks down the generic start time variable into station-specific variables, allowing the system to track and model equipment unavailability and configuration constraints at the individual station level, thereby enhancing adaptability without overwhelming complexity
Solution Approach 2:
The patent adds a new dimension to the scheduling model by incorporating station-specific start time variables alongside the existing equipment and start time variables. This dimensional expansion enables the model to capture equipment unavailability windows and configuration constraints that vary by station, transforming a two-variable model into a multi-dimensional constraint system
2Adaptability or versatility
If equipment setup changes for a task type, then equipment configuration adaptability improves, but the ability to update search variables to reflect unavailability becomes problematic
Solution Approach 1:
The patent implements feedback mechanisms where the scheduler monitors station status and equipment availability in real-time. When equipment setup changes occur, the system receives feedback about the new configuration state and automatically updates the per-station start time variables and constraints accordingly, ensuring search variable accuracy is maintained despite configuration flexibility
Solution Approach 2:
The patent makes the scheduling model dynamic by allowing per-station start time variables and constraints to be updated in response to changing equipment configurations. The system dynamically adjusts the search space and constraints based on current station availability and setup states, ensuring that search variable accuracy reflects the latest equipment configuration information
3Measurement precision
If multiple constraints are combined to identify unavailable stations, then scheduling accuracy improves, but computational complexity increases
Solution Approach 1:
The patent applies preliminary action by pre-calculating and establishing per-station start time constraints based on equipment availability windows and configuration requirements before the scheduling optimization process begins. This preliminary constraint setup reduces the computational burden during optimization while maintaining high accuracy in identifying unavailable stations, as the search space is already filtered and structured
Data Source
AI summary
A per-station start time scheduler identifies a station that is unavailable to perform a task over a time interval. The scheduler identifies a plurality of stations and a start time of a task. The scheduler monitors each of the plurality of stations using a station time constraint corresponding to the task. Upon detecting that a station is unavailable to perform a task over a time interval, the scheduler sends a notification specifying the station that is unavailable to perform the task.