Equipment Scheduling System Using Segmented Time Prediction
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Solution Overview
Problem
Conventional data systems provide inaccurate predictions of the total time required for measurements, as they only show the core measurement time and may add an estimated preparation time, leading to uncertainty in when equipment will be available for new tasks.
Innovation Solution
A computing system determines the core processing time, pre-processing time, and post-processing time for equipment tasks, using historical data and machine learning algorithms to estimate the total processing time and display it to users, thereby improving the accuracy of equipment availability predictions.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Ease of operation
If conventional data systems only show core measurement time, then the system complexity is reduced and ease of operation is improved, but measurement precision of total time prediction deteriorates
Solution Approach 1:
The patent segments the total processing time into distinct components: core measurement time, pre-processing time, and post-processing time. This segmentation allows the system to maintain simplicity in displaying core measurement time while accurately predicting total time by summing the segmented components, thus resolving the contradiction between ease of operation and measurement precision.
Solution Approach 2:
The system performs preliminary actions by pre-calculating and storing pre-processing and post-processing times based on historical data and equipment state. These preliminary time estimates are then added to the core measurement time to provide accurate total time predictions without requiring complex real-time calculations, maintaining ease of operation while improving measurement precision.
2Measurement precision
If estimated preparation time is added to core measurement time, then measurement precision of total time prediction is improved, but reliability of equipment availability prediction deteriorates due to uncertainty
Solution Approach 1:
The system implements feedback mechanisms by continuously monitoring actual processing times and comparing them against predicted times. Historical data from these feedback loops is used to refine and update the pre-processing and post-processing time estimates, reducing uncertainty and improving the reliability of equipment availability predictions while maintaining measurement precision.
Solution Approach 2:
The patent applies dynamics by making the time estimates adaptive and responsive to changing conditions. The system dynamically adjusts pre-processing and post-processing time estimates based on real-time equipment state, historical performance data, and identified patterns, transforming static time predictions into dynamic, reliable forecasts that accurately reflect actual equipment availability.
3Measurement precision
If more comprehensive time factors are considered, then measurement precision of total processing time is improved, but device complexity increases
Solution Approach 1:
The system performs self-service by automatically collecting, storing, and processing historical time data without requiring manual input or complex user interaction. The computing system autonomously analyzes patterns, updates estimates, and refines predictions using its own accumulated data, improving measurement precision while keeping the user interface simple and avoiding unnecessary complexity.
Solution Approach 2:
The patent uses copying by creating a simplified model that replicates the essential time components (core measurement time, pre-processing time, post-processing time) without capturing every possible variable. This selective copying approach maintains measurement precision for practical purposes while avoiding the complexity of modeling every conceivable factor, achieving a balance between accuracy and simplicity.
Data Source
AI summary
Novel tools and techniques are provided for implementing optimized scheduling of tasks involving equipment used by multiple individuals. In various embodiments, a computing system might receive, from a first user, a first request to use first equipment that is disposed in a work environment, the first request comprising information regarding a first task to be performed using the first equipment. The computing system might determine a core processing time during which the requested first equipment performs core processes involved with performing the first task, might determine a pre-processing time and a post-processing time involved with performance of the first task. The computing system might determine an estimated total processing time to complete the first task using the first equipment, based on the determined core processing time, pre-processing time, and post-processing time. The computing system might display the estimated total processing time to complete the first task using the first equipment.