Manufacturing Scheduling System Using Sensor Feedback
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Solution Overview
Problem
Current manufacturing environments face challenges in optimizing the scheduling of operators and resources due to variability in machine throughput, yield, and operator efficiency, leading to deviations from production estimates and inefficiencies in overall performance.
Innovation Solution
An integrated system for scheduling and simulation that automatically revises schedules based on real-time data from sensors, using an optimizer to generate schedules considering machine and operator availability, and a simulator to predict and evaluate manufacturing outcomes, allowing for continuous monitoring and adjustment to maintain production objectives.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual scheduling methods are used, then flexibility in handling variability is maintained, but manufacturing efficiency and productivity are reduced
Solution Approach 1:
The patent replaces manual scheduling mechanisms with an automated computer-based scheduling system that uses sensors, processors, and algorithms to generate and adjust schedules, thereby eliminating the need for manual intervention while improving manufacturing efficiency
Solution Approach 2:
The scheduling system automatically monitors machine throughput, yield, and operator efficiency through sensors and self-adjusts schedules without external intervention, enabling the system to serve itself in optimizing production parameters
2Adaptability or versatility
If fixed schedules are used, then planning simplicity is maintained, but adaptability to variability in machine throughput and operator efficiency deteriorates
Solution Approach 1:
The patent implements dynamic scheduling where the system continuously adjusts schedules based on real-time data from sensors monitoring machine throughput, yield, and operator efficiency, transforming static schedules into adaptive, living schedules that respond to changing conditions
Solution Approach 2:
The system incorporates feedback loops where sensors monitor production parameters, the processor analyzes the data against schedule performance, and adjustments are automatically made to improve adaptability while maintaining controlled complexity through structured feedback mechanisms
3Productivity
If real-time monitoring and automatic schedule revision are implemented, then manufacturing efficiency and adaptability are improved, but system complexity and computational requirements increase
Solution Approach 1:
The patent divides the scheduling system into modular components: sensor modules for data collection, processing modules for analysis, and execution modules for schedule adjustment, allowing independent optimization of each component while managing overall system complexity
Solution Approach 2:
The scheduling system is designed as a universal platform that can handle multiple machine types, operators, and production parameters through a single integrated system, reducing the need for multiple specialized systems and thereby managing complexity while improving throughput optimization
Data Source
AI summary
Methods, systems, computer program products, and articles of manufacture for managing a manufacturing environment are described. An optimized schedule for operators is generated based on an optimization data structure, the optimization data structure comprising one or more manufacturing objectives and one or more resource constraints. The manufacturing activity is simulated based on the generated optimized schedule and an initial state data structure, the initial state data structure comprising a representation of an initial state of the manufacturing environment. The simulation results are analyzed to, for example, determine if the manufacturing objectives are satisfied.