Production Planning System Using Binary Variable Adjustment
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Solution Overview
Problem
Current supply chain management systems face inefficiencies due to complex interdependencies and connectivity within sites, leading to excessive resource usage and costs, as they struggle to manage internal and external factors in real-time, especially in large-scale networks with numerous nodes and products, making manual solutions impractical for optimizing production plans.
Innovation Solution
A computer-implemented method and system that generates real-time optimal production plans by processing input and infrastructure data to adjust binary variables, using sub-period and neighborhood optimization techniques, to minimize costs and maximize revenue, while considering changeover and inventory costs across multiple production processes and periods.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If manual solutions are used to manage supply chain production plans, then flexibility and adaptability are maintained, but productivity and real-time response capability deteriorate due to the inability to handle large-scale complex networks efficiently
Solution Approach 1:
The patent replaces manual mechanical problem-solving approaches with automated computer-based optimization algorithms. The system uses software to automatically generate and evaluate production plans across complex supply chain networks, substituting human analytical capabilities with computational algorithms that can process large-scale data in real-time while maintaining adaptability through programmable optimization criteria.
2Productivity
If computer-based optimization algorithms are used to generate production plans, then productivity and real-time response capability are improved, but device complexity increases due to the sophisticated algorithms and computing infrastructure required
Solution Approach 1:
The patent segments the complex optimization problem into manageable components by dividing the supply chain network into individual sites, production processes, and time periods. The algorithm processes each segment separately using structured data models and constraints, then integrates results to generate comprehensive production plans. This segmentation reduces computational complexity while maintaining real-time response capability.
3Manufacturing precision
If comprehensive data collection and analysis are performed across all supply chain nodes, then manufacturing precision and optimization accuracy are improved, but loss of time increases due to the extensive data processing required
Solution Approach 1:
The patent implements preliminary action by pre-structuring data collection frameworks and optimization models before actual production planning occurs. Data schemas, constraint definitions, and algorithm parameters are established in advance, allowing the system to rapidly process incoming data without extensive real-time analysis. This pre-preparation enables high optimization accuracy while minimizing data processing time during actual planning cycles.
Data Source
AI summary
Input data comprises a particular quantity of one or more finished goods to be produced over a time period. Software is programmed for: accessing infrastructure data that defines an infrastructure of a particular production facility; generating one or more sequence-dependent production plans comprising a particular sequence of one or more production process steps; calculating one or more optimized production plans for the time period by: determining a sub-period optimization plan for a first sub-period by adjusting one or more of a plurality of binary variables; generating a neighborhood optimization plan by adjusting one or more of the plurality of binary variables for a predefined neighborhood; and generating a particular optimized production plan for the time period by adjusting one or more of the plurality of binary variables; filtering the one or more optimized production plans based on one or more filtering criteria; and outputting the optimized production plans for display.