Nonlinear Production Planning for Pressure-Balanced Device Utilization
Find Innovative SolutionsGenerate Solutions
Solution Overview
Problem
Conventional manual production planning methods in factories are time-consuming and inefficient, requiring 12 hours to arrange production plans based on experience and data, and existing systems fail to optimize production capacity effectively due to limitations in handling large volumes of production data.
Innovation Solution
A production programming system based on a nonlinear program model, utilizing a distributed storage device and analysis device with processors to acquire production data, construct a nonlinear program model, and solve for feasible solutions that optimize production programs across device sets, ensuring pressure equilibrium and process requirements.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Productivity
If manual analysis methods are used to arrange production plans, then production planning can be completed with existing data, but the process is very time-consuming (taking about 12 hours)
Solution Approach 1:
The patent replaces manual mechanical analysis methods with an automated computer-based system that uses nonlinear programming models and distributed storage devices to process production data and generate optimal production plans, dramatically reducing planning time from 12 hours to minutes
Solution Approach 2:
The system transforms production planning from a manual qualitative process to an automated quantitative optimization process by changing parameters such as using nonlinear objective functions, constraint conditions, and mathematical modeling to automatically determine optimal production quantities and schedules
2Productivity
If conventional systems are used for production planning, then existing production data can be processed, but they fail to optimize production capacity effectively due to limitations in handling large volumes of production data
Solution Approach 1:
The patent divides the production planning system into modular components including distributed storage devices for data management, nonlinear programming modules for optimization, and constraint condition modules for process requirements, allowing each component to handle specific aspects of large-scale production data independently
Solution Approach 2:
The system introduces nonlinear programming models and constraint condition frameworks as intermediaries between raw production data and production planning decisions, enabling effective optimization by transforming complex data into structured mathematical formulations that can be systematically processed
3Productivity
If production plans are arranged based on experience and conventional methods, then production can be scheduled using available data, but the method does not effectively optimize device utilization and pressure equilibrium
Solution Approach 1:
The patent transforms production planning from experience-based qualitative decisions to mathematically-driven quantitative optimization by introducing nonlinear objective functions that maximize device utilization and constraint conditions that ensure pressure equilibrium, changing the fundamental parameters of how production plans are determined
Solution Approach 2:
The system implements feedback mechanisms where the nonlinear programming model continuously evaluates production plans against constraint conditions and objective functions, adjusting production quantities and schedules to achieve optimal device utilization and pressure equilibrium across the manufacturing system
Data Source
Figure 1~2
Figure 3
Figure 4
AI summary
The present disclosure provides a production programming system based on a nonlinear program model, including: a distributed storage device and an analysis device, wherein the analysis device includes a processor configured to obtain production record information; construct the nonlinear program model based on the production record information; and solve the nonlinear program model to obtain first feasible solutions. The nonlinear program model includes a constraint condition that satisfies process requirements and an objective function indicating pressure equilibrium across the same device set, and each of the first feasible solutions is configured to indicate a production program. The present disclosure further provides a production programming method and a computer-readable storage medium which can improve efficiency and reduce device idleness rate.