Disassembling Sequence Optimization Using Simplified Swarm Algorithm
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Solution Overview
Problem
Conventional disassembling sequence planning methods, such as particle swarm optimization and artificial bee colony algorithms, are overly complex, leading to increased calculation time and reduced efficiency due to the handling of various data and variables.
Innovation Solution
A simplified swarm optimization method is introduced, which generates an initial disassembling sequence solution, updates it using a random probability mechanism, and calculates a minimal disassembling time through a fitness function to determine an optimal sequence, reducing computational complexity and enhancing planning efficiency.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Measurement precision
If conventional particle swarm optimization or artificial bee colony algorithms are used to plan disassembling sequence, then the optimal disassembling sequence can be found, but the calculation time increases and planning efficiency decreases due to complex data and variable handling
Solution Approach 1:
The patent changes the parameters of the optimization algorithm by using a simplified swarm optimization approach with fewer variables and data requirements. Instead of using complex algorithms like particle swarm optimization or artificial bee colony, the patent employs a streamlined method that maintains planning accuracy while significantly reducing calculation time through parameter simplification
Solution Approach 2:
The patent extracts only the essential elements needed for disassembling sequence optimization, removing unnecessary data and variables from conventional algorithms. By taking out only the critical components required for effective planning, the method reduces computational complexity while preserving the ability to find optimal sequences
2Adaptability or versatility
If conventional algorithms with multiple variables are used, then comprehensive planning can be achieved, but the device complexity and computational overhead increase
Solution Approach 1:
The patent extracts and retains only the essential variables and data elements required for effective disassembling sequence planning. By removing redundant or unnecessary components from conventional algorithms, the method achieves comprehensive planning capability with significantly reduced algorithmic complexity and lower computational overhead
Data Source
AI summary
A product disassembling method and non-transitory computer readable media thereof are provided. According to the components of the product and the disassembling attributes of the components, the disassembling sequence that minimizes the total disassembling time can be planned. The method includes the following steps: an initial disassembling sequence solution is randomly generated. The disassembling sequence solution is updated by using an update mechanism. The disassembling time of the update disassembling sequence solution is calculated by using a fitness function. The best fitness value is obtained after the continuously updating, so as to determine whether to update or maintain the initial disassembling sequence solution. The corresponding disassembling sequence is considered as the best planning result.