Placement Machine Setup Optimization for Electronics Assembly
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Solution Overview
Problem
Pick-and-place machines experience significant downtimes and increased production costs due to frequent changes in set-ups required for producing different assemblies, especially in electronics production with high variance and small batch sizes.
Innovation Solution
A method utilizing an electronic computing device to determine and optimize component sets for placement machines, creating combinations that minimize downtime by selecting the most efficient conversion kits for producing multiple assemblies without or with minimal changes, leveraging cloud computing for distributed processing and machine learning for efficient component placement.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Adaptability or versatility
If setup kits are changed frequently to produce different assemblies, then product variety is improved, but machine downtime increases
Solution Approach 1:
The system performs preliminary analysis of all required components for multiple assemblies and pre-calculates optimized setup kits before production. By determining the optimal component combinations in advance using computational algorithms, the system prepares setup configurations that can accommodate various assemblies, thereby reducing the frequency and duration of setup changes during actual production.
Solution Approach 2:
The patent creates universal setup kits that can serve multiple assembly types. By analyzing the component requirements of different assemblies and identifying common components, the system designs setup configurations that can be reused across multiple product variants, thereby reducing the need for frequent setup changes and minimizing machine downtime.
2Productivity
If setup kits are optimized for multiple assemblies, then machine utilization is improved, but setup kit complexity increases
Solution Approach 1:
The system segments the overall production requirements into multiple optimized setup kits, each tailored for specific combinations of assemblies. By dividing the component universe into logical groups that can be efficiently managed in separate setups, the system maintains manageable complexity while still achieving high machine utilization through strategic selection and rotation of different setup kits.
Solution Approach 2:
The patent implements a dynamic setup kit selection system that adapts to production requirements. Based on real-time factors such as assembly mix, quantity requirements, and component availability, the system dynamically determines which setup kit to use for each production batch, optimizing machine utilization without requiring a single overly complex universal setup.
3Ease of manufacture
If intuitive methods are used to create setup kits, then setup creation speed is improved, but production costs increase
Solution Approach 1:
The patent replaces manual, experience-based setup creation with an automated computational system. The electronic computing device automatically analyzes component requirements, generates optimized setup configurations, and determines production sequences, eliminating the need for manual setup planning while significantly reducing production costs through optimal resource utilization and minimized downtime.
Solution Approach 2:
The system performs self-optimization by automatically analyzing its own production requirements and generating optimal setup kits without external intervention. The computational algorithm independently evaluates all possible setup configurations and selects the most cost-effective options, enabling the system to improve its own efficiency without requiring continuous manual optimization.
Data Source
Figure 1
AI summary
The invention relates to a method for creating a setup set for at least one placement machine, wherein the placement machine serves to place components on/in assemblies, wherein in the method, by means of an electronic computing device, - for a multitude of different assemblies to be produced by means of the placement machine, the components required for the assemblies are determined, - possible setup sets for the placement machine are iteratively created from the determined components, wherein each setup set comprises several components, - an optimized setup set is selected from the setup sets.