Green Tyre Innerliner Coating Control with AI Weld Detection
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Solution Overview
Problem
Existing tire production methods struggle to ensure that the inner rubber weld of green tires remains free of coating during the painting process, leading to potential air leakage and reduced tire endurance due to inadequate whitewashing techniques, which rely on mechanical protection or manual inspection.
Innovation Solution
An AI-driven image processing system using neural networks for automated recognition of inner rubber welds and unpainted regions, employing a transition recognition neural network and a weld recognition neural network to detect deviations and ensure coating conformity.
Engineering Contradictions & Design Principles
Engineering Contradiction Analysis
1Reliability
If mechanical protection (adhesive tape) or manual inspection is used to protect the weld from coating, then the weld can be protected from coating, but the production efficiency is reduced and manual intervention is required
Solution Approach 1:
The patent replaces mechanical protection methods (adhesive tape) and manual inspection with an automated optical detection system using cameras and image processing algorithms. The system captures images of the tire inner surface, processes them through trained neural networks to identify the weld location and unpainted regions, and automatically controls the coating application. This substitution eliminates manual intervention and adhesive tape while maintaining reliable weld protection.
Solution Approach 2:
The patent implements preliminary detection and identification of the weld location and unpainted regions before the coating process begins. The image capture and processing occur upstream, allowing the system to pre-determine the exact boundaries that need protection. This preliminary action enables the coating system to automatically adjust and apply coating only to appropriate areas, avoiding the need for mechanical protection barriers and manual inspection during production.
2Reliability
If adhesive tape is used to mechanically protect the weld, then the weld is protected from coating, but the device complexity increases
Solution Approach 1:
The patent replaces the mechanical protection system (adhesive tape application and removal mechanisms) with an automated optical detection and control system. The system uses cameras to capture images, neural networks to process and interpret the images for weld and unpainted region identification, and automated controls to manage the coating process. This substitution reduces mechanical complexity while maintaining or improving protection reliability through intelligent automation.
Solution Approach 2:
The system performs self-service by automatically detecting the weld location, identifying unpainted regions, and controlling the coating application without requiring external mechanical protection barriers or manual intervention. The neural networks are trained to autonomously distinguish between areas that need coating and areas that must remain unpainted, enabling the system to protect the weld through intelligent control rather than physical barriers.
3Manufacturing precision
If manual inspection is used to ensure weld quality, then coating conformity can be verified, but the production speed is reduced
Solution Approach 1:
The patent replaces manual visual inspection with an automated optical inspection system using high-speed cameras and image processing. The system captures images of the tire inner surface and uses trained neural networks to rapidly analyze and verify coating conformity, including detecting the weld location and determining whether unpainted regions are correctly positioned. This automated inspection occurs at production speed without requiring human operators to slow down the line.
Solution Approach 2:
The patent implements continuous automated inspection throughout the coating process rather than intermittent manual checks. The image capture and processing systems operate continuously, providing real-time verification of coating conformity and enabling immediate detection of any deviations. This continuous automated monitoring maintains production speed while ensuring consistent quality verification that would be difficult to achieve with manual inspection.
4Ease of manufacture
If the painting process applies coating uniformly across the inner surface, then coating application is simplified, but the weld may be accidentally coated reducing airtightness
Solution Approach 1:
The patent implements preliminary detection and mapping of the weld location and unpainted regions before the coating process begins. The image capture and neural network processing occur upstream, creating a digital map of areas that must remain unpainted. This preliminary information is then used to control the coating application, allowing the system to simplify the coating process while automatically excluding the weld and unpainted regions from coating application, thus maintaining both simplicity and reliability.
Solution Approach 2:
The patent applies the principle of local quality by treating different regions of the tire inner surface differently based on their specific requirements. The system identifies the weld and unpainted regions and applies coating only to appropriate areas while leaving the weld and unpainted regions untouched. This localized control approach allows for simplified overall coating application while ensuring that critical areas receive the appropriate treatment to maintain airtightness and functionality.
Data Source
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AI summary
The invention relates to a method for controlling the coating quality of an innerliner (P ci) of a green tyre (PB) to which release agent has been applied. The method is implemented by at least one processor comprising a processing module which applies, to a deployed transition recognition neural network and a deployed weld recognition neural network, the data representative of the captured images of the innerliner; such that the conformity of the tyre is checked based on a predetermined abscissa deviation between the weld (Sp) of the innerliner and each of the edges (150A, 150B) that define a boundary of a profile of a region (150) of the innerliner to which no release agent has been applied, with an offset between the detected abscissa deviations and the predetermined abscissa deviation being denoted by a residual error between a prediction of the position of the boundaries of the profiles of the regions to which no release agent has been applied and the positioning of the weld, and a constructed automatic recognition model, such an error being indicative of a non-conformity in the application of release agent to the innerliner of the tyre.