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Advanced applications of Artificial Intelligence in remote visual inspection.

Published: October 23, 2023

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Author: Inspector/Predictive Analyst. Jose G. Lopez M, October 23, 2023.

Introduction

Advanced applications of Artificial intelligence (AI) in the visual inspection Remote applications are extensive and are experiencing rapid advancement, providing innovative solutions for various industries. These applications have the potential to improve security, optimize costs, increase productivity, and generate valuable insights through visual data analysis.

The integration of AI into this assessment method allows for the development of sophisticated algorithms that can detect and recognize specific patterns, anomalies, and characteristics in captured images. These algorithms use machine learning and image processing techniques to accurately and efficiently analyze large volumes of visual data, providing fast and reliable results.

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AI can automate routine and repetitive tasks, reducing manual workload and minimizing the risk of human error in inspections. AI systems can perform real-time inspections , continuously monitor the quality of products or infrastructure, and alert about any deviations or problems detected.

In addition to operational benefits, AI in remote visual inspection can also generate valuable insights from the visual data collected. By analyzing patterns and trends, AI can provide insights and recommendations to optimize processes, improve product quality, and make informed decisions in real time ¹ .

Detection and classification of highly variable defects

Visual inspection is a crucial procedure in quality control that involves the evaluation of objects, materials or systems by using the human sense of sight.

This technique is used in various industries to ensure the accuracy, integrity and compliance of products or processes. During visual inspection, careful observation and evaluation of visual cues is carried out, such as color, shape, color, size and position of cracks, stains or spatters may have many differences and variations. Rule-based detection of these variable defects is complex. The AI is capable of filtering defects, classifying them and assessing whether a part to be inspected may be in good condition.

The final assessment can be performed by a rules-based system or a human inspector. By feeding the AI with the corrected ratings, it improves its ratings

AI-based remote visual inspection is the integration of artificial intelligence (AI) and computer vision technologies into the visual evaluation process of products or components. This novel approach enhances traditional visual inspection methods by using advanced algorithms, machine learning, and deep learning techniques to analyze images or videos for defects, irregularities, or specific attributes.

Using high-definition cameras, visual data is captured and processed and analyzed by AI algorithms trained on labeled data sets.

What are the benefits of using advanced Artificial Intelligence (AI) applications in remote visual inspection?

AI-based visual inspection offers a number of significant benefits compared to manual inspections. Its accuracy, consistency and efficiency are noticeably superior, as it can handle large volumes of data quickly and perform inspections at a much higher speed.

This technology is being widely used in various industries such as manufacturing, quality control, automotive, electronics, oil and gas industry, among others, to ensure that products meet established standards and specifications.

It is important to highlight that this technology represents a crucial advance in quality control processes, as it leverages the power of artificial intelligence to improve accuracy and streamline inspection tasks.

Additionally, its ability to quickly and accurately analyze visual data contributes to early defect detection, thereby reducing costs associated with defective products and improving customer satisfaction.

Real-world applications of remote visual inspection with AI.

AI-based remote visual inspection has found a wide range of applications in various industries due to its accuracy, speed, and ability to detect defects that might go unnoticed by the human eye. Some notable apps include:

Product Defect Detection: Through AI-powered automation, visual inspection allows for the accurate and efficient identification of defects in manufactured products. This ranges from cosmetic issues to misalignments, faulty welds or assembly errors, ensuring that only high-quality items reach the market.

Damage Detection: This AI-based technology is used to autonomously identify damage to equipment, structures or buildings. It can quickly detect surface cracks, dents, structural integrity issues and even water damage, facilitating quick maintenance and preventing further deterioration.

Corrosion monitoring and detection: In industries involving infrastructure, pipelines, storage tanks and vessels, this technology monitors corrosion levels. This helps identify the early stages of wear, allowing proactive maintenance and minimizing associated risks.

Advantages of advanced applications of AI in remote visual inspection.

Below are some advantages of this integrated inspection method ² .

It offers improved accuracy by surpassing human visual capabilities to detect even the smallest defects or irregularities.

Automated systems ensure consistent performance, independent of factors such as fatigue or external distractions, resulting in reliable and standardized results.

Furthermore, the data processing capacity of AI-based inspection is high, enabling rapid decision-making and efficient handling of large volumes of visual data in real time.

From an economic perspective, once AI visual inspection systems are configured, the need for extensive human involvement is reduced, resulting in greater profitability by minimizing labor costs and operating expenses.

Importance of applying visual tests .

Often overlooked in lists of non-destructive testing (NDT) methods, they are actually one of the most common and powerful approaches in this field. These tests require adequate surface illumination and an accurate view of the inspector.

Specialized training is essential to maximize the effectiveness of visual testing, including a thorough understanding of the product and process, anticipated service conditions, acceptance criteria, and proper records documentation.

Additionally, it is important to note that all defects found through other NDT methods must ultimately be verified by visual testing.

Visual tests can be classified into direct visual tests, remote visual tests and translucent visual tests.

Some of these systems even incorporate fiber optics to access very small access holes and channels. In addition, many of these systems allow the connection of a camera to make permanent recordings of the inspections carried out ³ .

What is the difference of AI-based remote visual inspection and traditional visual inspection?

Conventional visual inspection typically involves manual examination of defects and corrosion by human inspectors, which can be time-consuming and subject to error due to the difficulty of detecting all possible defects.

However, AI-based visual inspection offers precise automation. Artificial intelligence systems can analyze images or videos of products quickly and effectively, overcoming human limitations.

Conclusion

AI-based visual inspection has become a fundamental technological tool in various areas, improving the efficiency and accuracy of inspection processes. By allowing the timely detection of defects, damage and corrosion, it contributes to the improvement of product quality, the safety of structures and the optimization of maintenance processes.

Automated visual inspection represents an innovative alternative in the current era, as it completely eliminates the need for human intervention in the inspection process.

Through the use of automated systems, it is possible to greatly exceed the standards established by manual inspection. This cutting-edge technology enables precision and efficiency when performing visual inspections, resulting in a significant improvement in the quality and reliability of results.

By eliminating subjectivity and possible human errors, automated visual inspection is positioned as a surprising alternative that marks a milestone in the industry.