Artificial intelligence (AI) is revolutionizing the industrial measurement field by enabling more precise automation processes, improving quality control, and promoting predictive maintenance. Future trends focus on further AI integration to create smart factories and highly efficient, flexible production systems.

Applying AI to industrial measurement

AI is integrated into measurement processes through various technologies and methods: 

• Automated quality controlComputer vision systems use deep learning algorithms to analyze product images, detecting defects with very high accuracy, sometimes up to 99,99%. This replaces costly and inefficient manual inspection.

• Predictive MaintenanceAI analyzes data from IoT (Internet of Things) sensors attached to machinery to predict when maintenance is needed, helping to minimize unplanned downtime and optimize equipment lifespan.

• Optimizing the production processBy processing large amounts of data from production lines, AI identifies complex correlations and suggests parameter adjustments to maximize efficiency and reduce material waste.
• Collaborative robots (Cobots)Intelligent robots equipped with AI are capable of learning and adapting to complex assembly tasks, working alongside humans safely and accurately.
• Big data analysisAI helps transform raw data from measurement devices into meaningful insights, supporting faster and more accurate decision-making. 

Trends in AI development in industrial measurement

The future of AI in industrial measurement is moving towards more intelligent and autonomous systems: 

• Extensive integration with IoT and Big Data.The combination of AI, IoT, and big data will create smart factories, where all measuring devices are connected and communicate seamlessly with each other, capable of self-adjusting in real time.
• Self-learning and adapting systemsAI models are increasingly capable of learning from new data without requiring detailed reprogramming, allowing measurement systems to adapt flexibly to fluctuations in production.
• Quantum precision measurementAlthough still in its early stages, the trend toward quantum precision in measurement will likely be supported by sophisticated AI algorithms for processing ultra-precise data.
• Sustainable developmentAI will play a crucial role in optimizing energy efficiency and reducing the environmental impact of industrial processes, contributing to a greener manufacturing environment.
• Enhancing cybersecurityAs measurement systems become more interconnected and data-driven, AI will also be used to detect and prevent potential cybersecurity threats. 

We can absolutely upgrade factories that are using outdated metering equipment to integrate new AI-powered systems. This process is often referred to as: digital transformation or industrial modernization.

This upgrade doesn't necessarily involve replacing all the hardware, but focuses on adding connectivity technologies and intelligent software to collect and analyze data.

Here are the main steps and methods:

1. Connectivity and Data Collection (IoT Gateway)

The first step is to make older devices "talk." This can be done through:

• Use retrofitting sensors.: Add external IoT sensors (e.g., vibration, temperature, sound sensors) to existing machinery to measure operating parameters that the original equipment cannot measure.
• Converters and GatewaysUse converters (e.g., from analog to digital signals, or from older protocols like Modbus to modern protocols like OPC UA or MQTT) and IoT gateway devices to collect data from the existing communication ports of older devices and send it to a central system.

2. Building a Data Platform

Raw data collected from older devices will be transferred to a centralized platform (cloud or on-premise). This platform is responsible for storing, pre-processing, and preparing the data for AI models.

3. Applying AI and Analytics

This is the core phase:

• Use analytical software.AI and machine learning algorithms will be applied to analyze data from older equipment. For example, analyzing vibration and temperature data can help predict when an engine is about to fail (predictive maintenance).
• Computer VisionInstall high-quality cameras and use AI software to inspect product quality on the old production line.

4. Integration and Visualization

The results of AI analysis will be integrated into existing management systems (e.g., SCADA, MES, ERP) and displayed on intuitive dashboards, making it easier for operators and managers to monitor and make decisions.

You can contact Semiki Instrumentation Co., Ltd. for consultation and discussion about AI-integrated measurement equipment solutions.

Semiki is the official distributor of precision measuring equipment from Japan and other international brands in Vietnam. SEMIKI offers a wide range of equipment for the mechanical, electronics, and medical industries. More importantly, Semiki has been and continues to implement technology-based solutions. Vision Camera Using software to detect, inspect, and alert for product defects in the production line is a core application of AI (specifically computer vision) in industrial measurement. 

SEMIKI MEASUREMENT EQUIPMENT COMPANY LIMITED

• Headquarters (Ho Chi Minh City): 12th Floor – Tower A2, Viettel Building, 285 Cach Mang Thang Tam Street, Hoa Hung Ward, District 10, Ho Chi Minh City, Vietnam.
• Hanoi Representative Office: 9th Floor, 3D Building, No. 3 Duy Tan Street, Cau Giay Ward, Hanoi.
• Phone (Hotline): +84 979761016.
• Email: [email protected]
• Website: You can find more detailed information about their products and solutions on Semiki website and send a request for a quote/consultation directly. 

When contacting them, you should clearly state your needs and that you are seeking solutions. Upgrading outdated measurement systems using AI technology. (for example, automated quality control camera solutions, integrated IoT sensors for predictive maintenance) so they can send the most suitable consultant.