How AI Transforms Cylinder Tracking and Lifecycle Management for Industrial Gas Companies

How AI Enhances Cylinder Tracking and Lifecycle Management

Artificial intelligence is changing how industrial gas companies handle cylinder management. New AI technologies improve registration accuracy, enhance traceability, and enable predictive maintenance. This shift addresses common challenges in cylinder lifecycle management, reducing errors and boosting operational efficiency.

TrackAbout, a tracking software specialist, and Datacor, a distribution software company, recently shared insights on applying AI to these challenges during a webinar. Their collaboration focuses on cutting down manual errors and increasing data integrity across cylinder management processes.

Smarter Registration with Visual Recognition

Elizabeth Wallace, Vice-President of Product at TrackAbout, explained how AI is integrated from the start to eliminate manual data entry. By using AI-driven visual recognition, the system captures accurate cylinder data from images, which serve as baseline records instead of relying on manual input of product codes or attributes.

Each cylinder carries data points like owner, manufacturer, barcode, valve details, serial number, weight, capacity, pressure, and standard. Automating data capture ensures the right information is recorded from day one, reducing the risk of errors that could affect downstream operations.

Wallace also pointed out that serial numbers are sometimes duplicated across different manufacturers. AI leverages historical data to identify duplicates and suggests the correct next steps, improving data quality and asset tracking.

Advanced AI Techniques for Accurate Data Capture

Lou Zhang, Senior Lead of Data Science at Datacor, detailed how their AI model uses deep learning and computer vision to read curved, embossed, and often worn cylinder markings from photographs. Training on tens of thousands of images allows the system to accurately identify serial numbers, retest dates, and other key details even under challenging conditions like poor lighting or cluttered backgrounds.

The software applies segmentation to isolate cylinders from backgrounds, then creates heat maps to locate text areas. This information is parsed into the correct data fields within TrackAbout’s platform. This approach can reduce manual workload and error rates by up to 90%, especially valuable for large distributors handling thousands or millions of cylinders.

Beyond Registration: AI for Maintenance and Compliance

AI is also used to assess cylinder condition by analyzing images for signs of wear such as oil stains, arc burns, or surface damage. This supports faster, data-driven maintenance decisions and lowers safety risks. These capabilities are available on rugged devices and smartphones, enabling real-time use by plant operators and field drivers.

Additionally, AI tracks cylinder movements to identify skipped lifecycle steps, like missed pickups or unrecorded deliveries, and automatically generates corrections or notifications. TrackAbout’s cloud-based software digitizes manual, paper-driven processes to improve accuracy and accountability.

Wallace emphasized that while the real world can be messy with missed scans or skipped steps, AI can detect and fix these issues while providing insights on why they occur and how to prevent them.

The Road Ahead: AI in Customer Portals and Forecasting

Looking forward, both Wallace and Zhang see AI integrated into customer-facing portals. These tools will allow users to generate reports, forecast demand, and interact with their data using natural language commands. The goal is to provide users with intuitive tools that deliver quick, actionable insights.

For managers interested in applying AI to asset tracking, predictive maintenance, or operational efficiency, exploring courses on AI applications in industry can be a practical step. Resources like Complete AI Training's latest AI courses offer valuable guidance on implementing such solutions effectively.

• AI eliminates manual data entry by using cylinder images for accurate registration.
• Deep learning models read complex cylinder markings even in poor conditions.
• AI analyzes cylinder condition to support proactive maintenance.
• Lifecycle tracking identifies missed steps and automates corrections.
• Future AI tools will enable intuitive data interaction and forecasting for customers.

By adopting AI-powered tracking and management systems, industrial gas companies can reduce errors, improve safety, and increase operational efficiency—key outcomes for any management team focused on performance and risk mitigation.