Yokogawa Releases New Software “Gas Chromatograph AI Maintenance Support”

Development Background

At production sites, the stable operation of instruments and other equipment is key to product quality. And while proper maintenance is required to ensure stable operation, production sites must also deal with issues such as shortages of highly experienced personnel and the need to streamline operations.

The Yokogawa GC8000 gas chromatograph is an instrument that plays an important quality control role at production sites by measuring the composition of the individual components in mixes of gases and volatile liquids. Dozens of GC8000s are often used at large oil and petrochemical plants, and the largest facilities may have several hundred units.

New Features

1.Data-based detection of measurement soundness
Slight changes shown in the chromatogram*3 data appear even before the wearing out of a component or some other issue begins to impact measurements. Though visible, they can have many different patterns, and their position on a time axis may differ depending on the instrument, meaning that only highly-experienced operators can distinguish between them.
2.Prediction of measurement soundness 90 days in advance
With chromatographs, gases are separated and measured on a time axis, and poor separation of the gas components impacts measurement quality. Using this degree of separation as an index, the GCAI tool can predict when maintenance will be required. Based on changes in the degree of separation, it can predict the degree of separation 90 days in advance, and provide notification when a predefined degree of separation is about to be reached. Knowing in advance when maintenance will be required makes it possible to identify which replacement components need to be ordered and to create an appropriate and effective maintenance plan for the instrument, thus helping to reduce downtime.
3.No need for consulting or complex device configuration

For the GCAI tool to automatically detect and record changes in the measurement data, users need only to set a reference date, area to be monitored, and notification threshold. This AI solution for predicting the soundness of measurements is easy to use and requires no special consulting or complex device configuration. The import and pre-processing of data used for machine learning is also automated. And as this software is offered on an annual subscription basis, users do not need to make a large initial investment.

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Yokogawa Releases New Software “Gas Chromatograph AI Maintenance Support”

Development Background

New Features