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Last updateSun, 04 Feb 2024 4am

Yokogawa develops Process Data Analytics Software for the Early Detection of Quality Issues

Yokogawa Electric Corporation announces that it has developed Process Data Analytics, an application program that can detect a decline in quality or productivity at an early stage of the manufacturing process by analyzing process data, facility status information, operation history, and other data. Used in combination with Yokogawa's analytical services, this software is a quality stabilization solution that can help companies stabilize and continuously improve the quality of their products. This software will be released for sale in March 2017.

While working to quickly respond to a diverse array of market needs, manufacturers face a growing need to stabilize the quality of the products coming off their production lines. Product quality is affected by factors such as fluctuations in the quality of raw materials and the aging of manufacturing facilities. Even when the raw materials supplied by different contractors vary in composition, the need to ensure high quality in the final product remains unchanged. To improve quality in each production process and thereby improve the quality of their final products, manufacturers must analyze various types of data. The effectiveness of such analysis has largely depended on the knowledge and expertise of the workers at each production site.

As a solution to such challenges, Yokogawa began offering a process data analytical service to its customers in 2008. To date, more than 100 contracts for this service have been concluded with companies in Japan's chemical industry and other industry sectors, and these companies have come to rely on this service.

Based on the insights that Yokogawa engineers gained by providing this service to their customers, the company developed an analytical tool to improve its efficacy and thereby help its customers maintain and improve product quality. This software makes use of the Mahalanobis Taguchi (MT) method*1, a pattern-recognition technique that is employed in multivariate analysis. The company is now preparing for the commercial release of this software.

Features of This Software

1. Early detection of abnormalities in production processes
2. Fail-proof quality inspection
3. Extensible via integration with MATLAB®*2
4. High speed and accuracy through use of AngleTry Associates' proprietary technology