Tokyo, Japan - October 6, 2016
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.
Process Data Analytics data display
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.
Process Data Analytics will run on Windows® PCs and will analyze production operations using temperature, pressure, flow rate, liquid level, and other process data as well as data on facility operations and equipment maintenance collected by a plant information management system (PIMS), DCS, or PLC. While data from such systems must normally be converted to CSV format for use in another program, data from Yokogawa's Exaquantum plant information management system can be used as is, without the need for file conversion.
Process Data Analytics will use the MT method for the analysis of multiple statistical variables. This will compare the collected data and accurately detect deviations from normal conditions. Any deviation will trigger a warning that quality may have deteriorated. By using the "four M" criteria of material, method, machine, and manpower to analyze process data, this software can visualize changes in production processes and thereby improve operations at manufacturing sites. Key benefits of this software are as follows:
Production quality control in the oil, petrochemical, chemical, pulp and paper, iron and steel, pharmaceutical, food, automobile, glass, rubber, electrical equipment/electronics, and other industries
Expanding our provision of advanced solutions for control applications is a high priority in the Transformation 2017 mid-term business plan. Yokogawa offers a variety of advanced software solutions that help manufacturers improve production efficiency, safety, and energy efficiency, and thereby make the most effective use of their production facilities. We will henceforth strive to expand our advanced solutions through the development of software and the pursuit of alliances, and will seek to accelerate growth for our customers by working with them to find solutions and create value.
*1 The MT method is a pattern-recognition technique. It is named after Dr. P.C. Mahalanobis, who introduced the Mahalanobis distance (a multivariate measurement scale based on the correlation among variables), and Dr. Genichi Taguchi, who was one of the key figures in the development of quality engineering. Based on the distance between reference data and sample data, this method can quantitatively determine the deviation from the target data.
*2 Please note that a license to use this product must be purchased.
*3 A consulting and MT systems development company that has sold over 500 licenses for pattern-recognition and other technologies mainly in Japan. The Japan Aerospace Exploration Agency (JAXA) has chosen AngleTry's technology for the autonomous inspection of its Epsilon rocket.
Yokogawa's global network of 92 companies spans 59 countries. Founded in 1915, the US$3.7 billion company engages in cutting-edge research and innovation. Yokogawa is active in the industrial automation and control (IA), test and measurement, and aviation and other businesses segments. The IA segment plays a vital role in a wide range of industries including oil, chemicals, natural gas, power, iron and steel, pulp and paper, pharmaceuticals, and food. For more information about Yokogawa, please visit www.yokogawa.com.
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Our Quality Analytics solution helps customers identify abnormal events and causes which may lead to poor quality products, utilizing a pattern recognition technology and the following steps: Identifies efficient/inefficient assets and high/low quality products by utilizing statistical analysis of historical process data, Identifies the root cause in the assets and products, Infers the state of asset and product quality on real time using the result of the analysis.