Yokogawa Develops Process Data Analytics Software
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:
- Early detection of abnormalities in production processes
By detecting changes in production process data, this software can spot quality and productivity issues at an early stage of the manufacturing process. Based on this information, measures can then be taken to bring production operations back to a normal condition and recover quality. - Fail-proof quality inspection
By detecting changes in the data from production processes, this software can detect any sign of deteriorating quality and thereby catch any fault that might be overlooked in a conventional pre-shipment inspection. This can help quality assurance departments improve their quality inspection process. - Extensible via integration with MATLAB®*2
This software supports MATLAB, the widely used numerical analysis tool from MathWorks®. Custom MATLAB calculations can be integrated within the Process Data Analytics software to ensure the leveraging of unique business and domain knowledge. - High speed and accuracy through use of AngleTry Associates' proprietary technology
Thanks to the use of a pattern-recognition technology licensed from AngleTry Associates*3, this software delivers quick and accurate analyses. This technology is particularly useful with consulting and systems construction.
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
Комментарии