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Software Why Data Analysis is the Key to Production Quality

| Editor: Dominik Stephan

Yokogawa launches its new Process Data Analytics, an application program that can detect a decline in quality or productivity at an early stage by analyzing process data, facility status information, operation history, and other data.

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Process Data Analytics data display
Process Data Analytics data display
(Source: Yokogawa)

Used in combination with the company's analytical services, this software is a quality stabilization solution that can help to continuously improve the product quality. While working to quickly respond to a diverse array of market needs, manufacturers face a growing need to stabilize product quality. This is affected by factors such as fluctuations of raw materials and the aging of facilities.

To improve quality in each production process, manufacturers must analyze various types of data. As a solution to such challenges, Yokogawa began offering a process data analytical service in 2008 – To date, more than 100 contracts for this service have been concluded. Based on the insights gained, the company developed an analytical tool to improve its efficacy and thereby help its customers maintain and improve product quality.

Insights in Software Development

This software makes use of the Mahalanobis Taguchi (MT) method*1, a pattern-recognition technique that is employed in multivariate analysis. 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. The software 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.

Four Criteria for Data Analysis

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 Math Works. 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 Angle Try 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.

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