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August 24, 2007
SPC Based Manufacturing Analytics
The increase in the use of Business Intelligence and Business Analytics is paralleled by the development of Manufacturing Intelligence and Manufacturing Analytics. The desire is to integrate production data and analysis with business data and analysis, the goal is to develop a better understanding of complete corporate performance.
This new opportunity has created the need for analytical tools that can perform in this joint environment, and deliver to these goals. SPC methods rise well to this new opportunity in the form of SPC based Manufacturing Analytics.
SPC based Manufacturing Analytics is statistical and rule based, providing the aggregation, analysis and role-based visualization and reporting of manufacturing data that enables users to better understand and improve their processes, identify and reinforce best practices, react quickly to process events, and anticipate potential problems before they affect product quality, yield, or cost. The key differentiating elements of the SPC based Manufacturing Analytics methodology for analyzing data is;
- Statistically based
- Focused on role based analysis and reporting
- Identifies significant events, separating out “noise”
- Emphasis on visual presentation technique to enable quick analysis
- Supports both reactive and predictive behavior
- Easy enough to be implemented, maintained, and used by existing plant personnel
- Aggregates data from different sources while preserving statistical validity
- Supports the ISA S-95 Production Performance Analysis Activity Model, which outlines the need for robust systems, methodologies, and tools to improve the ability to make very informed decisions based upon extensive and varied analysis functions.
The result from merging business analytics and manufacturing analytics are value parameters used to monitor the overall status and performance of an operation or enterprise. These are expressed as Key Performance Indicators (KPIs), which are usually a single parameter consisting of an aggregation of financial, operational, and measured parameters to provide a meaningful and reliable KPI variable. These variables are often monitored for a “good” or “bad” status in some sort of web-based visualization tool, such as a portal or dashboard. The ability to contribute to or provision this web-based visualization function is a key component of the new analysis opportunity.
SPC based Manufacturing Analytics enable a system to be created that monitors the stability and change of all the parameter components contributing to the KPI, which allows the detection of a change in one key KPI component before the KPI itself shows to be out of range. The visual status presentation can then be displayed not as just a “good” (green) or “bad” (red) status, but also as a “potentially getting worse” (yellow) status. Existing KPI analysis and reporting systems do not have access to all the parameters or the ability to represent all the components in a process based context so that operations and management can quickly identify, or even predict, early signs of detrimental change to take appropriate action.
Posted by Jeffery Cawley at 2:30 PM | Comments (0)
