Statistical Process Control for Power Plants

Statistical Process Control (SPC) is successfully used by manufacturing and service organizations to control processes. The advent of SPC has created significant improvements in manufacturing, and SPC is a key element in six sigma quality programs. The application of SPC allows trained professionals to analyze any process to better understand and control that process. SPC has been in steady use for decades, and numerous books have been written on its application. “SPC is a decision-making tool, and change is the foundation of SPC. When a process changes (goes beyond established limits), SPC helps the quality specialist identify the change and decide if the change is good or bad.” 1. “If the change is bad, the reason for the change is identified and every attempt is made to eliminate the occurrence of the cause of the change.” 2. “If the change is good, the reason for the change is identified and every attempt is made to make the occurrence of the cause of the change common practice.” [Statistical Quality Control, Seventh Edition] SPC may be applied to component and system monitoring at power plants. Equipment reliability, preventive maintenance effectiveness and plant aging have become more important to the owners and operators of power plants. These issues directly affect the plant’s capacity factor and operating costs. SPC provides feedback on measured process parameters, and power plants measure process parameters. SPC can be used to identify early indication of changes in these parameters. This allows plant personnel to identify performance changes that may be indicative of failing equipment reliability. Since it is a fairly simple tool, SPC is easily available to any power plant operator. Data can be loaded into Excel templates, and the appropriate graphs can be easily generated. Since many personnel are familiar with Excel, the application of SPC can be relatively easy initiate. Other statistical analysis programs are available (ex: EPRI MSET) for process parameter review. However, the other tools are not as simple as SPC. Examples will be provided that demonstrate how SPC can be applied to measured power plant parameters. These examples will also demonstrate how the results of SPC can be used to identify potential equipment reliability issues or to control parameters within narrow bands. Finally, the examples will demonstrate how SPC is superior to run graphs (i.e. a parameter graphed over time — over a “run”) as an analysis tool.