SPC (Statistical Process Control) What it is SPC is a statistical technique which compares current process output against a historical template. The template is usually based around a centre value with ± 3 standard measures of variation (of the characteristic being measured). The objective is to keep the current process stable, within these ± 3 control limits and to limit variation within them. Industry-standard rules are adopted: If data from the current process approaches these control limits or forms non-random patterns within the limits, then appropriate action to control the process is taken. No reference to specifications are made in SPC SPC was developed by Walter Shewhart and others, and many traditionalists refer to SPC charts as Shewhart charts SPC (Statistical Process Control) v1.ppt

SPC (Statistical Process Control) What it is Special causes act Common causes act UCL / LCL = Control Limits UCL LCL Centre Line The UCL/LCL is set by default at ± 3 standard measures of variation (of the characteristic being measured). Additional control limits can be added, but usually industry-standard rules apply. How to use it Detailed information regarding how to construct an SPC chart manually, how to run one in Minitab, how to select the correct SPC chart, and the main industry-standard rules are found in the aTQ training material referred to in the References. SPC (Statistical Process Control) v1.ppt

SPC (Statistical Process Control) Example Chart rules follow industry standards or adapt to suit Actions to follow if Rules are breached Standard Shewhart Control Factors, used to manually calculate centre lines and limits. Table for data collection SPC (Statistical Process Control) v1.ppt

SPC (Statistical Process Control) How it helps SPC charts must be seen alongside Process Capability graphs and indexes. References ASG aTQ training modules: 8.4, 8.5, 8.6, 8.7 : SPC (and non-SPC control) ASG “seniors” aTQ training module 1.5 : Capability SPC (Statistical Process Control) v1.ppt