Statistical process control (SPC) began as a tool when pencil and paper was the primary method. Originally, the benefits of these prevention vs. detection techniques were internally driven, but with today’s focus on supply chain improvement, greater accountability to external and internal stakeholders exists.
Technological advances in data collection and analysis allow for faster and more expansive SPC applications. If the analysis is based on flawed inputs, mistakes in applying SPC can magnify quickly and extensively, resulting in costly, flawed decisions for your organization. To avoid this, it is critical to ensure that the ways in which you are applying SPC techniques are correct.
This presentation will answer the following questions, focusing on the six areas in which mistakes are most commonly made in applying SPC and explaining how to prevent these mistakes in your organization: Am I using the right sigma? 2. Am I using adequate out-of-control tests? 3. Do I have enough data? 4. Do I have the right sampling plan? 5. Am I addressing non-normal data properly? 6. Is capability analysis premature?