Paul Keller

A customer inquired about confidence intervals for capability indices, emphasizing their role in process capability reporting. The capability index, often represented by Cpk, estimates how well a process metric meets customer requirements.

In many production settings, machine operators are tasked with monitoring processes by taking samples and making adjustments as needed to maintain productivity. However, there's a question worth exploring: What if ignoring these data-driven adjustments and allowing the process to continue unchanged is a better strategy?

Real-time process management using SPC software has never been more cost-effective, providing substantial benefits by consistently meeting customer requirements with minimal labor expense.

An SPC (Statistical Process Control) Software customer recently inquired if I could discern any issues in a process, as their customer had identified problems with three recent shipments. They provided data for the customer’s current year shipments for a variety of KPI (key process indicators) in an Excel file. 

For most processes, we have a choice of measurement options that vary with cost. Ideally, we seek the most accurate measurement at the lowest cost with the expectation that the result will be satisfactory. When measurements are critical to operations, we should validate these assumptions.

Quality professionals see many costs of quality firsthand. These include our salaries and benefits, the equipment used to measure and analyze quality outcomes, and the waste generated by these processes when they fail to meet requirements.

Statistical process control (SPC) charts are used in quality-focused facilities to monitor process output on a continual basis and alert process operators, managers and the support staff in real-time when the process is shifting towards an undesirable condition.

Spending too much (time or money) on part disposition? Start with an analysis of your measurement system. Even a marginal measurement system could contribute up to 30% of the variation seen in your control chart.