Next Generation SPC & Quality Analytics

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Statistical Process Control (SPC) is a data-driven methodology that uses statistical tools to monitor and control manufacturing processes. 

Unlike traditional inspection, which detects defects after production, the modern approach to minimize defects is data driven and proactive monitoring and control of the manufacturing process itself. Enter statistical process control (SPC).

Manufacturing decisions are only as good as the data behind them. 

Overall Equipment Effectiveness is arguably the #1 key performance indicator on manufacturing floors. 

In manufacturing, it’s tempting to assume that more machines mean more parts and higher throughput.

Statistical Process Control helps manufacturers move beyond defect detection by using real-time data to monitor variation, prevent quality issues and improve process performance before waste occurs.

Manufacturing teams often adjust process settings through trial and error. Engineers change one factor, observe the result, and repeat the process until performance improves. 

Quality professionals regularly prepare documentation for regulators, customers, and internal auditors. 

Quality teams feel constant pressure to act when something goes wrong. But reacting to every defect can create its own problems.

Twenty percent of every dollar spent in manufacturing is wasted, adding up to $8 trillion annually and contributing to 10% of global greenhouse gas emissions.