Next Gen Quality Analytics

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Last month, we covered how quality engineers use control charts, capability analysis, and Pareto charts. In Part 2, we'll explore how they link these patterns to their underlying causes.

Quality engineers help manufacturing teams identify and resolve production issues through data analysis. They use statistical tools to uncover root causes and apply principles from methodologies like Six Sigma and Lean Manufacturing.

Luc Burgard, a leader in pharmaceutical manufacturing with experience in biotechnology and automotive sectors, highlights the importance of data analytics in strategic decision-making and shares insights on building specialized teams using Minitab.

Quality assurance professionals in manufacturing know that even a single non-conformance can result in rejected batches or regulatory violations. The Process Capability Index (Cpk) helps teams catch potential issues before they become costly problems.

Time series analysis enables manufacturers to track quality data, revealing patterns, trends, and anomalies to maintain consistent production standards. This method can be applied to daily production output or hourly quality measurements.

In the realm of quality control, utilizing predictive analytics through Minitab's tools can transform proactive quality management.

In the medical device industry, reliability is critical. Manufacturers conduct extensive testing to ensure devices meet required standards, such as 95/95 or 95/99 confidence and reliability, assessed using Minitab Statistical Software.

In manufacturing, operators, inspectors, engineers, and systems measure characteristics to ensure product quality. This data helps monitor real-time processes, tracking performance indicators like cycle time, throughput, and efficiency.

Process capability measures, such as Cpk and Ppk, measure how well your process is performing relative to your customer’s specifications. Let’s review some capability analysis basics and then delve into another capability estimate.

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