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.
Collecting measurement and test data in manufacturing is vital for enhancing productivity and cutting costs. However, if key practices are not followed, resources can be wasted. To maximize the value of quality data, three essential actions must be taken.
In the fast-paced manufacturing industry, agility is vital for adapting to design changes. A centralized method for tracking modifications ensures team alignment, reduces miscommunication, and enhances productivity, fostering collaboration to keep up with innovation.
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.
AI is profoundly reshaping manufacturing, enabling businesses to achieve higher quality standards, greater operational efficiency and more imaginative resource utilization.
Unplanned downtime challenges manufacturers, but AI-powered predictive maintenance helps predict failures and reduce costs. A Deloitte study shows that 86% of executives view intelligent factory technologies as crucial for future competitiveness.
ERP systems have evolved to integrate key business functions and remain relevant, but their complex implementation requires effective planning for success.
As manufacturing quality demands grow, the shift to artificial intelligence (AI) presents an opportunity to streamline paper-intensive processes, reduce errors, and enhance product quality through better data integration.
While enjoying my Cheerios, I encountered a hard piece of plastic, dubbed a "quality escape." I reported this to General Mills, hoping for a thorough investigation, but received only a generic response with a coupon. I was left disappointed that my feedback didn’t prompt serious quality control actions.
Quality professionals are using statistical tools, originally meant for product quality control, to tackle climate change. For example, control charts that monitor manufacturing variations are now tracking energy consumption, identifying spikes, and measuring carbon emissions.
Embedded quality can enhance manufacturing strategies amid ongoing product failures and recalls. Discover why delivered quality is key to your organization’s success.