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Over the last 20 years at conferences, I've noticed many improvement posters rely on line and bar charts, which aren't always effective. While some use control charts and histograms, they often miss illustrating the "before and after" of improvements. It's crucial to better showcase these changes with appropriate chart types.

AHP Hydraulics, a Belgian solutions integrator known for delivering "smart solutions in hydraulics," faced a significant challenge from client SIDEM NV, which needed a more precise ball joint tester for its automotive suspension and steering units.

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.

PFÄFFIKON, Switzerland—AutoForm Engineering GmbH, a supplier of software for stamping and body-in-white (BiW) assembly processes, has released a new version of its AutoForm Forming R12 software. This version provides new capabilities and enhancements for the sheet metal forming process, in particular for the feasibility and validation phases of stamping processes.

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.

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.