Items Tagged with 'data analysis'

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.

The manufacturing industry is evolving due to Artificial Intelligence (AI) and robotics, significantly impacting job outlooks, as highlighted by the U.S. Bureau of Labor Statistics. This article will explore quality trends and provide guidance for future changes.

The manufacturing sector struggles with declining workforce experience as seasoned veterans retire and new operators lack the necessary skills. To address this, integrating predictive quality technologies and AI-driven recommendations can empower less experienced workers to achieve the quality and performance levels needed.

Traditional control charting techniques, despite their long history, can lead to wasteful outcomes due to certain mathematical properties. This article examines these issues using a Minitab dataset and introduces a free 30,000-foot-level metric-reporting app as an alternative, supported by Minitab analyses.

Compression testing is key in materials science for evaluating how materials respond to compressive loads. It helps determine mechanical properties like stiffness, strength, and fatigue life. This overview covers the testing process, material properties, standards, applications, challenges, and best practices.

In today's tech-driven world, companies use software to collect data, but the analysis can be flawed. Charts with only specification limits, arbitrarily chosen warning and action limits, and misused Process Behavior Charts contribute to misinterpretation.

While data mining can unearth a wealth of information, it takes discriminating analysis to make sure we are not just making connections, but the right connections.

Think ahead. Invest in your future. While this proverbial advice applies to all aspects of life, we will explore its relevance to young manufacturing businesses and their data management needs as they evolve from startups to market leaders.

Artificial intelligence has landed on our doorstep and will change the complete environment of data collection, data analysis, and real-time action. Not only has AI landed, but it is also here to stay, and parts can be used immediately.

Like a mad scientist turning the experiment on themselves, Renishaw used its own manufacturing operations as the proving ground for its new process control platform, Renishaw Central.