Items Tagged with 'data collection'

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.

When errors occur in manually entered data for project reports, it’s crucial to communicate with your supervisor and request more time to correct them. Acknowledging that mistakes happen, the priority should be on identifying and validating any unusual entries to ensure the report is reliable.

Nicholas Blake of Advex AI explains how synthetic examples can be used to help improve training models, what machine vision offers, and how AI inspection can cut training time down from years to hours.

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.

We are going to be dissecting six data integrity issues that require resolution prior to taking any further steps into the overall quality control process.

Are you throwing away a significant portion of your budget without realizing it? How often do engineers, scientists, and analysts regenerate knowledge work—solving problems or similar problems that have already been solved?

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.

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.

This month, I'm honored to speak at the ASQ Columbus (Ohio) Section’s annual conference on the theme "What is in Your Toolbox?" I'll discuss the seven basic quality tools I've extensively used over my 30+ years as a quality professional. Interestingly, unlike with my children, I do have a favorite among these tools.