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Data is everywhere on today’s production lines. The challenge is that though manufacturers may be collecting large volumes of data, it often isn’t being used proactively or efficiently to solve day-to-day problems. Consider the following best practices to start making better use of your production line data. 

Paper-based data management and reporting workflows tend to limit the line’s capacity and scalability, and are prone to manual error. When these workflows start creating noticeable bottlenecks on your line, it’s time to look for a more streamlined solution. Learn more.

Data is everywhere in manufacturing plants and yet there are gaps in the ability to turn it into actionable information. These 7 questions will help you identify the data gaps holding you back.

A common quality issue at the weld station on a production line is expulsion, which can result in a weak weld joint. By applying process monitoring and digital process signature analysis, Sciemetric enables manufacturers to identify weld expulsion before the part leaves the station. Learn how.

Due to the circumstances of 2020, manufacturing budgets and timelines have been under an ever-increasing microscope. This sentiment certainly rings true when we looked back at the most-read content from our blog over 2020, where improving efficiency and effectiveness seem to be top-of-mind. Set your line up for success in 2021 with these tips from our most-read posts of 2020, here!

When manufacturers consider the concept of quality control on their production lines, they often think that a quality check station is enough. But what happens when a part fails the test? This blog post discusses how to improve product quality and line efficiency by going beyond station checks.

When we talk to manufacturers, sometimes we find that the difference between machine data and actual part production data has gone unnoticed. While both have their role to play, one is not a substitute for the other, as they don’t measure the same things. This blog post discusses the pros and cons of these different data systems to help you decide what's right for you.

Manufacturers often ask us how much data they need to keep, what data they should archive, and for how long. In this blog post, Sciemetric's Rob Plumridge discusses the factors to consider to ensure your data is working for you as part of your short-term and long-term strategies.

In this blog post, Sciemetric's Rob Plumbridge discusses what data you should be collecting on your production line, and what data is the most important to determine root cause when there is an issue with quality or throughput. Read the post to learn more.

Dispense is one of the most complex processes on the manufacturing line to monitor for quality assurance. This blog post discusses key considerations for identifying the correct parameters for effective defect detection.