IIoT / Smart Manufacturing
7 production data gaps that are slowing down manufacturing engineers
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.
Monitoring for weld expulsion: A prime cause of weak welds, defects
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.
Set up your line for success in 2021: Lessons for improving product line efficiency and effectiveness
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!
Go beyond station checks to improve product quality and line efficiency: The value of process monitoring and data analytics
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.
Machine data versus part data: pros and cons | Manufacturing Data Series, Part 3
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.
How long should I store my manufacturing production data? | Manufacturing Data Series, Part 2
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.
What manufacturing data should I be collecting to improve part quality? | Manufacturing Data Series, Part 1
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.
10 considerations for effective defect detection during dispense operations
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.
The metric that could save you millions in manufacturing costs: The ROI of improving first time yield
In this post, we discuss the ROI investing in the improvement of your FTY results—including a case study which describes how we helped one manufacturer achieve over 3 million dollars in savings in one year by improving their FTY, decreasing their scrap and rework costs.
Continuously monitor and improve production using digital process signatures
This blog post discusses how digital process signatures can be employed when a new quality problem crops up in the field, to identify the root cause and enable continuous improvement on your production line.