Rapid growth in electric vehicle sales along with an increasing interest in fuel-cell-electric powertrain systems presents the auto industry with serious and largely unanticipated quality-control issues.
The science behind 3D scanners and CMM technologies is different; however, both collect coordinate measurement data and are widely used within the plastics industry. When is it better suited to use non-contact structured light 3D scanners than touch CMMs?
Additive manufacturing produces parts layer by layer and this opens up an array of unique issues that can affect the integrity of a finished product, and also a unique set of surface characteristics that make the job of measuring and validating that much more difficult.
As the pendulum swings from past decades of customized PLM to a far more flexible, highly-configured version, organizations need to borrow a page from modern software development and embrace automated testing as part of routine deployment.
Disruptions to your testing program can result in delayed shipments, upset customers, and lost revenue. For this reason, it is crucial to ensure that measures are being taken to prevent system downtime when planning the introduction or evolution of your testing program.
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Control charts should be implemented carefully. Here are best practices to keep in mind.
July 13, 2022
The Xbar/R Control Chart is a method of Statistical Process Control (SPC) manufacturers can use to reduce fill weight variation, maintain centerlines and avoid rework. Here are best practices to keep in mind:
Magnetic measurements are suitable to determine mechanical and technical properties of a material especially steel. The magnetic and mechanical properties of a material are determined by the microstructure.
The purpose of this article is not to review all techniques, but to discuss particularly the application of hardness testing to coatings, typical techniques used, best practices and special considerations to ensure accurate and repeatable results.
Fatigue testing is unique in that it repeatedly exposes parts to “real-world” conditions, producing data and results that helps manufacturers predict the part’s durability.