Just-in-sequence (JIS) manufacturing is considered an evolution of just-in-time. It delivers the right parts to the right assembly line in the right order. Just-in-sequence is perfect for automotive manufacturing environments because production tends to be high-variety and low-volume.
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As industrial manufacturing companies looking for solutions knew that first and foremost, they needed greater visibility into their operations– especially real-time visibility. Instead of relying on unsatisfactory communications between machines and applications, they turned to integrating IIoT with their legacy systems.
With more sensors now existing on the planet than people, companies are looking for new ways to reduce latency and increase security in their IIoT data. The answer they’re finding? The “fog.”
It seems that IIoT is disrupting the industrial sector in the best way by guaranteeing these improvements, but the fact is that most companies are not correctly or effectively implementing IIoT. Because IIoT gathers huge amounts of quantitative, largely unstructured data through sensors, your current analytics system is likely to be overwhelmed. Luckily, you just need one key to unlock the treasures that IIoT data has to offer: artificial intelligence (AI).
Where do you start when you need to ensure that your manufacturing process runs as smoothly as possible without any surprises? Keep reading to learn how to calculate your process’ RPN (Risk Priority Number) and download our Process Failure Modes Effect Analysis template to start error-proofing your processes today.