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Key Takeaways

You probably encounter predictive analytics every day in…


Key Takeaways

High production reliability needs a well executed asset performance management (APM) strategy. Industry 4.0 brings new technologies and a transformative approach to industrial productivity — a new mindset that can be applied to APM. Operational AI makes some of the most powerful, yet difficult to use parts of Industry 4.0 available to reliability and operations teams. …


Key Takeaways:

Space exploration and high reliability are synonymous. The reliability of probes and landers has come mainly because of massive design investment into reliability, including FMEA-driven component design, redundancy, remote monitoring and remote diagnostics. The same cannot be said about most other industrial segments, which struggle to universally make operational decisions based on quantitative data while being constrained by the technical limits of design…


Key Takeaways:

We have previously explained how software-defined reliability provides more flexible warnings of impending functional failures than do specialized hardware methods. In this post, we introduce another software-defined reliability technique that greatly enhances our ability to increase OEE without the need for additional instrumentation or capital investment. This technique…


Key Takeaways

Falkonry has added Event Horizon Estimation to its Operational AI suite. “Events” are behaviors of interest where the time until occurrence is important to know. We use this more general term because we have seen that, in addition to time to failure (TTF), operations teams try to…


Key takeaways:

It’s said analysis is only as good as the data. We put forth the corollary that data is only as useful as the analysis it can produce — the true test of the quality of data is the quality of insight that can be produced. Operational technology (OT)…


Oh if it were as simple as that!

“AI will Double your Cash Flow in 5–7 years”

“Smart Factories will realize 15–17% ProduIoT/IIoT pundits offer all kinds of value statements that’ll get your CFO chafing at the digital bit.

But manufacturing companies already on the digital journey know well how difficult it is to transform Mbps to M$.

In almost every case realizing value boils down to maximizing availability.

Take a real life example in heavy manufacturing: steel production.

Melting, moving, casting, and rolling metal is no easy task. Casting and milling are high-cost, long-term, capital intensive investments. These capital investments have physical maximum throughput. There are only so many metal molecules that can flow through a caster in an hour.

So how can the steel industry “double cash flow in…


Key Takeaways

The Industrial Internet of Things (IIoT) is not one simple thing. It is a system of systems:

“A system of systems (SoS) brings together a set of systems for a…


Key Takeaways

“Garbage in, garbage out” says that the quality of the output is only as good as the quality of the input. This is not a novel concept but it is of particular importance today where Machine Learning (ML) systems are expected to make trusted predictions and reliable detection of conditions; mistakes cost money. For example…


Key Takeaways

“In theory, there is no difference between theory and practice. But, in practice, there is”

— Benjamin Brewster (1882)

In theory, the problem with implementing predictive operations is finding a technically capable predictive analytics software package. It stands to reason — operations are running with the pieces already in place, so the challenge must be to measure the capability…

Falkonry

Falkonry enables predictive operations at scale for companies looking to achieve significant improvement in production uptime, quality and yield.

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