z = −1 + i' nα = θ + 2πk u = ρ (cosα + isinα) −x + 2y + z + t = −1 2x + 2y + z + 4t = 0 C = {z = x + iy x, y ∈ IR} z = −1 + i nα = θ + 2πk

Predictive Maintenance

More and more companies are collecting massive amounts of data to monitor the health of their products or processes, with the expectation that they should always be operating at peak performance.
Being able to recognize operating drifts and anticipate degradation and possible failures through data, is of paramount importance in order not to be left unprepared in the face of various unforeseen events that may occur (e.g. downtime, quality problems, or customers in trouble). It is also crucial for optimizing business planning and improving consumers' perception of the brand.

  • Description and benefits
  • Application examples
Always-on machinery
Increased sustainability
Costs and margins control

Application examples of Predictive Maintenace

Industrial
Transportation
Energy

Operating logic

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z = −1 + i nα = θ + 2πk u = ρ (cosα + isinα) f(x) = 3x − 2 z = r (cosθ + isinθ) ax + by + cz + d = 0 a (f(x + T) = f(x), ∀ x ∈ IR) (f(−x) = f(x), ∀ x ∈ D) 2x + 2y + z + 4t = 0

The solution for Candy-Haier