z = −1 + i' nα = θ + 2πk ax + by + cz + d = 0 a (f(x + T) = f(x), ∀ x ∈ IR) (f(−x) = f(x), ∀ x ∈ D) 2x + 2y + z + 4t = 0 z = −1 + i u = ρ (cosα + isinα) x + by + cz + d = 0 a (f(x + T) = f(x), ∀ x ∈ IR) (f(−x) = f(x), ∀ x ∈ D) −x + 2y + z + t = −1 2x + 2y + z + 4t = 0 C = {z = x + iy x, y ∈ IR} z = −1 + i nα = θ + 2πk u = ρ (cosα + isinα) f(x) = 3x − 2 z = r (cosθ + isinθ) (f(−x) = f(x), ∀ x ∈ D) −x + 2y + z + t = −1 2x + 2y + z + 4t = 0 C = {z = x + iy x, y ∈ IR}

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z = −1 + i nα = θ + 2πk u = ρ (cosα + isinα) f(x) = 3x − 2 2x + 2y + z + 4t = 0 −x + 2y + z + t = −1 nα = θ + 2πk
best-match.svg

Best Match

Knowing how to respond to customers quickly and with a high degree of customization is a differentiating competitive factor.

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.svg

Predictive Maintenance

How to improve the planning of maintenance interventions, so as to limit the impact on production and improve the service offered to customers.

C = {z = x + iy x, y ∈ IR} 2x + 2y + z + 4t = 0 z = −1 + i nα = θ + 2πk −x + 2y + z + t = −1 a (f(x + T) = f(x), ∀ x ∈ IR) (f(−x) = f(x), ∀ x ∈ D) nα = θ + 2πk
workfore-scheduler.svg

Workforce Scheduler

Analyze different scenarios to find the one that best resolves the trade-off between costs and service level for scheduling staff schedules.

a (f(x + T) = f(x), ∀ x ∈ IR) (f(−x) = f(x), ∀ x ∈ D) −x + 2y + z + t = −1 2x + 2y + z + 4t = 0 C = {z = x + iy x, y ∈ IR} 2x + 2y + z + 4t = 0 nα = θ + 2πk −x + 2y + z + t = −1
real-time-monitoring.svg

Real Time Monitoring & Anomaly Detection

Monitor and anticipate phenomena that influence the evolution of a process or the life of a product.

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