DISCRETE MANUFACTURING • CYCLE-TIME OPTIMIZATION

40% Higher Productivity.
Zero New Machines.

How a High-Volume Zippers Manufacturer Eliminated Breakdowns and Stabilized Cycle Time—with zero production downtime during deployment.

||
Production Status
Productivity Index +40%
Cycle Time Drift 0.2% (Stable)
+40%
Productivity Gain
ZERO
CapEx for Machines
100%
Proactive Maintenance
0 HRS
Deploy Downtime

01 // THE CHALLENGE

Reactive Firefighting

Operating in a high-volume, fast-paced discrete manufacturing environment, the factory struggled with chronic productivity losses and operational variability.

Run-to-Failure

Mechanical wear went undetected until components failed—triggering costly, unplanned downtime and emergency repairs.

No Cycle Visibility

Micro-stoppages and performance deviations were invisible until the end of the shift, making real-time intervention impossible.

Reporting Blindness

Reliance on handwritten logbooks prevented accurate root-cause analysis of bottlenecks and throughput instability.

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Non-Invasive Predictive Intelligence

Niotek deployed HORUS Predict as a high-frequency intelligence layer on top of existing control systems—without installing new sensors.

01

Predictive Analytics (No More Surprises)

Advanced analytics continuously monitored component health and performance drift. Maintenance teams now receive early warnings before failures occur.

02

Cycle-Time Optimization

High-frequency machine event data (stamping, cutting, assembly cycles) was captured to reveal micro-stoppages and station-level bottlenecks.

03

Real-Time OEE Visibility

Manual logbooks were fully replaced. A unified dashboard now calculates Availability, Performance, and Quality in real time—across all shifts and lines.

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From Reactive to Proactive

Within four months, the factory transitioned to a data-driven operating model—unlocking hidden capacity.

DATA_SOURCE: HORUS_PREDICT
Metric Before HORUS After HORUS Impact
Productivity Low Baseline +40% Higher Bottleneck Optimization
Maintenance Strategy Reactive (Fix-Fail) Proactive Fault Detection
Unplanned Downtime High / Frequent Significantly Reduced Early Warnings
Cycle Stability Untracked Measured & Stable Deviation Analysis

case-studies/case-zippers.tech_header

Discrete Mfg Focus

Analytics optimized specifically for high-speed stamping and assembly operations.

Non-Invasive

Connected directly to existing PLCs and counters with zero deployment downtime.

High-Freq Analytics

Real-time signal processing enabled instant detection of anomalies and performance drift.

Future-Ready

Machine-level digital models are ready for simulation and advanced optimization.

"We stopped fixing broken machines. We started preventing them from breaking."

This project demonstrated that predictive maintenance is the fastest, lowest-risk path to measurable ROI in brownfield discrete manufacturing.