---
title: "Zero New Machines. 40% More Productivity."
description: "Case Study: How a zippers manufacturer achieved 40% productivity gain and eliminated 78% of micro-stoppages with Niotek."
url: "https://niotek.net/en/case-study/zippers-manufacturer-capacity-increase"
language: "en"
---

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.

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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.

### case-studies/case-zippers.solution\_header

## 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.

### case-studies/case-zippers.results\_header

## 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.