---
title: "23% OEE Increase in High-Speed Packaging"
description: "FMCG OEE Optimization Case Study: 23% OEE increase and 35% downtime reduction using HORUS Optimize and OEE Tracking."
url: "https://niotek.net/en/case-study/fmcg-oee-optimization"
language: "en"
---

INDUSTRY: FMCG APP: OEE OPTIMIZATION

# 44% Less Downtime. 16% Higher OEE.

## How a Multinational FMCG Manufacturer Stabilized Operations with Predictive TPM—without replacing legacy control systems.

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System Status

OEE Score 78%

Availability 92%

44%

Unplanned Downtime Reduction

+16%

OEE Increase

46%

Faster MTTR

90%+

Schedule Accuracy

### 01 // THE CHALLENGE

## When Every Minute Costs Money

In high-speed FMCG environments, efficiency margins are razor-thin. This facility operated multiple packaging lines where reactive maintenance was bleeding revenue.

#### Reactive Culture

Equipment degradation went unnoticed until sudden failures occurred, forcing emergency line stoppages.

#### Fragmented Data

Work orders and spare parts history were scattered across manual logs, limiting accountability.

#### The OEE Blind Spot

OEE was calculated retrospectively, masking real capacity losses and preventing proactive optimization.

### 02 // THE SOLUTION

## A Predictive TPM Command Center

Niotek deployed the HORUS TPM Module as a non-invasive operational intelligence layer.

01

#### Unified Maintenance Command

A centralized command center was established to track MTTR, MTBF, and task completion in real time. Maintenance teams now operate from a single source of truth.

02

#### Predictive Anomaly Detection

Equipment health is continuously monitored for wear. Maintenance teams receive early warnings, allowing interventions to be planned instead of rushed.

03

#### Automated TPM Workflows

Work orders are now triggered, assigned, and tracked systematically—eliminating manual errors and missed interventions.

### 03 // THE RESULTS

## From Chaos to Control

Within four months, the facility transitioned to a structured, predictive model.

DATA\_SOURCE: HORUS\_ANALYTICS

Metric Before HORUS After HORUS Impact Unplanned Downtime ~52 hrs / mo ~29 hrs / mo 44% Reduction OEE Score 62% 78% +16% Gain MTTR 2.4 hrs 1.3 hrs 46% Faster Schedule Accuracy ~40% 90%+ 2.25x Improvement

### TECHNICAL SPOTLIGHT

#### Zero Rewiring Integration

Connected directly to existing PLCs on packaging and filling lines without modifying core control logic.

#### Root Cause Analysis

Structured fault classification enabled faster diagnosis and repeat-failure elimination.

#### Cost Avoidance

Achieved 18–22% annual maintenance cost avoidance by extending asset life and eliminating emergency repairs.

> "Predictive maintenance isn't just about saving machines. It's about saving time."

This project proved that TPM excellence in FMCG does not require new machines or disruptive upgrades. By digitizing maintenance workflows, the manufacturer achieved a significant increase in OEE and reliability.

OEE\_CALC.EXE

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Potential gain to reach 85% OEE (world-class standard)