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Environmental Monitoring System

Industrial IoT Case Study

How a Sail Loft Reduced Energy Costs in 30 Days, Achieving ROI in Just 5 Months

Table of Contents

This Industrial IoT case study demonstrates how data-driven monitoring and process optimization can deliver significant savings for companies.

The value of combining technology with strategic planning can be observed even in small, targeted, and data-informed interventions. By adhering to these principles, it is possible to achieve tangible improvements measurable in terms of efficiency, cost reduction, and higher quality standards.

THE CLIENT

A medium-sized Italian sail loft specializing in the production and repair of racing and cruising sails, with workshops for:

  • Thermal pressing and welding

  • Sewing and assembly

  • Technical fabric storage

The quality of their work depends on stable temperature and humidity to ensure:

  1. Proper adhesion of laminates

  2. Controlled fabric tension

  3. Minimization of deformation

THE OBJECTIVE

Reduce energy consumption while maintaining optimal conditions for production processes.

 

THE CHALLENGE

Before our intervention:

  • No continuous monitoring of environmental conditions

  • Manual and non-optimized use of heating and cooling systems

  • Systems switched on “by feel,” often prematurely or for longer than necessary

 

TECHNOLOGY IMPLEMENTED

We installed a real-time temperature and humidity monitoring system in:

  1. Pressing Area

  2. Macros Area

Data was collected and analyzed around the clock to map environmental conditions, identifying:

  • Time periods where natural cooling was sufficient

  • Peaks in humidity and temperature limited to certain hours

  • Differences between areas requiring localized adjustments

 

SOLUTIONS IMPLEMENTED

Based on the data collected, we were able to:

  1. Delay the start of cooling systems in cooler areas → fewer operating hours = lower energy consumption

  2. Activate humidifiers only when critical humidity thresholds were reached, avoiding continuous operation

  3. Schedule sensitive processes (e.g., pressing) during the most stable time windows (9:00–12:00)

 

RESULTS ACHIEVED (After 30 Days)

  1. 35% reduction in energy consumption for heating and cooling systems

  2. Improved process quality: fewer defects caused by thermal expansion or improper adhesion

  3. Enhanced operational control: managers now use data to plan shifts and production processes

  4. Return on Investment achieved in just 5 months from energy savings alone

Picture of Marco Tonsi
Marco Tonsi

Dopo un percorso maturato tra esperienze commerciali e imprenditoriali, fonda Automation-Kriz, software house specializzata nello sviluppo di soluzioni avanzate per il controllo di processo e l’innovazione tecnologica in ambito industriale. È esperto nello sviluppo in Python e C++, robotica, programmazione CNC, cloud e mobile development, oltre che in UX e testing.

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