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Predictive Maintenance Platform for Corrugated Manufacturing
  1. case
  2. Predictive Maintenance Platform for Corrugated Manufacturing

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Predictive Maintenance Platform for Corrugated Manufacturing

verytechnology.com
Manufacturing
Automotive
Aerospace

Predictive Maintenance Challenges in Corrugated Manufacturing

SUN Automation Group's customers in the corrugated manufacturing industry are facing challenges related to equipment downtime due to aging workforce and the need for proactive maintenance. Traditional maintenance approaches are reactive and inefficient, leading to production losses and increased operational costs. There's a lack of real-time insights into machine health and the ability to predict potential failures before they occur.

About the Client

A global leader in providing solutions for feeding, printing, and converting corrugated box plants, specializing in IoT solutions for industrial applications.

Project Objectives

  • Develop a predictive maintenance platform to reduce unplanned downtime in corrugated box plants.
  • Provide real-time insights into machine health and performance.
  • Enable proactive maintenance scheduling to optimize box plant productivity.
  • Offer a scalable and sustainable solution for monitoring machine health in the face of an aging workforce.
  • Provide SUN Automation Group with a competitive advantage in the market.

Functional Requirements

  • Real-time data collection from machine PLCs.
  • Anomaly detection algorithms for predictive maintenance.
  • Data visualization and reporting dashboards.
  • Alerting system for potential machine failures.
  • User management and access control.
  • Customer and machine management.
  • API for integration with other systems.
  • Historical data storage and analysis.

Preferred Technologies

AWS (Amazon Web Services)
Phoenix Framework
React
Elixir
Nerves
NervesHub
Terraform
AWS IoT
AWS Lambda
AWS Kinesis Firehose
AWS RDS
AWS S3

Integrations Required

  • PLC systems (via CIP over EtherNet/IP)
  • Existing SUN Automation Group systems (CRM, ERP - potential future integration)

Key Non-Functional Requirements

  • Scalability to support a large number of machines and users.
  • High availability and reliability.
  • Data security and privacy.
  • Real-time performance and low latency.
  • Secure API access.

Expected Business Impact

The implementation of this predictive maintenance platform is expected to significantly reduce unplanned downtime, leading to increased production output, lower maintenance costs, and improved customer satisfaction for SUN Automation Group's customers. It will also strengthen SUN's position as a leader in advanced manufacturing solutions.

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