Factories across continents are undergoing a transformation with the rise of Industry 4.0. New technological possibilities and data opportunities are laying the groundwork for reimagining nearly every aspect of traditional manufacturing – from production lines to the factory floor and supply chains.

The result is a smart factory, or Factory 4.0, with connected equipment, machines, systems and personnel designed to drive business value. Here we’ll take a closer look at what constitutes a smart factory, and the leading IoT use cases driving their adoption.

Smart Factory Benefits

The building blocks of a smart factory

At the most basic level, A smart factory is made up of a network of connected systems that collect, exchange and respond to data for increased productivity and efficiency.

There are dozens of ways to turn a factory ‘smart,’ from pre-packaged solutions to custom installation. But no matter how you approach implementation, these are the core features needed for a smart factory:

  1. Sensors data-collecting sensors installed in machines, workstations, and designated sites in the factory ecosystem such as the HVAC, security cameras or worker equipment
  2. Communication protocols the communication system that allows data to flow between the physical factory units and the cloud
  3. Cloud the data center for the factory, in which data is stored, processed and analyzed
  4. Analytics insights generated from system data for measuring performance, improving operational efficiency, and reducing downtime

The building blocks of the new factory - how a smart factory works

Why companies are turning to Smart Factory

Manufacturers are turning to Factory 4.0 to optimize production, reduce costs, and continually improve based on data insights. These are the leading IoT use cases for smart factory adoption:

Improving OEE (Overall Equipment Effectiveness)

Enhance operational efficiency with analytics-driven insights that enable root cause analysis of system issues, maximized asset performance, and increased productivity. Understanding machine output data allows OEMs to pinpoint changes required in manufacturing based on real-time availability, performance and quality.

Predictive maintenance 

Improve asset reliability and lower maintenance costs with analytics that monitor asset health and identify risks. Leveraging predictive maintenance analytics allows manufacturers to reduce downtime by getting automatic alerts of anomalies and optimized maintenance schedules to prevent machine failure. By locating system errors with data insights, manufacturers and their customers can greatly reduce the need for manual, preventative maintenance.

Remote asset monitoring

Gain visibility into the factory floor and control operations from anywhere and at any time. Manufacturers get alerts about the conditions of their machinery, equipment and the factory environment to continuously increase efficiency, maximize utilization, and improve compliance adherence.

Interested in exploring the power of industry 4.0 for your factory? Get a free demo of the Seebo IoT Development Platform to learn how.

Jackie Retig

Jackie is a technology expert, focusing on the Internet of Things and the ways in which our world is becoming more connected.