Retrofit used machines with IoT

IoT retrofit with open-source components

There is an understandable reluctance to investigate the Internet of Things among companies that fear they will need to eliminate obsolete machinery, retrain staff, or disturb or replace other assembly line equipment connected to it.

Retrofit used machines with IoT and additionally retrofit sensors that cost only hundreds of dollars are an affordable alternative that can allow these companies to access IIoT at moderate cost. They can keep machinery current while increasing operational efficiency and profitability.

Put simply, retrofitting is to add new functionalities or technological solutions to the old system. The goal of this approach is to minimize the negative impact on the continuity of business processes by increasing profits.
The retrofit of used machines with IoT is particularly important in sectors related to the operation of expensive equipment: automotive, chemical and food industries. Retrofitting is used where there is no economic reason to completely replace factory equipment. In many cases, it is sufficient to add sensors to the existing infrastructure to achieve performing results.

Retrofitted machine with iot

Laser cutting machines

At the beginning of the project, we found that the production times are not known in the current production process. Furthermore, the duration and causes of machine downtimes are unclear. The state of the art is as follows:

  • There is only a minimal connection of the machines to the ERP system
  • Manual entry of production data into the ERP system
  • Machine controls are partially blocked by manufacturers
  • Reliable planning of production and generation of offers is not possible

Finally, the preparation of the offer is carried out with theoretical reference times, as no actual information on the times is available.

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In this project we used vibration sensors and photocells.
The photocells are installed on the machines and are activated when the cutting head is lowered and in use. Used to measure machine condition, cycle times and number of parts. Vibration sensors are installed on the machine frame and detect the condition of the machine through vibrations.

iot visualization

Navigation is done through Grafana. The customizable menu allows you to quickly navigate between dashboards.

  • Dashboard for the plant manager/shift supervisor, which gives an overview of factory production
  • For each machine the current state of the machine
  • The overall effectiveness of the equipment / OEE for the selected period
  • A timeline showing the states of the machine
  • Overview of all orders including target / actual deviation and what reasons for downtime including setup times occurred during the order.