OXI-TWIN
Development of a digital twin and 4.0 platform for the digitalization of a water treatment plant.
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Implementation period
September 2020 – March 2021
Scope of work
Digital Technology
Participants
Ingeobrasinfo@ingeobras.com
Pirineos Metal pirineos@pirineosmetal.com
ZINNAEinfo@zinnae.org
Funding
This project has been funded by the national programe for clusters support “Ayudas a Agrupaciones Empresariales Innovadoras” (AEIs).
Description
Ingeobras and Pirineos Metal have combined their expertise in purification and digitalization to develop a water treatment system based on advanced oxidation processes. This system was connected to a 4.0 sensor-based management platform, which fed the CFD simulation system.
Objectives
Throughout the project, we have sought to ensure that the system can achieve:
- Diagnosis of the problem: It is possible to configure warnings when a problem is detected and receive them via Email, WhatsApp or in the most convenient way for the company.
- Predictive maintenance: It can prevent possible failures through learning from multiple sources.
- Automatic management of consumables: The system automatically warns of a future lack of consumables through a direct connection to ERP.
- Real-time data: Thanks to programming by functional blocks and high-level language.
- Remote management through different devices
- It can be switched off when not in use: By using advanced oxidation technology, it does not rely on live batteries to be maintained in the water treatment, and therefore, the system can be shut down when not in use, generating significant cost savings.
Results
OXI-TWIN has proven to be an efficient and effective system for purifying organic-rich wastewater. The use of advanced oxidation methods reduces the need to add consumables and saves purchase and storage costs. On the other hand, contrary to current bacterial beds, this treatment system can be turned off, which implies a saving in energy costs and can be continuously sensed. The use of sensors has made it possible to digitise the treatment plant, enabling remote control of the plant and predictive maintenance.
This data arrives in real-time and is automatically reflected in the server, which simultaneously sends the action to be taken to the plant.
This allows remote management through the mobile device (or similar), displaying real-time data that enables remote plant management and control of consumables. On the other hand, it also allows for diagnosing problems and predictive maintenance.
