Smart maintenance for ecological progress with omis 4.0
Published on: Feb 12, 2025
Advertorial
What’s the size of our ecological footprint? For us the only answer can be: As small as possible!
omis supports petrol station networks in various ways to reduce their CO2 emissions and establish a sustainable, environmentally friendly maintenance strategy. This is realized e.g. through
- error reports of higher quality that lead to less drives of service providers or technicians and avoidance of multiple drives.
- In addition, users have the possibility to first go through a checklist before an error report is even created.
- Instructions, pictures, tips and tricks support the self-repair on site and can lead to less unnecessary drives of service providers.
- omis provides all relevant information in real time and mobile.
- In the case of an error, a service provider that is nearby can take care of the incident which saves additional and unnecessarily long drives.
- Information about distances etc. is available via Google Maps which enables service providers to optimize their routes.
- Moreover, reducing drives leads to a reduction of fine dust and traffic noise.
With just one mouse click omis provides an overview of all relevant data for devices and equipment. It also shows the number of repairs. Based on this, older and prone to failure equipment can be replaced by a new one that consumes less energy.
Another advantage of an early repair:
- Less spare parts must be produced and delivered.
- The plant operator is able to plan what he needs when and prevents additional, multiple drives of service technicians.
- omis also contributes to reducing or even preventing stand stills.
- One example: What happens if the car wash at a petrol station does not work? Either there is a long queue or the customers drive to the next station and produce additional CO2.
Currently, omis is intensively working on integrating AI in the software solution. This will extensively change the way maintenance is managed in firms. Thanks to AI, processes will not only be more efficient but also eco-friendlier. A key aspect are precise forecasts and smart analyses to significantly reduce service operations and improve the accuracy of error reports. It supports service technicians in optimizing maintenance jobs and actively encourages environmental protection through a reduction of resource consumption and emissions. The required technologies for implementing AI in the existing software are constantly developed further, APIs are established, and the necessary server structure is built. A feedback loop enables continuous improvement of the system to make it even more efficient and eco-friendly.
In the future omis aims at strategically implement AI to further reduce the ecological footprint. One possible approach can be prioritizing repairs. The data-driven decision making of our AI-system supports the choice between repair or replacement of components which again should lead to a longer lifetime of equipment and less waste. Another important aspect is pattern recognition. Long-term analyses conducted by the AI reveal trends and patterns that are critical for sustainable maintenance processes. Sustainability analyses represent another interesting chance for the future. Our AI should give users the possibility to evaluate ecological effects of maintenance processes precisely and therefore offer a basis for eco-friendly decisions.
omis’ engagement to use AI as an instrument for saving the environment shows how technology is able to drive forward positive change.
