Data Analytics for optimizing car wash systems.
Data and AI
Develop your business further with data analytics
From
Helena Schwenk, Vizepräsidentin des Chief Data & Analytics Office, Exasol AG | Translated by AI
The industry leader in car wash systems, WashTec, is increasingly using data analytics to optimize operations and service. This enables predictive maintenance, the provision of enhanced digital services, and further development in the area of machine learning.
(Image: WashTec)
Road salt, pollen or Sahara sand – whatever blurs the face of a vehicle, the car wash helps. On average, car owners in Germany wash their car every two months – with more than 65 million registered vehicles, that would amount to about 400 million visits. A considerable market, therefore, that the Augsburg-based company WashTec has been shaping decisively as an industry and innovation leader for decades.
Efficient data usage with AI support
Through its customer portal and several thousand car washes, the company has a huge amount of data (error messages, car washing processes or state parameters) – data that has been collected for years, but contains far more insights than the company has used so far. This is to change fundamentally, also to be able to offer digital services to operators or service technicians via the online platform, to further develop their own sustainability initiatives and the topic of machine learning.
To harness the full potential of its data treasure trove, WashTec has teamed up with Exasol and its high-performance solution Exasol Espresso to be able to quickly and efficiently analyze its data stored in the AWS cloud from over ten thousand car washes connected to the network, and to be able to connect the corresponding results. In order to be able to use the data quickly, for the past year at Washtec, data from various information resources has been loaded into the Exasol database via Data Virtuality Pipes. As an optional part of the latest AI offering, Data Virtuality Pipes is capable of automatically replicating data from hundreds of sources without coding and transferring it to the target, in this case the Exasol database as a SaaS solution.
Data extremely quickly available for analytical purposes
A decisive factor in the decision was above all the issue of performance or speed of data queries, because certain data is delivered every five minutes. This means collecting enormous amounts of data that continue to increase as more facilities are continuously connected – amounts of data that often overwhelm other solutions and lead to a massive reduction in query speed. These data are now extremely fast to access for analytical purposes – a critical criterion for both ML and BI use cases.
Data-based predictions instead of crystal ball gazing
Keyword ML use case – besides sustainability, one topic is particularly in focus for WashTec at the moment: Predictive Maintenance. Because stationary plants cost hard cash – and in the worst case make the customers visit another plant the next time. The possibility of predictive maintenance not only contributes to customer retention. If defective parts are replaced in time in the future, more severe damage can also be prevented in the worst case.
The advantages of a digitally-controlled car wash are diverse: WashTec benefits enormously from automated operation, as machine learning can be used in the washing process, for example, to control the water pressure, the use of cleaning agents, and the movement of brushes and drying procedures. Digital models can identify anomalies in the washing process, thus increasing safety and quality. Furthermore, machine learning supports optimized resource use, which in turn saves energy, minimizes waste and reduces operating costs.
Well prepared for future challenges
Data is now one of the central resources for further development and success at WashTec – not only in terms of value creation, but also the improvement of the customer journey and thus customer loyalty. Investing in technology that helps collect, store, analyze, and interpret data means securing the future – something that the current “AI and Analytics Report” emphasizes. According to this, 72% of all and 68% of German survey participants believe that a lack of investment in AI threatens future viability.
We know that the future of business lies in the smart use of data – anyone who misses the connection today is putting their future viability at risk. The investment in a future-proof data analytics solution like Exasol’s has already paid off for us today and offers enormous potential to continuously improve our offerings in the future.
Offerings such as the myWashTec customer portal are just the beginning of their digital journey. The company is consistently pursuing this path in order to drive forward topics such as machine learning, sustainability and the improvement of the (digital) customer journey – a step that requires both a clear corporate vision and the courage to change.
