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AI-Based Object Recognition for Efficient Maintenance

A Case Study with E.ON

A Case Study with


less errors


process time reduced


cost savings


E.ON is a German energy provider with a wide range of products and variations in the infrastructure they use. The company’s outdoor service employees and technicians need to check the network infrastructure annually, which is a tedious and timeconsuming process. Until recently, they used to document the condition of each network node, which consists of a cable distributor with NH fuses, with checklists and forms in paper form. This process takes a lot of time, and the complex specifications of each product cannot always be known in detail by every employee. Inefficiencies and quality losses were identified as a result of a lack of service expertise, process knowledge, and the right access to information, leading to unplanned outages, avoidable downtime, and resource consumption. Therefore, E.ON turned to Dropslab Technologies, an innovative tech company, to enhance their maintenance process.

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  • Greater efficiency and cost savings
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