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AI-Based Object Recognition for Efficient Maintenance

A Case Study with E.ON

A Case Study with

80

less errors

15

process time reduced

40

cost savings

INTRODUCTION

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.

Discover the Results

Unlock the power of innovative workforce management with Dropslab Technologies. Our platform, powered by AI and AR technologies, is designed to help industrial workers complete tasks with greater efficiency and effectiveness. Sign up today to get access to our latest case studies and learn how our solutions can transform your workforce. Our platform offers major benefits, including:

  • Shorter training times for faster onboarding
  • Reduce process errors to a minimum
  • Greater efficiency and cost savings
  • A competitive advantage that sets you apart

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