AI-based predictive maintenance to reduce unplanned downtime of printing machines
Case Study
Objectives
The aim is to harness AI technology to develop a solution capable of detecting potential production downtimes in advance. This way, proactive measures can be initiated to prevent breakdowns or at the very least minimize their impact.
Solution
An AI-driven Predictive Maintenance solution was developed that evaluates the performance data of all HDM machines connected to the IoT Platform. By analyzing this data, the solution can identify potential production failures early on and notify customers in real-time. Furthermore, solution-oriented reports and evaluations are provided to customers to assist them in addressing the identified issues.
Results
Introducing the AI-driven Predictive Maintenance allowed customers to take proactive steps to prevent downtimes. If a breakdown is inevitable, they can detect it within minutes and adjust their production processes accordingly. Moreover, customers can now better align the need for consumables with any production delays, resulting in additional cost savings.
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Welcome, Carl Butler
We are delighted to welcome Carl Butler as a new partner at eStrategy Consulting. This adds more than 20 years of digitization experience for financial institutions, public authorities and software companies to our consulting expertise, especially for clients in the financial world and the public sector.
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