Agile Digital Transformation Solution for the Manufacturing and Production Industry

Pubilshed on August 25, 2020 From Vanessa Kluge

Step 1: Target analysis

In the first part, the target state and goals were determined. Why do the participants hope to benefit from a comprehensive service solution? What should the service portfolio during the machine life cycle look like? 
To this end, the participants were asked to evaluate the services during the machine life cycle from start-up, through operation and troubleshooting, to optimization, and finally recycling of the systems according to three categories: 

  • Improve
  • Offer anew
  • Not planned

In addition, a monitoring API was created for data scientists. The Python module was developed as a REST API wrapper to make the further processing of machine data with Python usable as a programming language in external AI tools. This serves as a basis for implementing predictive maintenance and use cases based on predictions made by AI.

This was followed by the presentation of the latest innovations such as the mobile version of EquipmentCloud® and the dashboard, which functions as a personal digital workplace. 

Existing challenges were taken as examples to show the workshop participants many practical solutions for digitizing services and improving service quality for their individual challenges. To expand your own service portfolio across the entire machine life cycle, the digital transformation solution EquipmentCloud® is the right platform for offering the proactive service of the future. 

Discover the advantages yourself with the practical test. Two machine manufacturers explain what proactive service means to them and how they have implemented this in practice. Find out more from the recorded webinar: Successful customer projects with RAMPF Production Systems & InnoLas Solutions.