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Project - Data science

Performance Increase on a Production Line

The challenge

A key KPI for measuring line performance is called OEE (Overall Equipment Effectiveness).

On the production line studied, the OEE is calculated in real-time but reveals that it fluctuates significantly from one hour to the next and is ultimately unsatisfactory when its average value is checked. There are different teams involved: automation, quality, maintenance, laboratory, operators, and everyone has their own idea about the reasons for this fluctuation. Who is right ? What changes need to be made to achieve rapid (and inexpensive) improvement ?

The solution

All available data sources are inspected and the resulting Machine Learning analysis allows the ideas of the different teams to be objectified to rule out any potential misconceptions. In addition, possible solutions are listed and prioritised according to their direct impact and cost.

The potential gain

The OEE has a direct impact on the return on investment of the process. The solutions are chosen based on the potential increase in OEE assessed (using historical data) and how easy it is to implement. The OEE will then be increased step by step, as will the return on investment.

Project Details

Client Activity

  • Pharmaceutical industry

Solution Brand

  • Rockwell
  • FT metrics
  • Maximo
  • IBM
  • EBR
  • Electronic Batch Recording
  • Python

Nature of the work carried out

  • Resource Optimisation


  • Data Science Offline and Optimisation

Other references More to be discovered

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