Plastic Omnium Painting

Plastic Omnium

Plastic Omnium

Auto Parts

Auto Parts Paint Line Scheduling

Plastic Omnium is an automotive supplier that produces pre-assembled auto parts and then delivers them to the assembly line of the car manufacturer.

Providing a high customer service is a key factor for the company’s success: Plastic Omnium must produce under a mix of Make to Order and Just-In-Time for its automotive customers. With demands that should be satisfied within 5 hours, it is essential to have enough stock of semi-finished products (painted parts) and be able to react very quickly. This translates into a schedule of the paint line that gives the right priority to each product.

Enhance manufacturing scheduling to increase quality schedules and reduce time.

Plastic Omnium needed to enhance its scheduling capabilities. Besides improving its manufacturing KPIs, Plastic Omnium objective is to reduce the time to develop operational schedules in order to give more flexibility to its schedulers and generate better quality plans.
Manufacturing process involving 3 steps
The scheduling is part of the smart scheduling sub-project: The priority scope is the paintline process focused on integrated scheduling. Secondarily is the injection process, storage flows, and demand delivery.

Painting loop description process
DecisionBrain solution is designed to develop an optimal integrated scheduling between the injection and the paint lines to improve on operational KPIs:

  • Maximize Service level by respecting target production quantity before due date
  • Minimize color changes and paint loss
  • Minimize number of empty masts
Gant chart where the paint line variables and changes are schedule.
The pilot implementation delivered strong results along all these operational KPIs with a running time below two hours.Different scenarios were made by changing constraints and demands, and all delivered satisfactory results,, such as 48% improvement in the service level and 67% in capacity usage. The solution allows planners to adjust the schedule n depending on the KPI that needs to be optimized.
Pain line scheduling scenarios comparison KPIs

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