CASE STUDY
How did Nutricia gain control over its production plan and the availability of raw materials?
About the project
We implemented an advanced production planning system for Nutricia Poland, a leading baby food manufacturer and part of the global Danone Group. Nutricia operates one of the largest plants in the region, producing a wide range of products, including dairy items, semi-finished goods, and jarred pasteurized foods.
The project covered not only the manufacturing site but also external warehouses and cold storage facilities used to store raw materials such as vegetables and meat. The production process was multi-stage – from raw materials to semi-finished goods to final products – adding to the complexity of planning.
Challenges and Project Objectives
Production optimization
Reduce production time by minimizing machine changeovers and cleaning operations.
On-time delivery
Ensure timely order fulfillment through stable and efficient production planning.
Resource optimization
Improve the use of raw materials, packaging, and production capacity.
Production constraints
Incorporate restrictions related to allergens and natural colorants, which require frequent machine changeovers.
Complex production process
Multi-stage manufacturing had to support not only the Polish site but also other plants in the region without their own production capacity.
Frequent changeovers and cleaning
Adjusting production lines for allergens (e.g., milk proteins) and natural colorants caused downtime and disrupted scheduling.
Logistics limitations
Coordination between the factory, warehouse, and cold storage required precise transport and inventory planning.
Meat quality control
The production schedule had to align with inspections conducted by independent veterinary authorities, requiring synchronization with quality processes.
Our Approach and Solution
Changeover Matrices and Production Rules
We created a detailed changeover matrix accounting for key constraints like allergens and natural ingredients.
Rules were implemented to minimize changeovers between product batches, reducing downtime and cleaning frequency.
Implementation of SAP PP/DS
We used advanced heuristics in SAP PP/DS to generate optimal production schedules based on resource availability, capacity, and market demand.
Scheduling was integrated with inventory management in external warehouses and cold stores to optimize transport and raw material allocation.
Incorporating Key Production Parameters
Mechanisms were added to ensure minimum batch sizes and effective use of raw material units (e.g., big bags).
Balanced use of semi-finished products ensured uninterrupted production at the Polish site while supplying other regional plants.
Integration of Logistics Processes
We developed a production call-off system to streamline transport between storage sites and the production facility.
Integration with SAP SNP enabled smooth management of material flows and transportation schedules.
Key Outcomes
32%
reduction in machine changeovers, significantly shortening production time.
5%
increase in machine utilization for dairy products.
7%
increase in machine utilization for pasteurized jarred foods.
2 weeks
14-day stabilization of the production plan, improving raw material management and reducing inter-site transport needs.
Business Benefits
Reduced downtime
Fewer changeovers and cleaning cycles increased overall production efficiency.
Better resource utilization
Higher machine utilization rates enabled increased production in less time, leading to operational cost savings.
Greater Predictability
A stable production plan allowed for better inventory and supply chain management.
Compliance with quality standards
Processes met strict requirements related to allergens and raw materials, including external veterinary inspections.
Summary
The implementation of the advanced SAP PP/DS system, integrated with SAP SNP, enabled Nutricia Poland to fully optimize its production scheduling. A key success factor was the development of changeover matrices and production rules, which effectively minimized downtime while meeting critical allergen and raw material constraints.
Any questions?
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Luke Krukowski
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