We offer the ideal solutions for digitizing the supply chain of the pharmaceutical and cosmetics industry. And we can prove it.

Expensive stocks, restrictions and endless cleaning.

In a very complex and specialized productive environment, the pharmaceutical and cosmetics industry requires good production planning and programming, whether in synchronism between processes and traceability of lots either in inventory balancing.

Company in the segment served:

Neo supports all the planning of its supply chain, from the long to the short term, treating industry characteristics, such as resource restrictions and labor by product type, filling synchronization with filling, perishable, production campaigns and inventory segmentation.

We are a
technology consulting firm specializing in
Supply Chain Planning and Production Scheduling.

Meet Opcenter APS

We’re one of Siemens’ largest Planning & Scheduling partners in the Americas and a certified Smart Expert. With Opcenter APS, the world’s leading software, we help you balance demand and capacity to achieve optimized production planning and scheduling.

Meet NPLAN

NPLAN is an innovative advanced planning platform for productive scenarios developed by Neo, which emerged with the mission of revolutionizing the digital acceleration of the supply chain. Generate your production planning scenarios agile, reliable and collaboratively.

Meet Evocon

Simple and agile, scan your factory data and optimize your equipment performance to the fullest. Evocon is a combination of IoT and plug-in-play software to help understand your factory's behavior easily and intuitively.

Meet Ax4

AX4 is a logistics management software developed by Siemens Digital Logistics to optimize and simplify logistics management. Combining advanced technology and a customer -centered approach, AX4 offers an efficient way to manage transportation operations, supplier deliveries, dock management, freight payments and more.

The key challenges for the textile industry:

Demand Variation

High sensitivity to demand forecasting errors combined with difficulty in predicting demand.

Leveling of resources

Complexity with line allocation alternatives, cleanouts, setups, and labor.

Batch Traceability

Identify that lots will be produced, consumed and supplied along the chain for better traceability, respecting lot sizes and approved restrictions with ANVISA.

Synchronism between processes

Complex dynamics to synchronize intermediate material manufacturing and finished filling.

What to expect:

Inventory reduction

With more balanced planning and scheduling, inventory health improves, lowering finished goods inventory and better synchronizing raw material purchases. The solution’s agility also enables rapid responses to demand changes, helping to avoid unnecessary inventory and losses due to perishability.

Increased productivity

Scheduling rules will group similar items, with mesformulation or packaging type, reducing setup times that do not add value. Better synchronization allows for reduced waiting times, generating more value directly for the product and making better use of company assets.

Reduced disruptions

Enhanced visibility, faster scheduling, and more accurate planning help reduce delays and stockouts by identifying issues in advance. This allows for simulations to take preventive actions and eliminate problems— all within scenarios that ensure product availability without compromising service levels.

More agility

Replanning is even more challenging than planning. A machine breakdown, rework on a component, or a change in demand for an item can create a cascading effect that requires rescheduling the entire plant. Responding quickly with a solid plan allows your team to focus on analysis and decision-making rather than just operational firefighting.

Increase your service level and customer satisfaction by more than 50%.

How Siemens Opcenter increased Incepa's customer service by 81%

Increase your service level and customer satisfaction by more than 50%.

How America Tampas became a benchmark in automated production scheduling.