Artificial Intelligence and Machine Learning

 AI and Machine Learning for adaptive planning, more accurate forecasts, and automation of repetitive tasks. 

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AI & ML

Constant fluctuations in demand require companies to be able to respond quickly; whether these fluctuations stem from new business opportunities, inventory optimization, or changing customer needs, the goal is to respond swiftly while minimizing the impact on production costs.  Operating within an extended, digital supply chain enables full visibility into all the parties involved in the process. For sedApta, this is just part of the solution.

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Results that make planning smarter

Artificial Intelligence and machine learning make planning faster, more accurate, and more flexible, improving forecasts and reducing manual work through advanced data analysis.

Greater forecast accuracy

The integration of artificial intelligence and machine learning enables the analysis of large amounts of historical and real-time data to accurately predict future scenarios. This results in more reliable forecasts than traditional methods, reducing errors and discrepancies in production and demand plans.

Adaptive planning

Smart solutions do more than just generate static forecasts; they continuously adapt plans to changing operational and market conditions. In practice, the system can automatically recalculate scenarios and recommendations based on new data, enabling faster and more responsive decisions in dynamic environments.

More accurate forecasts

Thanks to advanced machine learning models and “what-if” simulations, forecasts are not only more accurate but also better tailored to different possible scenarios. This allows you to evaluate alternatives, anticipate potential issues, and optimize resources and inventory with greater confidence.

Reduction in manual labor

Intelligent automation eliminates many repetitive and labor-intensive tasks, freeing up time for people to focus on strategic analysis and high-value decisions. AI analyzes complex data, suggests actions, and reduces the need for manual intervention in day-to-day planning.

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Today, thanks to a strategic partnership with Elisa IndustrIQ, a leading company in the fields of Artificial Intelligence and machine learning algorithms, sedApta is able to help industry leaders identify, predict, and prevent process inefficiencies by transforming data into actionable insights.

sedApta’s orchestrated processes are enhanced by the introduction of a new digital professional role: LUMI Virtual Manager. By leveraging machine learning algorithms and a set of predefined KPIs, this system is capable of independently analyzing and interpreting the available data, rapidly evaluating all possible scenarios, identifying the solutions with the lowest impact from among the various alternatives, and providing the other stakeholders in the process with a subset of carefully selected scenarios.

Digital twins, orchestrated processes, Analytics Bricks, and the Simulation Control Tower are the core components of the sedApta platform that enable the synchronization and coordination of all process stakeholders, providing them with exactly the information they need, at the right time, to efficiently carry out a specific process activity.

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Digital twins, orchestrated processes, Analytics Bricks, and the Simulation Control Tower are the core components of the sedApta platform that enable the synchronization and coordination of all process stakeholders, providing them with exactly the information they need, at the right time, to efficiently carry out a specific process activity.

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How sedApta's AI and ML Turn Data into Decisions

  • Predictive analytics: Anticipate demand, requirements, and supply chain issues by analyzing historical, seasonal, and market variables in real time.
  • Prescriptive recommendations: The system does more than just flag a problem; it recommends the most effective action to take, along with an estimate of the expected impact.
  • Pattern recognition: Identifies recurring patterns in production and demand data that traditional analysis misses, even with large volumes.
  • Anomaly detection: Detects significant deviations from expected models and brings them to attention before they propagate throughout the supply chain.
  • Self-learning models: automatically update themselves with new data. The more they are used, the more accurate they become: no periodic manual calibration required.
  • Cross-module integration: The AI operates natively within the sedApta suite, connecting demand planning, scheduling, and MES without information silos.

About O.S.A.

The digital backbone of sedApta Suite for an open platform

sedApta’s O.S.A. suite is an ecosystem that provides users with new “capabilities” to support Supply Chain Management and Change Management processes, enabling collaborative management of demand planning, inventory, delivery, and production processes. At the same time, it ensures complete transparency regarding all activities and actions at every level.

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