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Sequencing Algorithms in APS: How They Work and Where AI Comes In
Production Programming

Sequencing Algorithms in APS: How They Work and Where AI Comes In

As Artificial Intelligence (AI) continues to advance, new algorithms for production sequencing are rapidly gaining traction. But how exactly do these algorithms make decisions? Whether through optimization models—such as genetic algorithms or neural networks—or through step-based heuristics, the logic behind APS is evolving quickly. To explore these transformations in depth, read the article by Victor Todeschini, COO of NEO.

Posted in:
June 18, 2025
Posted by:
Victor Todeschini
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Sequencing Algorithms in APS: How They Work and Where AI Comes In

As Artificial Intelligence (AI) continues to advance, new algorithms for production sequencing are rapidly gaining prominence. But how exactly do these algorithms make decisions? Whether through optimization models—such as genetic algorithms or neural networks—or through step-based heuristics, the logic behind APS is evolving quickly. To explore these transformations in depth, read the article by Victor Todeschini, COO of NEO.

At NEO Summit 2024, we hosted the roundtable AI: Hype or Reality?” , where our COO, Victor Todeschini, and Lucas Lauck, leader of NEO Labs, discussed with clients the real impacts of AI on the planning and scheduling of .

At NEO Summit 2025, the message was clear: AI isn’t hype — it’s reality. The question now is: how can we avoid falling into trend-driven traps and apply this technology the right way?

‍

What are optimization and heuristics algorithms?

The standard concept of production sequencing is based on heuristics, which rely on predefined decision rules. A simple way to understand this is that, no matter how many times we run the heuristic, we will always get the same result, because it follows the exact same step-by-step logic for decision-making.

Optimization algorithms come into play when the goal is not simply to follow a fixed sequence of steps, but to find the best possible solution within a set of constraints and variables. Unlike heuristics, which are fast and deterministic, optimization algorithms explore multiple possibilities, often using strategies such as local search, genetic algorithms, or mathematical programming to minimize or maximize an objective function — such as total production time, delay, or setup

Opcenter APS has always been based on the concept of classic heuristics , like sequencing for shorter processing time , shorter delivery date , similar setup , etc. These are simple rules, but they work well across a wide range of scenarios.

However, in 2023, Neo launched its own turbocharged heuristic , called N-SBR (Neo Smart Balancing Rule). The N-SBR combines multiple criteria simultaneously-such as dates, priorities, setups, bottlenecks and historical behavior-delivering results that more closely reflect real manufacturing conditions, with logic tailored for the challenges of modern manufacturing.

But ... what if this heuristic could learn over time ? What if it could adapt on its own to different contexts, optimizing decisions based on real data rather than fixed rules?

This is exactly what we are starting to explore: how to supercharge N-SBR with artificial intelligence .

Let’s dive into this scenario — where structured logic meets dynamic learning — and discover what happens when we combine the best of both worlds.

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AI, yes. But done the right way.

At Neo, AI isn't here to replace heuristics - its here to amplify them. Our goal is to build a system where AI:

  • Learns from historical data to suggest adjustments to the N-SBR logic

  • Simulates scenarios and evaluates their impacts before execution

  • Recommends alternative sequences based on hidden patterns

  • Monitors actual results and feeds them back into the decision-making process

This isn’t some distant future. We are already building this ecosystem, blending the reliability of heuristics with the adaptive power of AI.

AI is part of the solution. But it should never be an indecipherable black box .
We continue to believe in clear logic, auditable decisions, and full control by the production team. Therefore, even with AI in play, we maintain:

  • Transparency in the rules

  • Speed in decision-making

  • Flexibility to customize and simulate

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Conclusion: Technology empowering industry

The secret to APS success is blending the best of heuristics — their simplicity, speed, and efficiency — with the strategic power of AI. At NEO, we are committed to solutions that genuinely deliver for your business, steering clear of trends and focusing on real, measurable results.

"Sequencing production in the short, medium and long term - with ease, agility, speed and assertiveness - is among the differentials that Opcenter APS gives us today."

— Anderson Petter, PPC Coordinator at America Tampas

If you’re ready to revolutionize your production planning and sequencing, partner with a team that blends cutting-edge technology with real shop floor expertise to genuinely supercharge your  business.

‍

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