AI-Powered Resilience: Transforming Manufacturing Efficiency in Uncertain Times feat. Data Lighthouse

In the dynamic world of global manufacturing, the last three years have been a bit of a rollercoaster ride. Two major events have particularly shaken things up:

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1.?????? First, the COVID-19 pandemic caused a massive disruption in supply chains. It was a domino effect: goods weren't delivered on time, if at all. Companies that couldn't adapt their operations quickly enough and strategies faced significant challenges.

2.???? Then, the war in Ukraine led to a massive energy crisis in Europe, sending electricity and gas prices soaring. This hit energy-intensive industries hard, forcing them to rethink their usual way of doing business.

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Right now, many companies are at a critical juncture, searching for ways to make their production more efficient and cost-effective. The key? Leveraging automation for better planning and optimizing value streams.

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One of the reasons why companies fail to implement this is – same as in every bad relationship – poor communication.

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To understand why, consider how production planning typically works. It starts with customer demand and requires coordination across various planning levels, from management to the shop floor , to clarify the question of which product is to be produced on which system. However, each person involved has their own goals and perspectives, that aren't always aligned and communicated effectively.

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Let’s get into an example.

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If a machine breaks down, shop floor employees might make a quick fix but fail to report it to the other levels. While this solves the immediate issue, it leaves no space for future adaptation, compensation for lost time, and improvement of the production process.

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Another issue is that traditional planning methods are proving insufficient.

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Why? Because they mainly work with metadata. How can it be done better? That's what the guys from akeno explained to me at the Hub Day in Hamburg. The team around Alexander Ebbrecht developed a solution in collaboration with the University of Hamburg – a real game-changer. It has two huge advantages:

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1.?????? The AI-powered software uses real-time data from production machines and the shop floor instead of just historical data. This approach provides an immediate and more accurate picture of all the production processes enterprise-wide.

2.???? The software employs probabilistic simulation, using all influencing variables and probabilities to account for unexpected events, like machine failures, fluctuating production times, or varying yields. Quite similar to how Google Maps reroutes drivers around traffic jams in real-time.

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In this way, the tool not only ensures transparency in real-time across the entire production process - it also constantly calculates an optimal production plan so that employees can react immediately to an unexpected event and pass these changes on to all planning levels.

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So, what's the business benefit?

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More optimized production processes and efficient machine usage lead to reduced inventory needs. This cuts storage costs and boosts productivity. Moreover, the solution can track energy prices and adjust production accordingly, a significant advantage for energy-intensive industries saving them a lot of money. And: It also optimizes logistics processes.

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In summary, their solution is not just a tool; it's a transformative approach to manufacturing, offering agility and foresight in a rapidly changing world.

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Pretty cool, right?

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