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Optimize Operations of Your Cloud-Managed Network with AI and ML

New emerging technology impacts different industries in different ways. Some technologies help us lower costs. Others help us make better decisions. Others keep us safer. AI and machine learning are technologies that will one day impact every industry. This week we explore and discuss the role and how AI and machine learning impacts manufacturing.

Predicting Capacity Demand

One of the challenges in manufacturing is controlling demand. Organizations have to strike a balance of keeping their supply chains full but being able to fulfill demand. As organizations implement a machine learning platform, they will be able to understand previous indicators to better control their future. They will be able to visualize past orders and market data to predict their future orders. An AI-driven platform will be able to automatically schedule assembly lines ahead of time to reserve capacity for customers.

Automating Inventory Planning

As with capacity demand, controlling inventory is a massive risk for organizations. If you have too much, it’s sitting on shelves not driving revenue. If you don’t have enough, you cannot fulfill your obligations to customers. If you cannot fulfill customer needs, you’ll lose out on current and future revenue opportunities. As you feed data to a machine learning platform, your inventory management will become automatic.

Optimizing Operations

One of the key challenges in manufacturing is keeping production lines operating at full capacity. Knowing in real-time how each line’s load level impacts overall schedule performance leads to better decision making. Optimizing the best possible set of production lines for a given run is now possible using machine learning algorithms. AI can then automate this on a day-to-day basis. Machine maintenance can now be controlled as machine Llearning can impact the precise time that repairs can be down without impacting overall operations.

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Manufacturing companies rely on data, and machine learning is taking that data and making it actionable. Without actionable insights, data is just data. Companies must be able to visualize how this data can be used.

AI and machine learning is how they bridge that gap.

 

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