Top 10 Use Cases of AI in the Manufacturing Industry

AI in manufacturing refers to using data in combination with machine learning and deep learning algorithms to automate tasks and make manufacturing operations faster, better, and more precise. Accurately forecasting demand is crucial for manufacturers to best plan production and, in turn, reduce inventory costs and maximize profit. Demand forecasting isn’t a new concept, but many manufacturers still utilize traditional forecasting methods (like Excel) to manage their supply chain. Generative AI can be applied to testing software to determine what materials create the most environmentally friendly product design while meeting Key Performance Indicators (KPIs). Due to its additive processes, the automotive industry is currently the biggest benefactor of generative AI for sustainability.

Core business processes should be strategically rethought and redesigned to effectively leverage GenAI. To get started, organizations need to first embrace the trends that will define 2024. This includes learning about emerging technologies from AI to distributed ledger technologies, low-code and no-code platforms and fleet electrification.

Manufacturing AI: 15 tools & 13 Use Cases / Applications in ’24

Not limited to just internal data, they can also analyze external factors to model hypothetical outcomes based on different scenarios. Now that we have a clear understanding around the major benefits of AI for manufacturers, let’s explore some of the most impactful use cases in more depth. There’s clearly an abundance of opportunity for manufacturers to leverage AI and, fortunately, most are already embracing cyber-physical systems and using available IoT data.

And the process lines are running so quickly, they had to make local, real-time decisions. Robotic workers can operate 24/7 without succumbing to fatigue or illness and have the potential to produce more products than their human counterparts, with potentially fewer mistakes. Manufacturers typically direct cobots to work on tasks that require heavy lifting or on factory assembly lines. For example, cobots working in automotive factories can lift heavy car parts and hold them in place while human workers secure them. Here are 10 examples of AI use cases in manufacturing that business leaders should explore now and consider in the future. Predict trends and plan your business steps with custom AI manufacturing solutions.

What’s Next for AI in Manufacturing

Additionally, machine learning can help to enable video surveillance systems to detect when workers are not wearing proper protective equipment or are engaged in unsafe practices. And unlike traditional forecasting solutions, machine learning models are, by definition, constantly taking in new information and adapting. Machine learning models can aggregate historical data with new data from a variety of sources, like enterprise resource planning systems, point-of-sale systems, and social media marketing campaigns. Generative AI can analyze vast amounts of data quickly and accurately, providing valuable insights for strategic decision-making related to areas like production planning, inventory management, and supply chain optimization.

Robots have been used to automate manual tasks in factories and manufacturing plants for decades, but cobots are a relatively new development. What makes them different is that they are designed to work alongside humans in a safe way while augmenting our abilities with their own. The figure below depicts that how manufacturers are generating revenues through AI.

Machine learning algorithms predict demand

Companies can use digital twins to better understand the inner workings of complicated machinery. Generative design is a bit like the generative AI we’ve seen in technologies like ChatGPT or Dall-E, except instead of telling it to create text or images, we tell it to design products. Cobots are widely used by automotive manufacturers, including BMW and Ford, where they perform tasks including gluing and welding, greasing camshafts, injecting oil into engines, and performing quality control inspections.

Read more about Cases of AI in the Manufacturing Industry here.