AI in Manufacturing: A Game-Changer for Optimized Production

Are your manufacturing processes outdated? Have you heard about AI and you’re not sure if it would be a good fit for your company?

Implementing AI is no small task and there is a lot of work involved. However — if done correctly — it can have a plethora of benefits for you, your company, and your employees.

What is Artificial Intelligence?

Artificial Intelligence (AI) is the concept of machines being able to learn through visual perception, speech recognition, decision-making, and language translation. The field of AI was first introduced in the 1950s by John McCarthy. Since then, the industry has grown and become a part of our everyday lives — from navigation systems in cars to Amazon’s Alexa.

Industry 4.0: The 4th Industrial Revolution

During the first revolution, manual labor was replaced and improved with the help of machines. In the second revolution, we sped up those machines with gasoline and electricity. Next came the digital era and the birth of the internet. Now we are entering the 4th industrial revolution, where artificial intelligence will help make our machines smarter and capable of things we can only dream of yet.

How AI is Changing the Manufacturing Industry

AI brings exciting changes to the way we process and analyze data and manufacture products. Robots are performing manual labor, and the need to upskill employees will be crucial. Just like when CAD replaced drafting boards, businesses will be forced to adapt to avoid being phased out.

Benefits of AI in Manufacturing:

• Predictive maintenance
• Faster actions and decisions
• Innovative products, services, and materials
• Improved efficiency
• Higher precision with reduced human error
• Reduced product and service costs
• Exponential scale
• Augments human skills
• Accelerates process timing
• Solves complex problems quickly
• Improves product and service quality
• Increases productivity
• Manages corporate task and domain knowledge
• Fewer biases in decision making

The Limitations of Manufacturing AI

AI is only as smart as the data it receives — human error can skew the results. Missing or incomplete data will impact accuracy. You’ll need skilled workers to operate it, and initial costs can be difficult if you have little capital to work with.

Examples of AI in Manufacturing

Siemens installed over 500 sensors in its gas turbines to monitor temperature, pressure, stress, and other data, feeding it into their neural-network AI to create optimal combustion conditions. According to Dr. Norbert Gaus, Head of Research in Digitalization and Automation, “Even after experts had done their best to optimize the turbine’s nitrous oxide emissions, our AI system was able to reduce emissions by an additional 10-15%.”

Toyota’s manufacturing plant in Sweden uses AI-equipped trolleys filled with baskets of tools, parts, and other components that navigate around the factory and avoid obstacles and collisions.

LG CNS, a Korean company known for its cloud-based smart factory service, implemented Microsoft Azure Document DB and HDInsight to automate their manufacturing process and monitor production efficiency, using Azure Machine Learning to predict emerging defects.

Will Robots Replace People?

AI and the internet of things (IoT) will bring drastic changes to manufacturing, but this won’t happen overnight. According to Matt O’Neill in the Business Futures Podcast by Datel, the 2-3 year forecast predicts the number of multitasking robots available will be approximately 5% of the current 200 million people who are unemployed. Until humans become less cost-effective than robots, companies will be slow to implement full automation. Businesses with small working capital can begin by integrating sensors to collect data and upskilling current employees.

Implementing AI into Your Manufacturing Processes

1. Analyze and Identify Your Current Processes — Before you can effectively implement AI, you need to know what your processes are so you can identify where improvements can be made.
2. Use Sensors and Smart Technologies to Collect Data — Research current sensors and technology, including motion detectors, accelerometers, gyroscopes, actuators, or GPS navigation systems.
3. Implement AI to Interpret the Data and Automate Processes — Once you know what data is being collected, use AI to interpret it and make decisions on what to do next.

The manufacturing industry is constantly changing, and businesses have to adapt quickly to stay ahead. Stay ahead of your competition and subscribe to our newsletter for the latest updates in the manufacturing industry.