The Role of Artificial Intelligence in Manufacturing: 4 Ways Machine Learning is Changing the Industry


Artificial intelligence is set to change the manufacturing industry. Did you know that 800 million workers could be laid off in the next 12 years?

By 2030, industry experts believe that half of all jobs will be automatable. Artificial intelligence will optimize processes and make manufacturers more productive.

Read on for a greater understanding of the role of artificial intelligence in manufacturing. Explore 4 ways in which machine learning is changing the manufacturing industry for the better.

1. Improvements in Predictive Maintenance

Unscheduled maintenance is a cost driver on the assembly floor. Productivity also suffers when equipment is down and manufacturing cannot proceed.

To combat this negative trend, manufacturers are enlisting the support of machine learning. One method is to use analytical tools to improve predictive maintenance. This way, costly repairs can be stopped before they happen.

Currently, only 28% of manufacturing companies employ predictive maintenance through these means. Over the next 5 five years, that number is expected to climb by 10 percentage points.

2. Supply Chain Forecasting

Supply chain errors are costly in the manufacturing world. When the product is unavailable, the company loses sales as a result.

Here is where machine learning comes into play. For starters, artificial intelligence is leveraging external parts data to improve demand forecasting. This ensures the company has the parts quantity needed to meet sales demand.

Improved supply chain forecasting yields optimized inventory levels. Machine learning in the supply chain arena is producing impressive results.

Experts predict that machine learning will cut supply chain forecasting errors. Lost sales will be reduced as well.

3. Optimized In-Transit Inventory

Artificial intelligence is taking other factors into consideration like weather patterns and other transportation disruptions. For example, a nasty storm can delay parts flow.

Machine learning comes into play by optimizing the supply network. There are many operational dynamics at play that affect your company’s inventory like plane or truck movement.

To address this, companies are leveraging machine learning. Multiple public and proprietary datasets are accessed for live updates.

Companies are using the data to adjust transportation routes and avoid potential delays. The achieved objective is the optimization of in-transit inventory.

4. Optimizing the Production Process

A sure-fire way to reduce costs and improve the bottom line is optimizing the production process. By reducing labor hours and assembly time, your company can achieve this.

Machine learning involves the use of algorithms to determine the best combination of equipment during the production process. Another area of consideration is the equipment’s load level.

Using machine learning, equipment operators receive live data on how the level loads affect the production schedule. This data allows floor managers to make the best decisions in the name of productivity.

Artificial Intelligence in Manufacturing – Wrapping It Up

Clearly, artificial intelligence has the capacity to revolutionize the manufacturing process. Companies are using machine learning to optimize in-transit inventory and production processes.

The goal is to improve productivity and reduce operating costs. If you want to learn more about artificial intelligence in manufacturing (and rest of the supply chain), contact us to see how we can help.

2 replies
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