Practical Applications of Machine Learning in Manufacturing

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Machine Learning in manufacturing is changing the way companies do business : From Marketing to Production. During Industrial Revolution 4.0, Modern manufacturing technology is incorporating machine learning throughout the production process. In this article we will discuss various applications of machine learning in manufacturing. 

IoT is an integral part of machine learning. Read this article to know in detail about Internet of Things.

Machine Learning has applications in various manufacturing processes. We can leverage following advantages by incorporating machine learning at various levels in the manufacturing process.

  • Reduced Labor Cost.
  • Defect Free Product.
  • Increased Production Speed.
  • Reduced Machine Downtime.

Applications of Machine Learning in Manufacturing Industry

Following are the various application areas of machine learning in manufacturing.

Predictive Maintenance and Minimize Equipment Failure

On manufacturing shop floor, Sensors regularly monitors machine parameters and its performance. Through IoT sensors they send real time data to cloud. Where machine Learning predictive algorithms helps in forecasting the machine failure before it actually occurs. Therefore machine learning helps in prevention of equipment failure through preventive maintenance instead of scheduled maintenance.

Predictive Maintenance and Minimize Equipment Failure

Advantages 

Utilization of machine learning algorithms for predictive maintenance on manufacturing shop floor offers following advantages: 

  • Reduced Machine downtime.
  • Prevents breakdown on production line.
  • Preventive Machine maintenance is performed instead of scheduled maintenance. Therefore maintenance is done when it is actually required. 
Improving Quality Control and Yield Rate

Applications of machine learning in manufacturing also include improving product quality and yield rate. Machine Learning computer vision algorithms are used in manufacturing to distinguish between good and bad samples on production line. 

To achieve this high quality camera is installed on the production line. Real time product Images are sent to the cloud for processing. In Cloud machine learning algorithms identify good and bad samples.

Machine learning models in manufacturing can also predict the problem before it actually occurs. Therefore By changing machine parameters, manufacturing quality problems can be avoided before it occurs. 

Machine learning algorithms helps in Improving Quality Control and Yield Rate on production line.

Advantages

Utilization of machine learning algorithms for product quality control on production line offers following advantages:

  • Reduced Rejection Rate.
  • Quality Product Manufacturing.
  • Increased production rate.
Forecasting Production Requirements

Machine learning algorithms also has application in forecasting accurate data for future requirements. Accurate product forecasting ensures fulfilling customer orders and their satisfaction. 

Machine learning algorithms use historical data and current data input to forecast future requirements. This forecasting data is used by planning engineers for  planning manufacturing activities.  

Supply Chain and Inventory Management

Keeping optimized low inventory in manufacturing helps in reducing inventory cost. Supply chain and inventory management helps in keeping product low inventory without affecting production line. Machine learning algorithms helps in controlling supply chain and inventory management.

Machine learning algorithms helps in improving Supply Chain and Inventory Management

Application Example

Artificial intelligence and machine learning helps manufacturing industry in controlling the supply chain. For example, according to existing weather data and other historical data, machine learning algorithms can predict the best shortest route and time for shipments.

Production Line Monitoring and Resource Management

Connected machines sends real time PLM and sensor data to cloud. From cloud, production manager can monitor real time data and take decisions accordingly. 

Machine Learning algorithms also monitor this real time data and send alerts. This data is also used by machine learning algorithms for process planning for effective utilization of resources.

Machine learning algorithms helps in Production Line Monitoring and Resource Management.

Application Example

Google managed to reduce approximately 40% electricity bills by managing their data center with machine learning. All this is done without any change in existing infrastructure.

Conclusion

To sum up, Machine learning is an emerging technology. It is changing the way we do manufacturing. It helps in monitoring the real time production data and processing that data in cloud. We suggest you to read this article on applications of IoT in manufacturing.  

Got Questions?  We will be happy to help.

If you think we missed Something?  You can add to this article by sending message in the comment box. We will do our best to add it in this post.


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