Machine Learning

Practical Applications of Machine Learning in Manufacturing

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

Machine Learning offers following advantages compared to conventional manufacturing process.

  • Reduced Labor Cost
  • Reduced Product Defects
  • Increased Production Speed
  • Reduced Machine Downtime

Predictive Maintenance and Minimize Equipment Failure

Sensors regularly monitors machine parameters and its performance. Through IoT they send this data to cloud. Where machine Learning predictive algorithms helps in forecasting the machine failure before they occurs. This also started a new trend of preventive measurement instead of schedule maintenance.

Advantages 
  • Reduced Machine downtime
  • It prevents any breakdown on production line.
  • Machine maintenance is performed when it is actually required. 

Improving Quality Control and Yield Rate

Machine Learning computer vision algorithms are used to distinguish good and bad samples on production line. For this high quality camera is installed on production line. Images of output products are send to cloud for processing. In Cloud machine learning algorithms identify good and bad samples.  

Machine learning models can also predict the problem. By changing machine parameters, quality problems can be avoided before it occurs. Therefore rejection rate will reduced. 

Forecasting 

Accurate forecasting ensures fulfilling customer orders and their satisfaction. Machine learning algorithms use historical data and current data input to forecast future requirements. According to forecast data manufacturing planning is done by machine learning algorithms.  

Supply Chain and Inventory Management

Supply chain and inventory management is required to keep low inventory without affecting production line. Low inventory results in cost saving.

Artificial intelligence and machine learning helps 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

Production line Machines connected with IoT sends real time PLM and sensor data to cloud. From where production manager can monitor real time data and take decisions accordingly. Machine Learning algorithms also helps in process planning for effective utilization of resources.

Example : Google managed to reduce approximate 40% electricity bills by managing their data center with machine learning. And this is done 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.  

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