Manufacturing Machinery and Machine Learning

MES Aerospace and Defense Auto and Transportation Consumer Products Food and Beverage Industrial Medical Equipment and Pharma Metal Manufacturing and Fabrication

As stated by The Manufacturer, “Machine Learning is the low hanging fruit of the digital toolbox. Everybody has data in their factories, and they can use that data to gain insight and gain operational performance. It can also be used to support the workforce, it can be used for AI virtual assistants and for making sure that anomalies are detected in the process.”

Machine learning is the study of computer algorithms. These algorithms automatically improve through experience and with the use of data.

With all of this automation, one thing remains the same, the process of manufacturing products is expensive and complicated. Manufacturers who implement the right tools and resources to develop quality products can significantly reduce unnecessary costs and complications. Machine learning is quickly becoming a key driver in helping to reduce cost and time of production.

Here are a few ways machine learning is impacting manufacturing:

Supply Chain Management

Machine learning can help logistical processes like inventory management, asset management, and supply chain management. Some machine learning solutions monitor every step of the manufacturing, packaging, and delivering processes.

Quality Control

Machine Learning is essential to enhancing the quality of the manufacturing process. By detecting early warning signs of anomalies in manufacturing lines, machine learning helps predict the availability, performance, quality, and weaknesses of the machine.

Overall Process Improvement

Manufactures can use machine learning to detect issues with production, from bottlenecks to unprofitable production lines.

Product Development

Access to accurate, actionable data that is derived from machine learning, also provides product development opportunities for manufacturing companies. The data helps the decision-making process related to developing a new product and the risk associated with it.

Through machine learning, operators can be alerted before system failure, and in some cases without operator interaction, avoiding costly unplanned downtime, by identifying, monitoring, and analyzing the critical system variables during the manufacturing process. Getting actionable insights that are accurate requires a significant amount of data in real-time to understand the anomalies before system failure.

ShopVue’s Smart Manufacturing APIs connect shop floor systems so you can access real-time data and convert it into meaningful insights that ensure operational excellence. To find out more, ask the experts at ShopVue.