Advantage #3: Improve Quality Assurance with Machine Learning

Over the course of seven blog posts, we’ve been exploring the challenges and advantages of machine learning in manufacturing. Thank you for joining us for the final post in the series, focusing on how machine learning can improve quality assurance.

How Does Machine Learning Improve Quality Assurance?

Improved quality assurance is one of the key advantages of machine learning (ML) in manufacturing. There are many ways that machine learning can be used to improve the quality of your end products, and complete day to day quality assurance tasks. Here are just a few.

Improved Quality Inspection

Quality inspection can be improved by using machine learning, and deep learning. After a machine has been programmed by an expert to watch out for certain factors, it will be able to catch even minimal inconsistencies that its human counterpart may be unable to recognize.

Deep learning is the most “human” type of machine learning. Deep learning systems improve with time and data, similar to the human concept of “practice makes perfect”. But humans can never be perfect. Eliminating human error is one of the biggest advantages of machine learning. Your technology will also be able to learn and improve from the data it gathers.

Improved Speed and Budget

Quality inspection takes time and money, but this application of machine learning in manufacturing can minimize both these investments. Although the initial cost of implementing manufacturing automations or machine learning technologies may seem high, once up and running, your machines will be able to inspect parts rapidly. This investment will lead to improved operational efficiencies, at lower cost over time.

New Product Development

Different but related to quality is the role of machine learning in new product development. As well as checking for inconsistencies in the products you already manufacture, ML can be used to identify what is working well, and what is not working so well, in your product lines overall. This data can be used to design better products moving forward, and to enhance designs as they move through the process, from initial concept to production. Machine learning in additive manufacturing can help successfully move designs towards success.

Why Invest in ML for Improved Quality Assurance?

There’s no doubt that machine learning has the potential to improve quality assurance in manufacturing. As a business leader, you’ll know the importance of producing a high quality, consistent product and meeting the expectations of your customers. By using machine learning to improve quality assurance, you’ll be able to work towards a seamless solution and reach a point where discrepancies between products are truly minimal.

Contact CTND to Take Advantage of Machine Learning in Manufacturing

With artificial intelligence to improve quality assurance, many of the risks and challenges you face today are eliminated. Ensure exceptional product standards and futureproof your business with a partner that can help you implement machine learning to improve operational efficiencies and quality assurance.

CTND has expert knowledge of Epicor ERP, and experience working with manufacturing businesses like yours, including those in aerospace and defense, engineer to order, furniture and woodworking and general manufacturing.

Contact CTND today to make the most of advances in quality assurance technology and all applications of machine learning in manufacturing.

Posted in ERP