Machine learning for manufacturers

In a manufacturing environment, two main models of machine learning are used – supervised and unsupervised learning. Choosing the right machine learning method and perfecting the algorithms will involve a lot of trial and error and will take time and effort. This episode of EUAudio aims to help ease that process.

Deep learning requires very high computational power, relying on fast processors, dedicated graphics cards and ample amounts of computer memory. Manufacturers who can successfully apply this method to their production lines and supply chains will reap the benefits in problem-solving and increased productivity.

In industrial manufacturing, reinforcement learning is used in processes where complex decision-making skills are required, especially where machines need to cope with changes in dynamic environments. This episode of EUAudio looks at how this method can be applied in order to increase productivity.