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.
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 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.
When a warehouse isn’t well organised, errors can occur and some businesses worry that introducing automation can be an expensive process requiring them to update and upgrade all of their legacy equipment. This episode of EUAudio discusses how plant managers can increase the efficiency of their inventory management processes using affordable automation.
How can manufacturers improve productivity on the factory floor without spending a fortune? In this episode of EUAudio, we look at advancements that SMEs can make even if they don’t have the budget to facilitate large-scale investment.