The world of industry is moving quickly into the fourth Industrial Revolution, also known as Industry 4.0. This is down to the rapid increase in artificial intelligence (AI) and machine learning based systems which are totally revolutionising the manufacturing sector. This development sees computerised systems linking with robotics to provide a smart factory environment in which machine learning algorithms contribute to added learning capabilities and so require very little input from human operatives.
There are a number of key requirements to be met for the creation of an Industry 4.0 level factory and at present manufacturers are eyeing up the possibilities and researching exactly what will be required to set the foundations for a smart factory that is totally connected and operates utilising AI-powered systems that are enabled with machine learning algorithms.
What constitutes an Industry 4.0 standard factory?
Industry 4.0 standard factories are also known as “smart factories” and are created when cyber-physical systems are in place for monitoring and decision-making relative to factory processes. The system communicates via the Internet of Things and all processes communicate with each and with the human workforce in real time.
Industry 4.0 factories must incorporate all of the following:
– machines, sensors, devices and people inter-operating within a connective environment
– the transparency of information, whereby sensor data creates a virtual copy of the physical surroundings so that information can be contextualised
– technical support in that the machines offer humans the decision-making and problem-solving support required and also provide abilities to assist with tasks that are too difficult or dangerous for humans to perform
– a decentralised decision-making process, where machines are autonomous and the cyber-physical system is enabled to make its own simple decisions.
Some of the issues arising from the move to an Industry 4.0 factory model include problems that could arise surrounding data security and achieving the stability and reliability that’s required for successful cyber-physical communications. Less human oversight of the production process may also affect the integrity of the procedure, while technical problems could cause severe outages that impact considerably upon production levels. Concerns over the loss of some of the more technical and higher level jobs have also been raised as a significant issue within a variety of industries.
The benefits offered by Industry 4.0 do considerably outweigh the perceived disadvantages, and this is particularly the case in working environments that pose health and safety hazards to human employees. It’s also perceived that advantages over supply chain controls will be quickly realised, giving more consistent levels of output and productivity.
Current use of AI in factories
AI technology already exists in a number of industries from the automotive sector to the fast food industry. However, complex decision-making is still a long way in the future as humans are still required for programming purposes. At present AI incorporated into smart machinery is focused on more repetitive tasks; however, as machine learning is developing in leaps and bounds there is likely to be a far more swift move into mainstream manufacturing.
Manufacturers around the globe are investing heavily into Internet of Things technology to cut production costs and drive up productivity. At present there is very little combination of data industrycollected from smart devices and AI to drive forward the smart factory of the future.
The application of AI to manufacturing processes requires an integrated and intelligent business operation that networks data from the production lines and design, engineering and quality control teams to produce a cohesive system and presently most manufacturers just don’t have this in place.
The process needs to have the correct foundations in order for AI to make the required decisions in the production cycle, with all data fed directly to the cloud for verification and real-time problem solving. Sensors will have the ability to pick up defects as they are developing on the production line and the problem-solving abilities of the AI will be enabled to remove the defective parts and solve the problem while working to just-in-time methodologies to minimise cost implications and supply problems. This type of manufacturing process has the ability to save industries millions of pounds in lost business, recalls and repairs.
The incorporation of more AI systems into factories is likely to lead to greater levels of trust from the human side and allow the system intelligence to build over time. Greater enhancements to existing capabilities such as blockchain, augmented reality and AI will see even more developments within the field and the capability for businesses to operate at greater speeds and levels of productivity.
Data is the key ingredient for any AI-based system, so the collection and analysis of data from any Internet of Things enabled devices needs to become a priority for any manufacturing organisation considering a move into Industry 4.0 and the creation of a smart factory environment.
