What is Industry 4.0?
Humans are evolving continuously and inventing ways to improve our lives. Since the industrial
revolution started with steam power, we are constantly working on improving it further. Taking
it to the second generation with mass production and assembly lines and then to the third gener-
ation where automation with the help of computers is the reality. So what’s next? With the wide
use of IoT and AI, the scope of connecting all these machines in the complete supply chain is on
the horizon. Connected machines produce an enormous amount of data in terms of production
throughput and maintenance. and this data needs to be managed in a proper manner in order
to make use of it. It is beyond any human’s ability to analyze this large amount of data, identify
patterns and act on it in a timely manner. This is where AI can play a significant role by making
decisions on this data by identifying patterns to perform the required tasks. These machines are
fed with data churned by machine learning algorithms to meet the business goals. This ability of
data exchange, process and analyze this data eciently, make them so intelligent that they can
take the decisions by themselves without needing any human involvement. This type of major
transformation in the manufacturing process is called as Industry 4.0.
Benefits of AI for IoT
Without AI, IoT will not be able to deliver much value, as we will not be able to utilize a large
amount of data generated by these machines or devices. AI provides this much-needed sup-
port where the stream of data can be analyzed, processed and acted upon without any human
intervention. Following are some of the benefits AI can provide to make an IoT implementation
successful.
Reduction in Downtime: When we talk about manufacturing, downtime plays an important
role. The whole reason industrialists thought of bringing revolution to the industry sector is
because they wanted to increase the production eciency. Production is a series of processes
and one process is dependent on another process. If one process is down or in delay serving,
the other dependent processes go in a waiting stage. This means the factory is not producing
anything until that single process is fixed. This is a snowball eect and ultimately aects the mar-
kets where products are out of stock due to the failure in replenishment. As you can see, it has a
higher economic impact on the entire supply chain. Therefore it is extremely important to find
ways to reduce this downtime. That’s where AI can help, as without AI the data that IoT is gen-
erating has no use. AI can easily detect if one particular machine is not responding or sending a
stress signal. AI can also trigger an action on that machine by running self-diagnostic tests, send-
ing emergency alerts to the technicians, reassigning, and resetting timeline for other dependent
processes, alerting the entire supply chain about the process change so further resources can be
used in an ecient manner.
Preventative Measures to Reduce Downtime: With the help of AI, we can prevent these costly
downtimes. Machine learning can play an important role in analyzing data generated by these
machines and train them on taking preventative actions based on triggers. It can help identify
the maintenance requirements and perform maintenance in an orderly manner. Machine learn-
ing can also identify patterns that can cause disruptions and schedule predictive maintenance.
Operational Eciency: By reducing downtime and using preventative measures to avoid them,
industries are able to achieve higher operational eciency. This can further be enhanced by using
predictive analysis on the supply and demand side. The whole supply chain can be re-planned
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