Heaptalk, Jakarta — The industrial revolution 4.0 is a necessity. The fourth revolution has rapidly changed the landscape of today’s industrial business. As it occurred in the manufacturing industry, the industry is now migrating progressively into the digitized, projected to bring simplification and modernizing the process with computers’ adoption. Also, it is enhanced with autonomous and trackable systems constructed by a set of data and machine learning and assisted with Artificial Intelligence.
“One of the implementations that face great expectation is how the stakeholders want to know about the overview of the factory’s process, whether it is effective or feeble, like how the data from every source can be collected and then interpreted to make a decision faster and more accurate,” Mochammad Irzan, Systems Engineering Senior Manager, Juniper Networks, speaking during the ABDI Industry 4.0 event on 9 March 2021.
Imagine if all of these were conducted manually, just like when we want to know the tendency or pattern of assembly behavior. In this case, we need to collect thousands of records from every single data source per hour, where data tools like sensors used can be more than ten, then we need to interpret, summarize, and visualized the data on the length of one week. Of course, this work is arduous for the human to do, and although it could take how much human resources to be mobilized just for this.
Therefore, optimizing the data management and handling has become the key problem that most industrial keen to solve. Regarding this, the network’s topology is changing right now. It uses multiple communication (any-to-any) rather than a single communication known as the modest behavior connecting one client and one server.
“In the past, the industry tended to use a single site (client and server), now the implementation is more complex. Some industry is turning into any to any model, where devices can communicate each other, such as servers to smartphones, smartphones to sensors, and so on. A 24 hour non-stop network operation is required, with a large number of network devices and security. The applications used have grown from being limited to varied forms,” explained Irzan.
Information technology must adapt to changing times
The main challenge: is for the implementation
Irzan also explained that most companies still misconstrue the data management’s spending cost, which is supposed to be exorbitant since they have to hire more human resources and the data growth that they should manage.
“It is true that people are needed to manage the data. Especially the network data. But even the network is growing more extensive, the support teams’ numbers will not grow linearly. It is because Juniper provides a solution to manage data and network efficiently based on Artificial Intelligence,” Irzan added.
Irzan Said, as the company who has experienced for 20 years on Networking Solution, Juniper can provide the automation, where the tools are the essential parts to operate the network and conducting the data. Whereas from the technological support, it is varied where user can utilize something to Machine Learning, Deep Learning Algorithm, combined with automation and Artificial Intelligence.
The Infrastructure Implementation
The other challenge for the enterprises to initiate the automation environment is preparing the infrastructure. According to TechTarget Research, the percentage of the infrastructure set up to fail (Falire Rate) is dominant. The highest rate mentioned is like for the Telecommunication industry, followed by energy infrastructure and also transportation.
Thus, the implementor should be more cautious. As the Networking and Cybersecurity solutions principal, Juniper maps the implementation process into three phases; design, deployment, and operations. The operations phase runs then iteratively, including analysis, validation, compliance, and finally making the root cause identification. After experiencing the four processes, it is then entering into the Operate and Assure process. As long as the deployment lifecycle runs, the client-side will face continuous development and improvement. (FK)
