Technologies that will dominate manufacturing in 2022
03-04-2022 321
Chúng tôi mách bạn 4 xu hướng công nghệ sẽ cách mạng hóa kịch bản sản xuất công nghiệp vào năm 2022
Mục lục
Manufacturing technology offers an unprecedented transformation of business profitability and competitiveness. Among the technologies that have transformed the manufacturing industry recently are Big Data, IoT, 3D printing, and Artificial Intelligence.
However, development is accelerating and new ways to increase productivity and profitability of manufacturing plants are emerging.
We tell you 4 technology trends that will revolutionize the industrial production scenario in 2022
The technology is increasingly transformative, allowing anyone to configure computer software that enables “robots” to simulate and integrate human interactions in digital systems. to run an industrial or commercial process.
RPA acts as a complex and complex system, taking the traditional ERP system to another level, giving it machine learning to take full advantage of the automation it enables.
RPA enables automation at a fraction of the cost and time previously spent. Furthermore, the technology is non-intrusive in nature and leverages existing infrastructure without disrupting the underlying systems, which would be complex and expensive to replace.
RPA multiplies the efficiency of any repeatable, business-ruled, high-volume process. Order lists are automatically generated and executed by a software robot, helping employees focus on tasks that bring real value to the company.
- Immediate and significant cost reduction:
Robots perform repetitive tasks much more efficiently than humans. When work is automated, not only is it done faster, but it can be done 24 hours a day at a much higher rate, without errors, and at a much lower cost than employees.
- Quickly realize benefits:
The initial investment required is low, but the short-term results can be seen as a significant improvement in the quality of some processes, which will forecast the company's profitability.
- Improved cycle time:
This complex automation system saves time for all parts of the company and avoids disruption of basic systems. Companies won't have to hire third parties to hire labor-intensive pieces of work, so they'll have more and better control over their operations while reducing risk.
- The system is flexible and highly scalable:
It adapts to the changing business environment, helping business leaders make better decisions for the future in different situations. Also, automation through RPA requires no coding or scripts so transferring processes from person to machine won't be an issue.
Distributed Cloud is the future of the cloud and the evolution of Cloud Computing. It is a multi-cloud concept with geographically distributed infrastructure.
While services are delivered to different physical locations, they are centrally managed and operated, with management and development still the responsibility of the public cloud provider.
The pandemic has greatly reinforced the need for organized ecosystems to be able to operate remotely. The positional independence it has created requires a technological shift that can support this new version of business.
The speed of these changes has yet to allow for sufficient agility and functionality, either at the practical level or the regulatory level. For this reason, a growing trend is to use hybrid and multi-cloud deployments.
This model enables the delivery of the entire public cloud provider's computing stack to wherever a customer may need it: on-premises, in the customer's own datacenter, in a private cloud or off-site. This model provides a flexible environment for low-latency organizational scenarios and allows servers and applications to run closer to where data is generated.
- Improve visibility and manageability of hybrid or multi-cloud:
Any organization can gain greater control over its multi-cloud infrastructure by providing centralized visibility and management, leading to improved manufacturing processes.
- Ensure scalability and flexibility:
Expanding or building data center locations is expensive and time consuming. With the distributed cloud, an organization can scale existing infrastructure or edge locations without physical construction.
- Data security and compliance in place:
Distributed cloud infrastructure makes it much easier for the organization to process personal information (PI) in each user's home country and thus to comply with data privacy regulations.
- Provides repeatability and reliability:
Geographic scaling drives cost reductions and significant latency reductions. By storing information dynamically, companies can combine the capabilities of different locations and reduce the risk of global network disruption.
Augmented analytics combines natural and narrative language technology, enhanced data preparation, advanced automated analytics, and visual data exploration to improve workflow.
It's about leveraging technologies like machine learning and analytics to help automate the entire data management process, from data preparation to knowledge generation and to assist with build and implementation. paradigm.
It enhances the way people discover and analyze data across analytics platforms. By automating many aspects of data science, it democratizes access to advanced analytics and leverages data management. It aims to automate the data collection and preparation process to save a lot of time and money for data scientists and organizations.
Democratizing data science for the entire organization:
They make the data analysis process simple and accessible to many of the organization's records. Any user with minimal knowledge of how it works and what it contributes, will be able to make valuable connections and conclusions.
- Improved knowledge of data:
With natural language that helps interpret findings and provides automated analysis of the results, your users can improve their data literacy. In addition, it allows you to have automated and easy-to-understand dashboards, as well as descriptive and predictive approaches, and the SQL language is no longer needed.
- Reduce analytical bias:
Enabling the analyzer to perform analysis can help reduce analytical bias. If you don't know what you're looking for, you make assumptions to try to find it. Often those assumptions can lead to the use of specific data to support it. Predictions become more accurate about machine behavior, accounts, consumption patterns, and more.
The name 5G refers to the fifth generation of mobile networks as we know them. The most important progress is related to speed. 5G will enable navigation at up to 10 GB (gigabytes per second), 10 times faster than mainstream fiber optic cables on the market. Another improvement related to latency can be reduced to 5 milliseconds, which will allow actual connection in real time.
This new network will be transformative for devices that drive automated industrial processes. Its high reliability and low latency will feed the sensors in industrial machines more efficiently than ever before.
High bandwidth and connection density ensure universal connection. For these reasons, it will help generate large amounts of data, opening new avenues for cost savings and efficiency when combined with machine learning.
- You will connect more devices significantly faster:
By allowing large volumes of data to be transferred from a larger number of more responsive devices more quickly, more valuable information can be obtained.
- Allows near real-time data transmission:
By dramatically reducing latency to less than 10 milliseconds, latency between devices is greatly reduced and data is recorded in near real time.
- Prevent data loss and increase productivity:
Ensure extremely reliable and secure connections to prevent data loss and maximize production performance without sacrificing flexibility, traceability, sustainability or security .
- More flexibility with wireless factories:
Operators can power all of their facilities, on- and off-site, seamlessly with the network for near-wireless operations and faster adoption of new technology.
As businesses face the difficult and economic consequences of the COVID-19 pandemic, organizational leaders continue to face the challenge of achieving effective human-technology interaction. On the other hand, industrial companies increasingly need technologies that support them, making them stronger and more resilient in the face of future uncertainties.
Related Posts:
However, development is accelerating and new ways to increase productivity and profitability of manufacturing plants are emerging.
4 technologies to dominate the manufacturing industry in 2022
We tell you 4 technology trends that will revolutionize the industrial production scenario in 2022
1 - Robotic Process Automation (RPA)
The technology is increasingly transformative, allowing anyone to configure computer software that enables “robots” to simulate and integrate human interactions in digital systems. to run an industrial or commercial process.
RPA acts as a complex and complex system, taking the traditional ERP system to another level, giving it machine learning to take full advantage of the automation it enables.
What will robotic process automation be used for?
RPA enables automation at a fraction of the cost and time previously spent. Furthermore, the technology is non-intrusive in nature and leverages existing infrastructure without disrupting the underlying systems, which would be complex and expensive to replace.
RPA multiplies the efficiency of any repeatable, business-ruled, high-volume process. Order lists are automatically generated and executed by a software robot, helping employees focus on tasks that bring real value to the company.
The benefits of robotic process automation:
- Immediate and significant cost reduction:
Robots perform repetitive tasks much more efficiently than humans. When work is automated, not only is it done faster, but it can be done 24 hours a day at a much higher rate, without errors, and at a much lower cost than employees.
- Quickly realize benefits:
The initial investment required is low, but the short-term results can be seen as a significant improvement in the quality of some processes, which will forecast the company's profitability.
- Improved cycle time:
This complex automation system saves time for all parts of the company and avoids disruption of basic systems. Companies won't have to hire third parties to hire labor-intensive pieces of work, so they'll have more and better control over their operations while reducing risk.
- The system is flexible and highly scalable:
It adapts to the changing business environment, helping business leaders make better decisions for the future in different situations. Also, automation through RPA requires no coding or scripts so transferring processes from person to machine won't be an issue.

2 - Distributed Cloud Computing
Distributed Cloud is the future of the cloud and the evolution of Cloud Computing. It is a multi-cloud concept with geographically distributed infrastructure.
While services are delivered to different physical locations, they are centrally managed and operated, with management and development still the responsibility of the public cloud provider.
What is distributed cloud computing used for?
The pandemic has greatly reinforced the need for organized ecosystems to be able to operate remotely. The positional independence it has created requires a technological shift that can support this new version of business.
The speed of these changes has yet to allow for sufficient agility and functionality, either at the practical level or the regulatory level. For this reason, a growing trend is to use hybrid and multi-cloud deployments.
This model enables the delivery of the entire public cloud provider's computing stack to wherever a customer may need it: on-premises, in the customer's own datacenter, in a private cloud or off-site. This model provides a flexible environment for low-latency organizational scenarios and allows servers and applications to run closer to where data is generated.
Distributed cloud computing benefits:
- Improve visibility and manageability of hybrid or multi-cloud:
Any organization can gain greater control over its multi-cloud infrastructure by providing centralized visibility and management, leading to improved manufacturing processes.
- Ensure scalability and flexibility:
Expanding or building data center locations is expensive and time consuming. With the distributed cloud, an organization can scale existing infrastructure or edge locations without physical construction.
- Data security and compliance in place:
Distributed cloud infrastructure makes it much easier for the organization to process personal information (PI) in each user's home country and thus to comply with data privacy regulations.
- Provides repeatability and reliability:
Geographic scaling drives cost reductions and significant latency reductions. By storing information dynamically, companies can combine the capabilities of different locations and reduce the risk of global network disruption.
3 - Enhanced Analysis
Augmented analytics combines natural and narrative language technology, enhanced data preparation, advanced automated analytics, and visual data exploration to improve workflow.
It's about leveraging technologies like machine learning and analytics to help automate the entire data management process, from data preparation to knowledge generation and to assist with build and implementation. paradigm.
What is augmented analysis used for?
It enhances the way people discover and analyze data across analytics platforms. By automating many aspects of data science, it democratizes access to advanced analytics and leverages data management. It aims to automate the data collection and preparation process to save a lot of time and money for data scientists and organizations.
The benefits of augmented analytics:
Democratizing data science for the entire organization:
They make the data analysis process simple and accessible to many of the organization's records. Any user with minimal knowledge of how it works and what it contributes, will be able to make valuable connections and conclusions.
- Improved knowledge of data:
With natural language that helps interpret findings and provides automated analysis of the results, your users can improve their data literacy. In addition, it allows you to have automated and easy-to-understand dashboards, as well as descriptive and predictive approaches, and the SQL language is no longer needed.
- Reduce analytical bias:
Enabling the analyzer to perform analysis can help reduce analytical bias. If you don't know what you're looking for, you make assumptions to try to find it. Often those assumptions can lead to the use of specific data to support it. Predictions become more accurate about machine behavior, accounts, consumption patterns, and more.
4 - 5G Network
The name 5G refers to the fifth generation of mobile networks as we know them. The most important progress is related to speed. 5G will enable navigation at up to 10 GB (gigabytes per second), 10 times faster than mainstream fiber optic cables on the market. Another improvement related to latency can be reduced to 5 milliseconds, which will allow actual connection in real time.
What will 5G networks be used for?
This new network will be transformative for devices that drive automated industrial processes. Its high reliability and low latency will feed the sensors in industrial machines more efficiently than ever before.
High bandwidth and connection density ensure universal connection. For these reasons, it will help generate large amounts of data, opening new avenues for cost savings and efficiency when combined with machine learning.
Main benefits of 5G Network:
- You will connect more devices significantly faster:
By allowing large volumes of data to be transferred from a larger number of more responsive devices more quickly, more valuable information can be obtained.
- Allows near real-time data transmission:
By dramatically reducing latency to less than 10 milliseconds, latency between devices is greatly reduced and data is recorded in near real time.
- Prevent data loss and increase productivity:
Ensure extremely reliable and secure connections to prevent data loss and maximize production performance without sacrificing flexibility, traceability, sustainability or security .
- More flexibility with wireless factories:
Operators can power all of their facilities, on- and off-site, seamlessly with the network for near-wireless operations and faster adoption of new technology.
Trends in 2022
As businesses face the difficult and economic consequences of the COVID-19 pandemic, organizational leaders continue to face the challenge of achieving effective human-technology interaction. On the other hand, industrial companies increasingly need technologies that support them, making them stronger and more resilient in the face of future uncertainties.
Related Posts:
- What is Smart Manufacturing?
- Warehouse automation risks to avoid
- ROI - Motivation for Investments IIOT