I. The "Takeover" of Digital Twinning
Digital Twin is a simulation process that integrates multi-disciplines, multi-physical quantities, multi-scales and multi-probabilities by making full use of data such as physical model, sensor update and operation history, etc., and completes mapping in virtual space, thus reflecting the whole life cycle process of corresponding physical equipment.
Digital twinning provides virtual objects that correspond to physical components used in the industrial sector. For example, a robotic arm building a car could be monitored using digital twinning, which collects data about the arm's operations and provides information about components that need regular maintenance or replacement.
Digital twinning can make predictive maintenance easier and provide valuable visualization capabilities to improve efficiency. While there are many ways to collect and manage Internet of Things information, digital twinning offers a more intuitive and powerful approach.
Second, innovative man-machine interface
Computer screens, and even more primitive displays, still dominate industry, but that's changing.
Augmented reality apps can provide more valuable feedback when viewing device components and provide employees with IoT derived information about manufacturing equipment so companies can better manage and maintain it; Virtual reality can also use more traditional technologies to provide powerful visualizations for workers.
VR and AR are often tailored for specific tasks, and as headsets and smart glasses become more prevalent and cheaper, these technologies will become more popular, especially in industrial Settings.
Better predictive maintenance
Predictive maintenance has been playing an increasingly important role in industrial environments for many years, and the continued growth of IoT components provides more information than ever before.
Combined with machine learning and other artificial intelligence tools, modern industrial software is more effective than it used to be to rely on personal experience to determine when equipment parts need to be replaced.
Unlike other technologies, the benefits of predictive maintenance are easy to calculate. As an industrial IoT technology, predictive maintenance is bound to become an excellent assistant to industrial managers in the future.
Fourth, cyber security investment is increasingly important
In its early stages, the Internet of Things will often be chaotic in the process of performing its tasks. At the same time, for many companies, safety equipment is not considered a top priority.
Now that's changing, companies that are about to or have invested in the Internet of Things are increasingly taking steps to ensure that new investments are protected from cyberattacks.
Part of the reason for the change is that cyberattacks are becoming more rampant and profitable, and industrial equipment with less security is particularly attractive.
One of the challenges facing manufacturing companies is to make sure they use the right security protocols and ensure compliance with all operations, as there is no one-step solution that will 100% protect a device from an attacker.
Five, more flexible transformation
Due to the high downtime cost of industrial equipment, companies usually try to avoid hardware and software upgrades and transformations. Therefore, changes in industrial enterprises are sometimes very slow.
However, improving efficiency across the board will force companies to operate in a more flexible way. IoT and AI analysis can sometimes lead to surprising results, as AI is so important for discovering relevant areas that humans may never explore.
The long-term transformation of the real industry will find ways to adapt more quickly to informationization, and this will continue to increase in the coming years.
6. More efficient automation technology
Automation has always been at the heart of industry, and digital technology is extending this trend. Instead of investing in expensive heavy equipment, companies can now rely on low-cost equipment to complement a wider range of manufacturing components.
As automated systems continue to prove their value, businesses will invest more and see significant efficiency gains and lower labor costs.
Hiring of workers will remain strong, however, because even highly automated systems require people to monitor progress and find ways to maximize efficiency.
Seven, more timely edge calculation
The amount of data collected by IoT components can be staggering, and one of the bottlenecks in IoT applications is ensuring that the system can monitor the necessary information in real time.
As a result, a powerful component of IoT operations will rely on edge computing devices that can collect, process, and analyze data before it is sent to more centralized servers.
While investment in servers or off-site cloud solutions will continue to increase, edge equipment will see significant investment in the future and relieve some of the processing pressures common in today's industrial environment.
