digital twin uses - Robotic Simulation Services

IoT and Digital Twins can reduce the costs in the manufacturing industry, minimizing unexpected downtime. These emerging technologies also help to perform complex simulations, offer deep insights and suggest equipment improvement. IoT technology also safeguards the interest of the manufacturer adding speed and flexibility in every situation.

What is a Digital Twin in simple words? Or, for that matter, IoT?

Digital Twin is the virtual twin or copy of the actual product. The digital twin connects the physical and digital worlds.

On the other hand, IoT, or the Internet of Things, is a physical "things" network. IoT platform is the medium for connecting and exchanging data between material objects. Generally speaking, we embed the sensors and software into physical objects over the internet.

As we live during the industrial revolution 4.0 (Industrie 4.0), manufacturers and industries embrace emerging tech to automate traditional systems. They are using emerging technology like AI, Robotics simulation, Biometrics to speed up the industry systems.

Emerging tech like IoT and Digital Twins are also reducing costs in astonishing ways.

IoT & Digital Twins Case Studies:

The evolution of IoT has made data transfer hassle-free by connecting sensors to the cloud and other "things." Apart from this, IoT is also serving as an effective tool for predictive maintenance.

Conversely, Digital twins leverage IoT to aid organizations in monitoring assets or processes virtually. Unfortunately, these are assets that are hard to check due to their distant location or a hazardous environment.

IoT and Digital Twins have unimaginable use in reality. For instance, power grids breakdowns create hindrance in every life, causing delays in businesses and services.

We can now tackle unwanted interruptions in power distribution thanks to IoT predictive maintenance.

Finland's electrical substation is the exemplary model of the predictive maintenance case study. In 2018, the electrical sub-station used Haltian's Thingsee wireless sensors for the first time. But, unfortunately, these sensors require manual checks from the human side.

The electrical sub-station used the sensors to collect temperature components, including humidity, air pressure, and distance.

This IoT-based predictive maintenance helped to increase efficiency in the electrical sub-stations while eliminating equipment failures. In addition, predictive maintenance helped to detect flopping assets and understand the factors leading to abnormal operations and disrupting schedule maintenance activities.

Finland's electrical sub-station isn't the only example of successful IoT in industrial applications.

Ericsson Panda manufacturing plant in China is another IoT case study we need to discuss.

The Ericsson Panda plant in Nanjing used Cellular IoT and connected 1000 devices to form a gigantic branch. In addition, the system had embedded IoT modules to send and receive data in real-time.

The IoT modules are said to transmit about 100 bytes of data per 8 hours from recent usage. Later, Ericsson Panda used the data in a cloud solution for analysis. The IoT solution costs just $20 per unit, will cut 50% maintenance work, saving USD 10,000 annually, and achieving breakeven for Ericsson Panda in 2 years.

The Ericsson Panda manufacturing plant is the first cellular IoT –based smart factory, and its immense success has contributed to the expansion of IoT worldwide.

Today, IoT technology has become a key element in the global supply chain already.

Since the beginnings of the industrial revolution, companies were eager to measure the temperature of the transported goods using the low-cost solution. IoT-based predictive maintenance and analysis applications in refrigeration systems help to understand when the system may fail. Therefore, it helped to avoid wastage of valuable agricultural goods and medicines and save money and time.

Similarly, companies have managed to keep the maintenance costs of factory equipment under control by 40%. IoT -based predictive maintenance has also helped to reduce equipment downtime by 50%. It reduced equipment capital investment by 3% to 5%. It saved the overall capital investment by 3% to 5% by extending the life of machinery.

Digital Twins can save money by predicting future failures. So, companies can repair defects at their earliest at a much lesser cost. It also recommends best strategies to improve the product development cycle, maximizing profitability. In this way, companies using Digital Twin can maintain a good relationship with their consumers.

As we can see, emerging technologies can help industries in the most remarkable ways. However, the expansion of Digital Twin and IoT isn't just limited to electrical sub-stations, supply chains, or manufacturing plants.

IoT and Digital Twin have expanded to other utility industries like healthcare, rail transportation, and oil and gas.

Oil and gas industries are adopting Digital Twins faster to minimize the costs of assets and productions. These industries have costly investments and handle them very carefully. Thus, it's no surprise that they aggressively adopt digital twins for modeling operations such as oil rigs, pipelines, and processing facilities.

Oil and gas companies have digitalized their systems to cut off weeks of unplanned downtime while reducing production costs. In addition, these industries have adopted predictive maintenance and IoT analytics to review historical data to detect failures in major components located at their offshore oil platform.

Digital Twins have transformed the transport industry as well. Today, the transport industry applies high-value rolling stock, such as locomotives, to maximize fuel efficiency and optimize maintenance.

The transport industry is willing to achieve the highest fuel efficiency possible to save hundreds of dollars to buy fuel. The rail transportation industry had reported saving about 10% on maintenance costs when they switched to condition-based preventive maintenance of rolling stock.

The digital twin is making remarkable contributions in the healthcare industry as well.

Q-Bios can be a great example to discuss. Q-Bios is the first clinical digital twin platform that harnessed the ability of digital twins to replicate anything indifferently.

Q Bios Gemini Digital Twin platform has built Mark-I, a computational biophysics model to scan the whole body. The company reported that Mark- I will examine the human body in 15 minutes and doesn't require radiation or breathe of the actual person.

Q Bios Gemini has claimed that Mark- I can work 10X better than the traditional MRI scanners for many critical diagnoses. In addition, Mark-I, the computational model, can eliminate bias or hallucination risk from AI and machine learning.

Another most significant advantage of the Mark-I is that it shields the patients from exposure to radiation, protecting them from running into the risks of developing cancer cells in the future.

Q Bios Gemini has received over $80 million from Andreessen Horowitz and Kaiser Foundation Hospitals to develop and expand its breakthrough whole-body scanning technology. In the future, the full-body scanning tech from Q Bios Gemini will provide data-driven and affordable care for all.

Medical and software companies are collaborating on digital twinning projects to create exact replicates of human body organs like the heart and the brain. The aim is to minimize risks in critical surgeries and aid organ donations.

Sim&Cure, a medical technology company, has built a digital twin called Sim&Size. This digital twin simulation will make brain surgery safer for Aneurysms patients as they will need less invasive surgery using catheters to install implants.

In another instance, Dassault Systèmes SE, a French software company, developed a Digital Twin heart using MRI images and ECG measurements. This digital twin model of the heart replicates the structure and some functions of the human heart. Now, heart surgeons can feed the patient data into the Digital Twin heart to determine whether the surgery will be successful.

Dassault Systèmes SE has launched the Living Heart Project in collaboration with academic and industrial members like Medtronic, Philips, and Boston. All the Living Heart Project members are working together to build safer and effective cardiac devices for patients.

Conclusion:

All the major industries are gaining massive value from IoT and Digital Twins. In other words, they are saving and making money simultaneously.

According to the predictions of McKinsey & Co, IoT technology would reach $11.1 trillion in economic impact by 2025. In addition, Cisco reported that data derived from IoT devices would surpass 800 Zettabytes by the end of 2021. There's no doubt that industries using IoT devices are experiencing explosive growth.

These industries are witnessing such massive growth because they managed to cut off shocking downtimes with Industry 4.0 technologies and build the ability to predict future failures and make necessary repairs using a digital twin.

Sadly, many companies have no idea about unplanned downtime's costs, root causes, and consequences. According to Service Max, 82% of companies reported that they had experienced unplanned downtime for three consecutive years. In addition, these companies experienced an average outage duration of 4hours every day with a median cost of $2 million.

Service Max also concluded that 70% of companies have no idea when their production machines will need maintenance or upgrades.

So, we can say that companies adopting IoT and digital twins are increasingly performing better than those avoiding emerging technologies. It happens because IoT and digital twins improved situational awareness and aided industry leaders in making faster business decisions.