Top 7 Industrial IoT Trends of 2019 and the Industries They Disrupt
Many industries hope that IoT will boost their operational efficiency and growth. According to Forbes, the Internet of Things investments are expected to reach $1.2 trillion by 2022. Such massive spendings don’t seem so overwhelming after you take a closer look at what IoT can do for different industries. This technology can help businesses link their OT and IT data with each other, which facilitates production, quality management and supply chain processes. What’s more, IoT can help companies build a single operational model oriented toward maximal results and the smallest risks. Here, take a look at the major industrial IoT trends of 2019 businesses should watch out for. Why? Each of these trends can cause a major shift in the industry that it penetrates.
Top 7 industrial IOT trends of 2019
IoT is finding its place in the most unexpected places. Major IoT industrial trends of 2019 include digitalization, 3D printing, AI manufacturing, contextualization, edge computing, predictive analysis and supply chain optimization. Without further ado, let’s take a closer look at each of them.
1.Rise of 3D Printing
3D printing is not a wonder shown at the top tech expositions anymore. This technology has already penetrated industries like aerospace, agriculture, automotive, education, and more. Currently, 3D printing is not a luxury that businesses incorporate to create innovative items. It is rather a technology widely used in contemporary manufacturing. At the beginning of the 3D printing era, the process was expensive, time-consuming, and, frankly, quite problematic. Currently, businesses use 3D printing to reduce production costs and save time.
Deloitte expects the 3D printing market share to reach 3.1 billion dollars by 2020. As an industrial trend, 3D printing impacts a wide range of productions. As of now, it influences automobile design, defense, and aerospace most of all. Digital manufacturing allows businesses to turn their digital models into actual products. 3D printing lets you design and print complex geometries that were impossible to make in the past.
IoT turns manufacturing devices into smart things that facilitate production. According to Hackernoon, around 35% of manufacturers in the US already use data they get from smart sensors in manufacturing, logistics and final products. IoT devices allow different devices to connect with each other and share data around the network. They help to connect assets with different processes and systems in the manufacturing industry. Businesses can handle operation data properly with the help of smart IoT devices.
IoT can make manufacturing more time-efficient, resource-sparing, and cost-effective. Manufacturing digitalization can give a nudge to a new era in the global economy. Digitalization allows businesses to concentrate on their primary strategic goals and stop worrying about routine manufacturing processes. Yet, industries embracing digitalization worry about data security. Hacking sensitive information from smart devices can cause irreparable damage to companies.
3. Industrial AI in Manufacturing
According to Statista, the artificial intelligence market share revenue is expected to reach 118.6 billion US dollars by 2025. Modern industries have a lot of issues that artificial intelligence can potentially solve. AI can teach smart machines many things that are far beyond human capabilities. Machine learning and pattern recognition technologies can transform manufacturing soon. The most acute AI issues, like natural language processing and computer vision, are solved to the point the current industry development level allows.
No matter what AI application you have in mind for your company, there is probably someone working on an AI project like yours. AI aims to digitalize manufacturing processes in many industries. It can perform quality control, reduce time, materials, and money input, and boost productivity. AI is also expected to manage predictive maintenance in manufacturing. It can also reduce supply chain delays and losses through real-time product updates.
IoT can improve the accuracy of data-driven insights and their relevance in manufacturing. Contextualization is what helps a manufacturer track the right data and drive accurate conclusions based on it. A manufacturer can optimize their operational processes by combining operational data with the IT systems data. Manufacturers can also contextualize their operational technology data with dimensions like production process course, product and batch details, production recipes, quality assurance test results, and more.
Many companies have already shown interest in IoT systems that can boost their production results. IoT systems can help businesses get the production insights needed to reach mass-production excellence. And smart IoT systems that can contextualize massive amounts of data for manufacturers are likely to get significant investments.
5. Edge Computing
Small everyday devices become more and more powerful. Manufacturers of IoT devices use the best practices of AI and local data processing for their products. Edge computing brings computer data storage closer to the location where it is needed. IDC says that 22 Zettabytes of digital storage will be shipped across all storage media types between 2018 and 2025.
Of course, manufacturers already collect massive amounts of information and handle it in the best ways they can. By managing sensitive production information in the cloud, businesses face significant security risks. Edge computing can be a safer and more affordable solution. Handling sensitive production data closer to its source allows cutting down the costs and improve data security. Edge computing can help businesses cut down cloud data storage costs and improve the security of data that gets uploaded to the cloud.
6. Predictive Analytics
Predictive analysis is one of the most discussed IoT trends impacting many industries. Modern factories and plants often run 24/7 and have little time for regular maintenance, let alone emergency maintenance. Manufacturers also receive more information from their factories than their staff can handle. With machine learning, businesses will leverage manufacturing data analysis continually. Predictive analysis can help companies deliver the required information automatically. It will allow them to get rid of excessive production complications and improve product quality quickly and efficiently.
Predictive analysis allows businesses to prevent failures or errors in manufacturing, giving manufacturers more time to handle potential issues and prevent downtime. As a result, companies would save costs, improve operational safety, and earn more. Production should try to turn the asset maintenance processes into the predictive maintenance processes. This way, most production issues, and delays could be prevented.
7. Supply Chain Optimization
Supply chain optimization is one of the main pain points businesses worry about. As the world becomes more connected, businesses compete harder on a global level. Simple logistic processes have long turned into complex multi-layer operations. Modern customers have high expectations toward the product and service quality, transparency, and delivery. To survive in the fierce race for customer attention, businesses need to make their supply chain processes more flexible, optimizing the efficiency of their supply chain through digitalization. Some use digital twins, others turn to mobile apps and some experiment with AI-powered digital tools.
Artificial intelligence can potentially disrupt supply chain management in a lot of industries. Mapping every step and monitoring its execution in real time can improve the speed and transparency of supply chains. By implementing advanced forecasting tools and gathering production data in the real-time mode, businesses can speed up the process lifecycle. Timely updates from IoT devices can improve the quality and speed of the supply chain.
Global industries work on incorporating IoT solutions into their processes. As the IoT technology gets more sophisticated, new spheres for its application emerge. IoT can already help different industries optimize their operational efficiency and grow faster. Given this, we expect industrial IoT to draw more investments, launch more startups, and conquer more grounds in production in 2019.