Smart manufacturing: IIoT analytics and predictive maintenance
For manufacturing especially, the applications of the Internet of Things (IoT) are endless. By using data collected via IoT platforms, manufacturers can prevent potential plant shutdowns, increase efficiency, and proactively repair plant equipment. The potential gains are huge, matched by the amount the manufacturing sector is planning to invest in IoT solutions by as much as $70 billion by 2020.
Helping machines get smart
The ability to predict and correct machine failures before they occur is one major driving force behind Industrial IoT (IIoT) investments. According to recent research by IoT Analytics, the market for predictive maintenance applications will expand from $2.2 billion in 2017 to $10.9 billion by 2022. Predictive maintenance strategies, which aim to predict machine failures before they occur, are based on the combination of traditional condition monitoring enhanced with analytics algorithms. The IoT and ever-more sophisticated analytics are driving widespread market adoption with users reporting as much as 25 to 30% efficiency gains.
For example, a U.S. automobile company recently implemented an IoT platform. The scalable IoT platform connected the business’ objects to the cloud seamlessly via small sensors for customized monitoring and control. The automobile company’s goal was to measure the efficiency of its painting process for car parts on the conveyor belts and correct any lags or errors found in the system. After each part was painted, the sensors measured the part’s movement to determine if the paint was being ruined by excessive motion. This solution allowed the company to easily and quickly identify and correct problem areas before they caused cascading and costly mistakes.
This is one example of what IoT-enabled sensors can measure to minimize plant shutdowns and increase productivity and profits. IoT platforms are also capable of providing diagnostic data such as vibration, movement, temperature, and humidity that decision-makers can use to analyze and predict the health and performance of machines. IoT-powered analytics also can be used for comparative analysis between machines or to determine if any steps in the process are causing costly slowdowns.
IoT platform operations
Each IoT platform operates a little differently, but typically, small sensors are applied to motors and machinery. A self-contained electronic circuit board embedded with a code connects the object with the sensor and collects data. Each circuit board has its own power source as well as communication capabilities with other circuit boards and the software program or app where the data is accessed.
Many IoT platforms offer additional features and customization. For instance, a platform can offer cloud services and a plug for connecting additional enhancement modules. The company’s software development kit (SDK) allows developers to build customizable mobile applications to interact with the circuit boards and the cloud and integrate with whatever third-party hardware kit makes the most sense for the business and the application.
IoT platforms can also vary in what data gets reported. Manufacturers most likely want an IoT platform that uses edge computing. This creates a profile for "normal" behavior of the object and then only reports the exception occurrences, which means instead of sifting through endless amounts of data, company operators are alerted in real-time of unusual movements or conditions that could signal a problem. [subhead]
Big Data, easy integration
IoT promises a lot of benefits for manufacturers, but the benefits luckily aren’t matched by the price or integration time—IoT doesn’t require hiring a team of tech experts or building a system from the ground up. Many IoT platforms are easily scalable and offer end-to-end integration solutions that encompass on-premise, legacy and cloud systems and platforms. Many also operate under a Platform as a Service model, which makes integration cost-effective and quickly puts fully customized data into the hands of the customer.
Capital equipment can last years, so it may be impractical to purchase new equipment embedded with smart technology. Integrating with an IoT platform using small sensors fills the gap, enabling manufacturers to get the benefits of today’s technology without investing in entirely new machinery.
Before integrating with an IoT platform, manufacturers should identify potential problem spots to determine what data would be most useful and ask questions such as:
- What components or steps in the process cause the most trouble?
- What could potentially be automated that currently requires manual monitoring?
Questions like these are a good place to start when deciding how to start with IoT. Manufacturers should also think through what capabilities are needed in an IoT platform. Communication protocols vary, as does pricing, customizability and flexibility. The technology landscape is evolving and manufacturers should look for an IoT provider that can keep up.
Guy Weitzman is the CEO and co-founder of Atomation, a U.S.-based company that connects any object to the internet, making the object alive, smart and able to communicate previously unavailable data. Guy learned the skills of an entrepreneur during his 12 years serving as a military intelligence technology officer in the Israel Defense Forces. Prior to founding Atomation, Guy was a director of business development and operations and a director of M&A at an international investment firm. He has more than 10 years of experience in product, operations and business development in the internet and mobile fields. Edited by Emily Guenther, associate content manager, Control Engineering, CFE Media, firstname.lastname@example.org.