Predictive maintenance
Instead of replacing machinery parts at regular intervals to minimize the risk of failure, technicians can use predictive maintenance to monitor the condition of equipment and replace parts only when necessary.
IoT in manufacturing: 8 use cases, technologies, and examples
September 19, 2023
IoT in manufacturing is the use of connected sensors and devices to automate and optimize production processes. By gathering data from sensors in real time, manufacturers can make more informed decisions about managing resources, improving product quality, reducing costs, and increasing efficiency.
At Itransition, we offer a complete suite of IoT-powered solutions and services for the manufacturing industry, enabling our clients to transform their operations and get a competitive advantage.
The state of IoT in the manufacturing market
Nowadays, there is a gamut of innovative technologies that manufacturing companies can use to enhance operational efficiency. Artificial intelligence, 5G, various automation solutions, and cloud platforms are poised to change manufacturers’ business models for good. However, IoT lies at the core of Industry 4.0 and can generate the most value in manufacturing.
Scheme title: IoT in manufacturing market size, 2021 to 2030 (USD billion)
Data source: globenewswire.com — IoT in manufacturing market size to reach USD 1.52 trillion by 2030
$5.5 - $12.6 trillion
will be added in value globally by IoT in manufacturing by 2030
- McKinsey
26%
the largest share of all IoT applications in factory settings by 2030
- McKinsey
8 IoT use cases in manufacturing
IoT offers manufacturers numerous opportunities to innovate their operations and gain a competitive edge. Here are eight examples of how businesses in the manufacturing industry can leverage IoT technology:
Benefit
By utilizing smart sensors similar to those used in smart offices, edge computing, advanced machine learning algorithms, and computer vision in manufacturing, industrial companies can accurately predict equipment failure and make real-time adjustments to ensure that production flow is uninterrupted.
Energy management
With the help of an IoT-enabled energy management system, manufacturers can have a comprehensive view of energy consumption per unit of equipment or plant 24/7. Wearables, sensors and other IoT devices can collect this data throughout all the manufacturing processes.
IoT allows manufacturing companies to save costs by reducing transformer losses and standby loads and preventing peak loads. What is more, an automated monitoring system helps manufacturing organizations streamline energy audits due to optimized data collection and reporting.
Benefit
This allows manufacturers to identify areas where energy is being wasted and make changes that reduce operational costs and environmental impact.
Digital twin
Digital twin in manufacturing is a virtual representation of what is happening inside the factory. A myriad of sensors installed across the facility collects product characteristics data, including asset color, thickness, and temperature, allowing engineers to adjust production systems and optimize assembly in near real-time.
Benefit
The implementation of a digital twin can lead to cost reduction, productivity increase, and product quality improvement.
Real-time product enhancement
With the help of IoT-enabled sensors, manufacturers can remotely analyze product performance data and tune parameters even when the product leaves the production facility. With IoT, manufacturers can perform over-the-air updates, remotely calibrating software and firmware even after the product has been released. This way, they can fix bugs, introduce improvements, or enhance the solution's capabilities without physically accessing the product.
Benefit
This allows manufacturing companies to enhance product performance, significantly boosting customer loyalty and satisfaction.
Supply chain optimization
Manufacturing companies can optimize supply chain management with the help of smart sensors. By equipping products or machines with RFID/NFC tags or QR codes, organizations can track their goods from raw materials to production stages. What is more, IoT-enabled asset tracking systems can be used to monitor and identify discrepancies between actual and expected stock levels.
Benefit
This allows manufacturers to accurately track their industrial assets and identify bottlenecks in the production process.
Quality assurance
Manufacturers can use IoT-powered sensors to monitor many parameters, including pressure, temperature, and humidity, to ensure that goods meet set quality standards. By automatically examining product quality during the production process instead of when it's finished, organizations can considerably improve product quality while saving time and money.
Benefit
This allows manufacturers to reduce the risk of product returns, boosting customer satisfaction and loyalty.
Safety improvement
By equipping workers and machines with sensors, manufacturers can detect any potential safety hazards in near real-time. For example, manufacturers can quickly identify the presence of hazardous chemicals or high temperatures in a factory environment and take appropriate actions to ensure worker safety. In addition, preventive maintenance practices can be triggered if sensor readings suggest a machine is malfunctioning.
Benefit
As a result, manufacturers can reduce the risk of costly accidents or lost time.
Data-driven decision making
Companies can use the vast amount of data generated by IoT sensors to gain a better understanding of their production process and customer demand.
Benefit
Relying on data, manufacturing businesses make better decisions about resource allocation, improve operational efficiency, and adjust pricing strategies accordingly.
Ready to enter the new era of production efficiency with IoT?
Examples of IoT in manufacturing
Tenaris
Tenaris, a global manufacturing organization that produces steel pipes, has joined forces with ABB, a multinational producer of automated electrical equipment, to streamline the maintenance of more than 400 electric motors that drive rolling mills at their Italian plant.
ABB installed smart sensors on each of the plants’ motors that send performance data to a dedicated platform so that the Tenaris engineering team could monitor the condition of all motors in real time.
On top of that, when certain metrics go above the established threshold, the system automatically sends notifications to the maintenance team. Ettore Martinelli, Tenaris Maintenance Engineering Director, claims that ABB’s solution does a perfect job at detecting excessive motor vibrations, which is often a sign of failure. Similarly, smart sensors have proven to be effective in detecting voltage anomalies that indicate the likelihood of a short circuit.
Unilever case study
In 2019, Unilever partnered with Microsoft to develop a digital twin of its production facilities. As a result, the majority of machinery in Unilever factories is now constantly sending data to an IoT-based platform, providing engineers with much better control over the operations. For example, in one instance, the digital twin is using data to assess how long it takes to produce a bottle of shampoo, which helps engineers to optimize the manufacturing process. Similarly, the digital twin now helps control the moisture levels in Unilever’s soap-making machine, enabling consistent product quality.
After adopting a digital twin in its facility in Brazil, Unilever saves $2.8 million yearly due to reduced energy consumption and increased productivity.
Volkswagen
For over eight decades, the Volkswagen Group has been a cutting-edge automaker in Europe, producing 11 million cars yearly. The Group recently developed the Volkswagen Industrial Cloud in collaboration with Amazon Web Services (AWS) to modernize its automotive manufacturing and logistics processes. The Volkswagen Industrial Cloud brings together data from machines, plants, and various systems located across 120+ factory sites with AWS IoT services. The Volkswagen Industrial Cloud has the potential to elevate productivity by 30%, reduce factory costs by 30%, and save €1 billion in supply chain expenses.
Sealed Air
Sealed Air is a global manufacturer of protective and specialty packaging for consumer goods and cleaning solutions. The company wanted to gain new insights into one of its products to increase energy efficiency and improve compliance. To do this, they turned to ThingLogix to develop an IoT solution for their SoftCare line of soap dispensers. With the help of IoT-enabled soap dispensers, custodial crews know when exactly a device is getting low on soap and know how much soap is used by employees. This led to a decrease in human involvement when restocking and improved employee hygiene compliance.
IoT solution architecture
A сommon IoT solution consists of sensors and computing devices interconnected through a dedicated network. While there is no universally accepted standard for an IoT solution architecture, in most cases, the architecture includes the following components:
Sensors
Cameras, temperature sensors, motion detectors, and other types of IoT sensors form the foundation for any successful industrial IoT solution. Depending on the application, they are responsible for detecting movements, collecting environmental data, or providing insights into equipment conditions.
Edge devices
Edge devices are computing capabilities that sit between embedded systems and cloud or premises-based servers. Edge devices can process data locally, analyze it in near real-time, and make decisions without sending it to the cloud for analysis.
Cloud solutions
Cloud solutions are used to store, process, and analyze large amounts of data collected from sensors. Importantly, the cloud plays a pivotal role in making AI-based data analytics accessible on a large scale.
Embedded systems
Embedded systems are single-purpose computing devices that can significantly enhance production efficiency by handling day-to-day tasks on their own. A machine vision system responsible for quality control is a common example of an embedded system in the manufacturing context.
Human-machine interfaces
Human-machine interfaces (HMIs) are used to communicate data between machines and humans. For instance, HMIs can be used to visualize the performance metrics of connected equipment or interact with a machine vision system during an inspection.
Best IoT cloud platforms we use
The future of IoT-based systems in the manufacturing sector is closely associated with cloud computing. Cloud-based IoT platforms are designed to capture data and provide insights that can be used to make more informed decisions. Here are some of the best IoT cloud platform solutions for manufacturers:
AWS IoT
AWS IoT offers a broad range of services that make it simple to connect devices to the cloud and process data securely on a global scale. AWS provides an easy-to-use interface so you can quickly get your connected solution up and running.
Data services
- AWS IoT Events for event monitoring
- AWS IoT Analytics for data analysis
- AWS IoT FleetWise to process vehicle data
- AWS IoT SiteWise to process facility data
- AWS IoT Twin Maker for building digital twins
Control services
- AWS IoT Core for connecting IoT devices
- AWS IoT Device Advisor for device validation
- AWS IoT Device Defender for data security
- AWS IoT Device Management to control IoT devices
Device services
- AWS IoT Device SDK to connect devices to AWS
- AWS IoT ExpressLink to maintain hardware modules
- AWS IoT Device Tester for automated testing
- AWS IoT Greengrass to manage edge devices
Azure IoT
Azure IoT is a comprehensive, enterprise-grade cloud platform for securely connecting, managing and analyzing data from millions of devices. You can use Azure IoT to build complete IoT solutions that span across the cloud and edge.
- Azure IoT Central for accelerating IoT development
- Azure Digital Twins for IoT modeling
- Azure Time Series Insights for data analysis
- Azure RTOS for establishing IoT connectivity
- Azure SQL Edge to enable IoT and IoT Edge deployments
- Azure IoT Edge to offload artificial intelligence and analytics workloads to the edge
- Azure Sphere for connecting MCU-powered devices
- Azure IoT Hub for secure device management
Achieve the most ambitious production milestones with IoT in manufacturing
IoT implementation challenges and best practices
Challenge/inefficiency
Solution
Focusing on a single application
Challenge/inefficiency
Solution
Unlike many other technology implementations, IoT systems can prove truly efficient only when applied in multiple use cases. In other words, it’s better to implement many IoT tools than pick the most potent technology and focus solely on it. Importantly, this doesn’t mean that you need to implement all possible IoT use cases at once but to take a holistic approach.
Lack of change management
Challenge/inefficiency
Solution
One of the most common traps that manufacturing organizations fall into is treating IoT digital transformation as a solely IT project. The implementation of the first use cases implies a rather serious working process transformation for many employees and, most importantly, a shift in their attitude to work. This is why change management should be among the top preparatory measures when embarking on the IoT transformation journey.
Overpreparation
Challenge/inefficiency
Solution
For the majority of manufacturing organizations, any digital transformation initiative is a sign of a new beginning. Understandably, it’s very tempting to ensure 100% readiness in terms of technology, talent, resources, etc. But in fact, it’s far more feasible and effective to approach transformation head-on, failing and learning as you go. Not to say that you don’t need to prepare at all. Instead, the preparation should center around establishing a dedicated transformation team, which utilizes proven transformation management practices.
Lack of security
Challenge/inefficiency
Solution
The implementation of IoT solutions in the manufacturing process requires a certain level of security to protect it from external threats. This means companies must use secure authentication protocols when connecting devices, develop comprehensive access control policies, and monitor all data flows. It’s also critical to ensure that these security measures are regularly tested and updated accordingly.
Related services to build a smart factory
The digital transformation of manufacturing, often referred to as Industry 4.0, is a rapidly growing sector driven by advances in technology such as the Internet of Things (IoT), artificial intelligence (AI), cloud computing, data analytics and robotics. These technologies provide new ways for companies to optimize their production processes and remain competitive in an ever-changing market:
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Artificial intelligence
AI provides manufacturing facilities with the ability to analyze data collected from IoT devices in order to identify patterns, anticipate problems, and take preventive actions. This helps increase efficiency, reduce downtime, improve asset management, and achieve the desired KPIs.
Real-time data analytics
By bridging the gap between data collection and analysis, real-time data analytics can help factories prevent risks, anticipate disruptions, and make adjustments that bring immediate improvements in day-to-day workflows.
Data warehouse modernization
Data warehouse is a critical component of the digital transformation process. As factories collect more and more data from IoT devices, it is essential to have an infrastructure that enables them to store, access, and analyze this data in the most efficient way.
Cybersecurity
Poorly configured IoT sensors and edge devices can become hacking targets, so factories should ensure that their networks are secure and properly monitored. To protect their ecosystems from malicious actors, factories should develop robust cybersecurity measures and regularly monitor for potential breaches.
The new era in manufacturing led by IoT
The IoT adoption in manufacturing environments is revolutionizing the industry. It enables factories to optimize production processes, improve asset utilization, increase uptime, and anticipate disruptions. With the help of Itransition’s expertise in IoT development and data science, factories can embrace the Industry 4.0 revolution with confidence. Our team will provide you with a tailored solution to make sure that your factory is ready for an era of unprecedented transformation. Contact us and start your journey toward digital transformation today.
FAQ
How is IoT used in manufacturing?
IoT is used in manufacturing to analyze data from sensors to automate and optimize production processes.
What are the examples of IoT devices in manufacturing?
IoT devices used in manufacturing include smart sensors, edge devices, industrial robots, and RFID tags. These devices are used to monitor and collect data from production lines, detect potential problems in the supply chain, and coordinate automation processes across plants.
Why is IoT important in the manufacturing industry?
IoT is important in the manufacturing sector because it enables companies to improve production efficiency, reduce operational costs, increase quality and safety, create new services, and drive innovation. With IoT devices providing real-time data and insights into manufacturing operations, manufacturers can make informed decisions and, ultimately, improve bottom lines.
What is the future of IoT in manufacturing?
The future of IoT in manufacturing lies in the convergence of connected devices and systems, AI, big data analytics, and digital twin technologies. In the future, manufacturing companies will rely more on automation and data-driven insights to optimize manufacturing operations, increase productivity, reduce waste, and improve safety. IoT will enable companies to create new revenue streams through the development of new services based on the real-time data gathered from connected devices.
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