IoT in Manufacturing

The Factory of the Future: Decoding Top 5 Industrial IoT Use Cases Transforming the Manufacturing Industry

Resilience is the bedrock of organizational excellence. Today, leading manufacturing industry firms are quickly adopting digital solutions across shop floors and piloting IIoT initiatives on a large scale in the wake of the coronavirus pandemic, which highlighted the need for digital management tools and connectivity for business resilience and continuity.  

Today, IIoT solutions have become the cornerstone of various manufacturing processes, and their evolving use cases are driving significant operational and financial benefits. Companies can now experience reduced downtimes, streamlined outcomes, substantial cost savings, and redefined efficiency levels. 

The following article looks at five top industrial IoT development services use cases making waves. 

Industry Overview

Exorbitant logistics costs, shortage of skilled workers, and the acute complexity of the global supply chain are a couple of challenges that have sent the manufacturing industry into a tailspin. So, most incumbents are encouraged to turn to distributed manufacturing to stay afloat. 

Distributed manufacturing entails the decentralization of manufacturing processes. Leaders build a network of geographically dispersed units or hire industrial iot companies to stay close to functional regional markets, attract the best talent, enhance bottom-line performance, and cut operating costs. While such an approach seems logical, it cannot be denied that distributed manufacturing poses difficulties as far as the control, coordination, and compliance of remote manufacturing processes are concerned.

Before COVID, manufacturers brushed aside the need to embrace integration technologies across shop floors and left significant value on the table. However, as soon as the pandemic hit and unleashed its impact by pulling the plug on industrial activity, one area of investment became clear: the Industrial Internet of Things, also known as IIoT. The associated  technologies reflected a new era of opportunity, helping manufacturers gain visibility and control over their remote operations and assist with adjusting production capacities in response to market disruptions through real-time data. IIoT paved a new path where productivity and sustainability weren’t at odds. 

Cut to the present; the manufacturing industry has come a long way since the first wave of COVID-19-induced lockdowns. Leaders are earnestly investing in digital technologies to stay competitive. And while challenges have reduced a bit (the manufacturing sector continues to bear the brunt of high logistics costs, demand and supply imbalances, trade war effects, and skilled labor gaps), the technology of IIoT is making a solid case for itself, exhibiting the potential to build organizational resilience in the face of catastrophe events. 

In a Nutshell: What is the Industrial Internet of Things (IIoT)?

With complex shop floor operations, extended supply chains, and resources spanning a large geographical area, manufacturers must have a deep, real-time business view of what occurs where, when, and why with the right data to support strategic decision-making. Understanding where performance is lagging and what needs to be done to fix and improve it can help them enable new efficiencies, outsprint risks, and future-proof value generation. 

Industrial IoT (IIoT) is a network of interconnected machines and systems that allow data to be collected from processes and analyzed in real-time. The insights generated revolutionize the way businesses operate by providing them with a 360-degree view of their operations. By understanding the behavior of machines and systems, companies can make better decisions and optimize their processes, ultimately leading to increased efficiency and productivity.

IIoT in Manufacturing: Growth and Adoption in Numbers

The IIoT market is growing exponentially, helping manufacturers break legacy barriers and build smart factory software solutions that inspire productivity and new pools of profitability. By 2024, the market for IIoT Platforms for the manufacturing industry is forecast to grow from $1.67B to $12.44B, growing at a compound annual growth rate (CAGR) of 40% over the next seven years. As per another report, it is estimated that the market for connected products will grow from $519 billion to $685 billion, and according to other estimates, IIoT-based predictive maintenance solutions could reduce factory equipment maintenance costs by 40% and generate $630 billion in economic value annually by 2025.

So, to sum it all up, IIoT is instrumental in transforming the manufacturing industry from its core and is set to empower and accelerate business outcomes in various dimensions. While what comes next remains unexplored, let’s take a closer look at five top IIoT use cases, helping incumbents make significant strides. 

Getting hands on the current article about IIoT in manufacturing, read another article about how IoT is evolving in Industrial Sphere.

Top Industrial IoT Use Cases In Manufacturing

iot use case


1. Location Tracking

IIoT provides a substantial value shift by helping manufacturers ensure that machinery and assets on shop floors are where they are supposed to be, operating within safe thresholds and being used as intended. With IIoT-based sensors and edge connectivity devices, organizations can gather insights in real-time and accurately geo-locate or track devices. Real-time location data reduces confusion, allowing staff to find what they need faster and with less effort. Location tracking based on modern GPS systems, RFID tags, and other wireless technologies can provide organizations with rapid information about the whereabouts of their assets.

Logistics companies use IIoT-based tracking solutions to collect comprehensive vehicle data and track indicators such as fuel consumption, temperature, and driver identification. Such devices can also be deployed to inform workers well-informed about manufacturing facilities and communicate the details about where materials are located. 

2. Predictive Maintenance

Predictive maintenance is one of the most critical aspects of maintaining a successful shop floor. By understanding the conditions that led to a failure and identifying potential issues before they happen, manufacturers can prevent costly downtime and equipment failures. By deploying sensors and capturing data for insights, organizations can analyze performance metrics, make real-time predictions, discover anomalies, and send alerts to dodge possible crises and safeguard machinery and the workforce. This allows for better decision-making and faster response times, ultimately delivering cost and efficiency benefits up and down the supply chain.

With IIoT at the forefront, service calls can be reduced to a minimum; operational efficiency can take off; costs can be reduced; and a great deal of time can be saved, especially in the current scheme of things when 31% of the assets are deployed in the field. 

3. Warehouse Management

With IIoT, organizations can input the data, extract insights, hunt down inefficiencies, and instantly lay the groundwork for streamlined operations. Automated alerts and event reporting can allow companies to be notified immediately when there is a disruption in their supply chain or inventory and then take appropriate action. This will enable them to stay one step ahead of the competition and ensure that they can always meet customer demand. 

Sensors can deliver insights to help professionals on the floor keep needed consumables (fuel and lubricants) handy, avoid costly outages, and ensure that their equipment is continuously operating at peak performance. IIoT sensor technology offers a unique ability to track the condition of specific components—no matter where they are in the supply chain. This makes it incredibly valuable for companies and their customers, who can order replacements ahead of time if necessary. 

4. Environmental and Workforce Safety,

The Environmental Protection Agency employs IoT sensors to track the condition of resources and products, such as the water supply, in real-time, identify exceptions, and enable a more rapid, effective response to keep hazards at bay. IIoT represents a convergence of physical, process, and data domains, offering significant opportunities for cost savings and increased efficiency in the areas of economic, environmental, and workplace safety regulations. 

Remotely monitoring the quality of raw materials and finished products is essential for ensuring that the manufacturing plants produce safe products. However, traditional monitoring methods are often time-consuming and require physical visits to the plant. Thanks to the growing popularity of the Internet of Things, however, chemical processing plants and pharmaceutical firms can deploy sensors to monitor the quality of their materials from a distance. This way, they can avoid any potential disasters or injuries to employees on the floor and ensure that their products are of the highest quality. Similarly, real-time notifications can motivate quicker responses, reducing the likelihood of mishaps that could harm the product if left unchecked for an extended period.

The fact that remote quality monitoring is a relatively new concept means that there aren't readily available off-the-shelf devices and services for every application. Organizations may be required to outsource industrial IoT development services to get custom solutions to measure metrics relevant to them.

5. Energy Consumption Optimization

Optimizing energy consumption is a less glamorous but one of the most critical industrial IoT use cases. Adding Internet of Things connectivity to industrial machinery, HVAC systems, and other systems that consume a lot of energy can help minimize energy consumption. Internet of Things (IoT) sensors can identify peaks and valleys in energy use and automatically alter activities to utilize the least amount of electricity feasible.

Industrial IoT devices enable organizations to significantly cut the costs related to regulatory compliance by remotely monitoring critical assets. Here are a few illustrations:

  • Equipment Tracking: Embedded sensors can offer businesses accurate, real-time information about the location of expensive machinery—cranes and bulldozers, to name a few—and the usage and maintenance requirements of such machinery.
  • Emission Monitoring and Controlling: Through emissions monitoring solutions across a fleet of emission-producing assets, businesses can keep tabs on areas with high concentrations of hazardous pollutants and ensure that employees do not visit these areas without the required protective equipment.
  • Asset Monitoring: Overheating equipment, excessive vibration, or equipment that harnesses strong electric currents constitute a safety concern to personnel, especially if they are unaware of the danger. Thanks to the Internet of Things, it is feasible to operate assets from a distance, allowing managers to restrict particular functions or shut down equipment to avoid injury.
  • Logistics Management: Intelligent sensors may optimize workflows by automating orders, optimizing the location of machinery and personnel, and advising routes to transport equipment and supplies.
  • Workers’ Protection: Wearable gear like hard helmets, vests, and network-connected boots transmit workers' geolocation coordinates to a cloud-based data analytics service to improve overall worker safety. The capacity to monitor equipment for unsafe operations or breakdowns can also help prevent fires, malfunctions, leaks, and other problems that endanger worker safety in a manufacturing environment.

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IIoT Adoption in Manufacturing: What are the Pain Points

IIoT has opened new horizons of growth and value for manufacturing companies. Several organizations are making a concerted effort to identify where IIoT fits across their complex processes, what’s the correct adoption route, and how to scale initiatives for ROI.

Unfortunately, only a few manufacturers have been able to maximize IIoT’s impact and harness its full potential. There are a host of technical and operational factors to blame. 

  • Technical Bottlenecks:

Heterogenous, maze-like application landscapes, which are challenging to plan, configure, and manage

More confusion, less clarity on what functions are ripe for IIoT-led transformation

Less understanding about what functions need what technical systems (for example, ERP or IIoT)

Constant wrangling over which IIoT systems should be deployed where—at the site, in the cloud or on the edge.

  • Operational Bottlenecks: 

Lack of prerequisites and requisites to enable the broader application of IIoT use cases

Leadership, which is non-committed to mobilizing resources for transformation

Employee mindsets that are resistant to change and pose extreme cultural barriers to innovation

Talent gaps and shortage of skilled professionals to execute the right adoption and scaling strategy


The Path Ahead for IIoT in Manufacturing

IIoT is taking a pole position with respect to what technologies are uniquely positioned to reimagine the manufacturing industry for the better. It is sowing the seeds of a future where “smart manufacturing” will be the order of the day. 

IIoT allows a single view of the factory operations and helps leaders monitor, manage, control, and coordinate every aspect of supply chains‒anytime, anywhere. Advancements in IIoT will carve the way for more advanced, more insightful solutions with AI and Machine Learning at the core. These technologies will enable the smart factory to run on operational intelligence and provide an impetus to close collaboration between humans and robots.

But every rose has its thorn. With remote data access, security concerns will naturally mount, compelling manufacturers to pump investments into robust defense systems and of course, the professional industrial iot companies to handle the complexities. Currently, security measures on factory shop floors aren’t as mature as they should be. IIoT will pressure manufacturers to recognize security as a top priority to stay resilient in the age of sophisticated cyberattacks.