IoT in Manufacturing: Applications and Upcoming Trends

Written by: Emily Himes

Read Time: 8 min

What is IoT in manufacturing?

Industrial companies are increasingly prioritizing digital transformation investments, yet many struggle to scale because they haven’t focused enough on defining the business goals that these investments should be supporting. While digital transformation can take many different shapes, the Internet of Things (IoT) is a common foundational technology. Most Industry 4.0 initiatives that rely on delivering data—from connected devices and sensors to connected people, products, and processes—use the IoT to power digital transformation. By using IoT platforms, manufacturing companies can connect, monitor, analyze, and take informed actions based on live data. This transformative approach enhances efficiency, maximizes revenue growth, and reduces costs across the entire manufacturing landscape.

As the technology and utility of the IoT have matured, the applications have become more diverse, and the use cases more impactful. As such, the IoT has followed a hype cycle from a ubiquitous buzzword to a true foundational technology that has become accepted as a necessary part of digital transformation efforts—and critical for keeping pace in an increasingly challenging market. To understand the current state of IoT and emerging possibilities, it’s useful to look back and understand the circumstances that gave birth to the Internet of Things.

History of IoT in manufacturing

The history of IoT in manufacturing began with the invention of the programmable logic controller (PLC) in 1968, which allowed for detailed control of individual elements in the manufacturing chain. In 1975, Honeywell and Yokogawa introduced the world’s first distributed control systems (DCS), which enabled flexible process control throughout a plant. As IT systems roared ahead powered by internet/extranet/intranet connectivity, OT systems quietly (and admittedly more slowly) followed suit as opportunities to use data for automation, information, and control emerged. If IT and personal applications of the internet were a revolution for OT and manufacturing, the IoT has been more of an evolution.

The IoT as we know it today emerged in the early 2000s. By connecting machines that were once isolated and giving them a way to communicate, analyze data and optimize performance, the IoT began to enable a world in which operators could make informed decisions using real-time data. Clearly, a set of factors put some limitations on the pace of growth. These headwinds include the sophistication of both edge computing (e.g. the ability processor embedded in factory machines to run algorithms and store data) as well as cloud computing’s ability to effectively (and securely) manage computation. Connectivity had also created perceptions that only net-new machinery could be eligible for IoT-enhanced operations; for organizations dependent on a reliable fleet of brownfield equipment and machinery, the IoT was simply a sales pitch that had no real-world relevance.

Industry 4.0 is the next step in the evolution of manufacturing, and redefined the expectations held of machines’ ability to connect with each other to create efficiencies and drive growth. Fueled by a need to boost efficiency, become more agile to respond to market unpredictability, and improve quality, manufacturing organizations of all stripes are now embracing Industry 4.0—and reaping the impactful benefits of digital transformation initiatives.

As the capabilities and reliability of the cloud and edge computing matured, and after-market connectivity solutions allowed previous siloed machines to become IoT-ready, organizations recognized that the IoT wasn’t merely a possibility, but that it was a sought-after competitive advantage. With more organizations pursuing IoT-driven solutions increasingly expansive solutions and value, competitors took notice. Industrial companies could see clear examples of the IoT’s transformative impact and benefitted from clearly defined roadmaps to IoT success.

Today, the IoT has come into its own as a must-have part of digital transformation for manufacturers, and most organizations would now view the absence of IoT technology as a significant disadvantage.

How is IoT used in manufacturing?

IoT solutions are integral for optimizing operations and enabling productivity to keep pace with market opportunities and challenges. The use of interconnected devices and sensors gives manufacturers real-time data from various stages in production, enabling predictive maintenance to minimize downtime and reduce costs. IoT-connected manufacturing environments also provide actionable insights to optimize production processes and resource utilization, fostering continuous improvement and operational excellence. By leveraging connected devices and data analytics, manufacturers can unlock new levels of efficiency, agility, and innovation. In total, the IoT has redefined levels of productivity, efficiency, safety, and quality that simply could not be achieved without it.

What are the benefits of IoT in manufacturing?

In the dynamic manufacturing landscape, the integration of IoT solutions represents a paradigm shift, offering impactful benefits that extend beyond simple operational improvements. From mitigating the risks associated with downtime to optimizing maintenance protocols, ensuring stringent quality control, enhancing safety measures, and ultimately reducing costs, IoT solutions serve as indispensable tools across the entire manufacturing enterprise.

Increased productivity and efficiency

Finding new ways to improve efficiency across the value chain is more essential than ever. Whether manufacturing organizations are looking to boost the performance of equipment on the shop floor or help employees work smarter in the factory, IoT solutions allow for improved efficiency by:

  • Accelerating changeovers by up to 70%

  • Reducing unplanned downtime by up to 50%

Unplanned downtime poses serious threats to industrial profitability. From producing waste to interrupting supply chain networks to equipment safety hazards, machine downtime can create impactful downstream impacts. With IoT solutions, manufacturers gain real-time data visibility into equipment performance and usage data to fix problems before they result in more costly interruptions.

Improved maintenance

In industries reliant on machine performance, encountering maintenance challenges can disrupt operations and compromise safety. Predictive maintenance is crucial for ensuring machine reliability and safety. IoT-based maintenance systems make use of data-collecting sensors to gain insights from machines and equipment about operating conditions and use analytics to pinpoint potential problems or failure risks.

Better quality control

IoT solutions have a major impact on quality control by enabling real-time monitoring and defect detection throughout the production process. By continuously monitoring equipment performance metrics, IoT solutions can detect red flags that indicate potential failures. By addressing these issues proactively, manufacturing organizations can avoid unexpected downtime and ensure that machinery operates as intended, resulting in consistent product quality.

Enhanced safety

Real-time IoT feedback creates higher levels of safety and compliance by combining an audit trail of checkpoints within digital work instructions with live production data. IoT solutions help monitor and interpret important safety trends in factories, including injuries, near misses, malfunctions, accidents, chemical damages, and property damage. Further, these issues are notoriously underreported, meaning safety data is often skewed and unrealistic. Without comprehensive, real-time data, it is impossible to anticipate where risks are emerging, or whether a malfunction is about to occur. With IoT solutions, it’s easy to gather live data from factory equipment to get insights into worker safety. More real-time, accurate data allows for safer decision-making and stronger regulatory compliance and has a positive impact on worker health and well-being.

Reduced costs

IoT solutions help manufacturing leaders leverage data from connected products and systems to increase productivity, lower costs, and improve efficiency. By harnessing real-time insights from connected devices, manufacturers can identify areas of inefficiency, minimize downtime, and optimize production processes, ultimately resulting in significant cost savings.

IoT use cases in manufacturing

The integration of IoT solutions in manufacturing triggers operational optimization and efficiency. From enabling remote monitoring for proactive equipment fixes to facilitating predictive maintenance strategies, IoT emerges as a key element of innovation, transforming various aspects of manufacturing operations.

Predictive maintenance

Predictive maintenance continuously analyzes the condition of connected assets and equipment to reduce the likelihood of unplanned downtime or machine failure. By using real-time data collected through the IoT, predictive maintenance continuously analyzes the condition of equipment during normal operations to reduce the likelihood of failure, helping achieve:

  • Decreased downtime: Technicians can detect issues in advance and resolve problems before equipment failure occurs.
  • Greater worker productivity: Since maintenance is planned around workers’ schedules, there is no need to disrupt productivity for unexpected malfunctions or breakdowns.
  • Reduced field service costs: Service departments can generate major cost savings and increased ROI by anticipating machine maintenance.
  • Improved product design: Designers use vital IoT data in product development.
  • Heightened worker safety: By predicting when a malfunction may occur, service can be completed before a machine becomes dangerous.

Quality control

By using IoT sensors to continuously monitor production and detect defects in real-time, manufacturers can adjust before faulty products come off the line. This practice reduces costs in several ways: first, it lowers the risk of making faulty products, allowing manufacturers to save money on costly recalls and repairs. Automating the quality control process also helps reduce the need for manual inspections, limit waste, and boost efficiency—meaning organizations can increase productivity without increasing costs.

Worker safety

IoT solutions play a crucial role in enhancing worker safety within manufacturing environments by providing real-time monitoring and predictive analytics. Machinery equipped with sensors can track vital signs, detect hazardous conditions, and alert workers and supervisors to potential dangers. By leveraging these technologies, manufacturers can create safer work environments, reduce workplace injuries, and ultimately foster a culture of safety and productivity.

Workforce efficiency

Worker efficiency is a key component of asset efficiency. IoT data empowers plant floor operators to increase efficiency by offering real-time visibility into asset performance. This allows operators to predict maintenance needs and fix problems before they cause downtime. Additionally, implementing processes such as Single Minute Exchange of Dies (SMED), which reduces changeover and setup time, allows for quicker changeovers and greatly reduces unnecessary downtime.

Performance management solutions

Performance management solutions deliver the insights needed to make the most impactful changes in the factory. They provide real-time, closed-loop problem-solving capabilities, empowering manufacturing teams with timely insights about bottlenecks, root causes, and the improvements that CI initiatives deliver. Based on a single metric of time, performance management solutions enable manufacturing organizations to compare and establish the most efficient priorities for improvement opportunities. This allows for the recapture of finite production hours lost in current processes, potentially increasing effective time up to 20% or more. Subsequently, process improvements can be validated by tying them directly to the plant P&L.

IoT trends in manufacturing

Edge computing

Edge computing enables processing closer to data sources, such as IoT devices, rather than relying solely on centralized cloud servers. The practice is gaining popularity due to its agility and real-time processing capabilities. In smart factories, it can closely link data processing with the equipment itself, enabling real-time analytics and decision making. Manufacturing organizations use the low-latency processing provided by edge computing to improve efficiency and agility.

Smart factories

Factories are increasingly being relied upon to handle more complex operations to serve a wider range of products, meaning industrial companies are turning to new digital solutions as they rethink how their physical products are engineered and manufactured. In fact, 92% of industrial companies are executing digital transformation initiatives with goals of achieving:

  • Reduced costs to improve efficiency
  • Exponential growth through product innovation
  • Heightened quality and customer engagement

AI and IoT

AI is essential in IoT, as it enables devices to collect and analyze data in real time, enabling smart decision-making, task automation, pattern prediction, and issue detection, which ultimately improves systemic productivity and accuracy. AI also helps automate tasks, predict patterns, and detect problems in IoT systems by analyzing data that can then help improve the efficiency and accuracy of connected devices.

Operational efficiency

IoT integration in manufacturing streamlines operations, from supply chain management to factory floor monitoring, optimizing resource utilization and minimizing downtime. By leveraging real-time data insights provided by IoT devices, manufacturers can proactively address maintenance needs, enhance equipment performance, and ensure a seamless workflow. This focus on operational efficiency empowers manufacturers to achieve higher productivity levels and maintain competitive edges in rapidly evolving markets.

Connected workers

In today's fast-evolving manufacturing and service landscape, it's becoming essential to connect frontline workers to help bridge the gap between skills and innovation and gain a competitive advantage. However, many organizations struggle to keep pace with the growing distance between skills and innovation. By connecting people, processes, and products, frontline workers can collaborate more effectively, familiarize themselves with modern solutions, and access critical information when and where it’s needed. Connected worker strategies offer improved on-the-job training, more effective digital instructions, seamless remote-team collaboration, while saving valuable time and resources.

The future of IoT in manufacturing

Industry 4.0 has already changed the way we live and work, but it will only continue to evolve from here. By combining the IoT with advancements in robotics and artificial intelligence, organizations are realizing a plethora of benefits, including data-driven decision making and heightened safety.


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Tags: Connected Devices Industrial Internet of Things Industrial Equipment Thingworx

About the Author

Emily Himes Emily is a Content Marketing Specialist on PTC’s Commercial Marketing team based in Boston, MA. Her writing supports a variety of PTC’s product and service offerings.