A Complete Guide to Leveraging Industrial IoT in Manufacturing

How to Implement Industrial IoT to Create Smarter, Faster, and Safer Production

Manufacturing is changing at an almost unprecedented pace, driven by technological innovations.

At the forefront of this great reshaping of the factory are IoT technologies and the increasing implementation of IoT in manufacturing. The future of industry—known as Industry 4.0—will rely on IIoT technologies that will create smarter, faster, and safer production.

Manufacturing Before IoT

Since its radical beginning in the late 18th century, the industrial revolution has completed three successful laps and is currently on its fourth.

From early innovations to Cloud Computing, here is a quick summary of the different phases of industrial revolutions. Before the industrial revolution, 80% of people were engaged in farming and agricultural activities. Today, less than 1% of the U.S. population farms. This major shift in work is due to the Industrial Revolution.


The first industrial revolution brought mechanization, which drastically changed the way goods were manufactured. Previously, most products were handmade. Then the wheel, cams, and shafts powered by steam engines began taking over the role of artisans.


The second wave came almost a century later in the form of assembly lines. Henry Ford and Charles Sorensen organized all the key elements of manufacturing systems, including man, machine, and tools. This arrangement debuted with the manufacture of the Model T automobile. It increased the speed and efficiency in which cars were built.


The third revolution was chiefly built around the concept of efficiency in manufacturing. The aim was to improve production flow by identifying and eliminating waste. This approach was very different from massification, which was the focus of the previous two revolutions. The massification movement began in Japan’s automobile industry in 1948 and later began to influence various other industries and regions in the 1990s.


The ongoing fourth industrial revolution encompasses internet and cloud computing-enabled interoperability of machines, lines, plants, systems, and enterprises. It involves a rather complex mesh of networks woven around technologies like artificial intelligence, cloud computing, machine learning, and IoT.

What Is IoT In Manufacturing?

IoT combines hardware, software, and the internet to create a more connected, smart, agile and responsive manufacturing environment.

Today, big data and the availability of inexpensive sensors and actuators have helped in the rapid proliferation of IoT frameworks across manufacturing industries.

The many possibilities of IoT applications in factories promise to solve key challenges manufacturers face today. For instance, IoT-based systems can efficiently facilitate production flow, automatically monitor development cycles, and manage warehouses and inventories.

IoT systems ensure the effective use of data that would otherwise lie dormant. The insights and analytics extracted from these data sets can be used to effectively improve business outcomes.


It is estimated that investment in IoT devices will
grow to $15 trillion by 2025
as more industries
look to harness the benefits of an IoT Solution.

The Benefits Of IoT Technologies

Industrial Internet of Things, or IIoT, refers to the billions of industrial devices equipped with sensors that are connected by the internet.

These sensors and actuators are used to collect data and drive artificial intelligence and predictive analytics. IIoT can be used to improve the manufacturing efficiency and quality of both a company’s product and production process.

The concept of IoT, if not the name, has been around since the early 1980s. Its first realworld device was reportedly a Coca Cola machine located at Carnegie Mellon University. The machine’s inventory could be accessed via the Internet to check if sodas were stocked and cold.

The actual term “Internet of Things” and IoT began to appear around 2008 to 2009. This was when more things than people were connected to the internet. Since then it has continued to expand in hundreds of new directions, particularly the industrial sector.

The economic viability of sensors and actuators along with the ever-widening bandwidth of the Internet sowed the first seeds of Industry 4.0.

Improve Visibility & Safety

IIoT is not only reshaping the dynamics of the manufacturing world, but also is consistently increasing productivity with reduced error rates. IIoT-enabled manufacturers are seeing significant improvement in visibility and safety standards.


Data from sensors is continually collected and interpreted with intelligent analytics to help managers make better decisions. The data from these sensors can help track and study trends that determine what is performing in optimal capacity, what is not, and what could be.

The insights gathered from these sensors can also be used to look for inconsistencies in products and processes along the assembly line, improving accuracy and reducing waste.


Manufacturing often involves high-risk work. Activities like brazing, welding, soldering, metal cutting, and rigging involve frequent exposure to radiation, gases, and magnetic fields. In fact, statistics show that workplace hazards lead to roughly 150 deaths per day in the United States alone.

Manufacturing firms have strict guidelines for safety. Workers are equipped with protective gear like helmet, goggles, and vests, depending on their jobs. IIoT wearables can supplement existing conventional protective equipment by improving worker visibility. Wearables can also monitor factors like posture, noise, fatigue, and physiological data. Features like fall detection alerts warn personnel about impending collisions. Data from these sensors are processed in a central repository where managers can get a clear understanding of factory floor safety.

The computer vision generated by these sensors can also detect and notify of any change in the optimal environment conditions. It can screen data collected by sensors to detect any anomalies on the factory floor as well as alert factory personnel when action needs to be taken to maintain a safe environment.

IIoT-enabled safety goggles can be equipped with augmented reality components. Wearers can get real-time feedback to see if they are complying with production practices. For example, an operator can reference visual aids for complex procedures. AR wearables can also help keep track of checklists or provide alerts for assistance. A voice recording feature can help personnel easily document an entire process

Reduce Costs

Cost reduction initiatives generally have multi-dimensional implications , and IoT implementation is no different. Manufacturing costs can be reduced in a number of ways. For instance, direct labor can be reduced by increasing in-process efficiency, while cost of quality can be brought down by a decrease in process variation. Similarly, the bottlenecks in processes are eliminated through line balancing, while uniform productivity and one-piece flow is improved by Load Leveling.

IoT platforms for manufacturing gather data to provide insights to engineers or operators, giving them enough lead time to take necessary actions. IoT in manufacturing can also help maximize production by offering data analysis and predictive maintenance to increase uptime, and avoiding downtime caused by parts failures and obsolescence.

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An established IoT platform can help immensely with cost reduction initiatives by delivering savings across various touch points or processes. It can reduce costs by improving the efficiency of the manufacturing line, reducing the cost through the identification of potential failures and preventing failures, and by minimizing waste. Based on the data gathered by IoT sensors, it can ensure that optimum throughput is maintained by consistently improving asset utilization.

Manage Supply Chains

Manufacturing industries are the leading investors in IIoT worldwide. Enterprise systems like Product Lifecycle Management (PLM), Materials Resource Planning (MRP), Enterprise Resource Planning (ERP), Supply Chain Management (SCM), and Manufacturing Execution Systems (MES) can contribute to improved savings and better returns by harnessing the power of IoT.

IoT-based devices can help manufacturers gather and feed important delivery information to critical systems like ERP and PLM. Manufacturers can leverage this to identify and correct critical supply chain issues, reducing cost, optimize yield, and improve efficiency.

One of the most widely used applications of industrial IoT is predictive maintenance. Effective implementation of predictive maintenance can help eliminate unnecessary downtime, reduce maintenance costs, and shield against financial losses.

Faster Product Changeover

‘Changeover’ is defined as the time from the last good part of one product run to the first good part of the next product run. This plays a significant role in process flexibility and capacity utilization. In the manufacturing world, the average set up time can be as high as one-third of total production time,and to compensate manufacturers tend to run larger batch sizes. Shorter set up times allow a wider variety of product mix at an optimal order quantity. Single Minute Exchange of Dies (SMED) is one of the critical components of lean manufacturing used to tackle longer setups. Even with an increased number of setups with a shorter batch run, the total downtime due to change over can decrease tremendously. IoT devices capture this information in real-time, helping manufacturers realize shorter setup times consistently. This feature can also help partly increase the Overall Equipment Effectiveness (OEE) for the asset.

Quick Turnarounds

Manufacturing environments are complex. In most cases, the difference between a successful and less successful operation lies in the resilience of the manufacturing line to quickly return to productivity after an incident or machine failure. This type of resilience is possible only when the right data is available to empower decisions for plant operations. This crucial information can help personnel retrace their steps to identify the cause of the problem and take corrective actions to ensure similar events won’t repeat. IoT can help develop meaningful insights that can speed recovery from incidents and mitigate future problems. Data extracted from IoT-powered sensors can be used to empower traditional analysis methods for process improvements. For instance, data can answer the 5 Whys backward step-by-step, making the root cause analyses more robust and analytic.

Fully - Custom Operations

IoT combined with field action sensors can help build configurable production environments which can respond quickly to changes in market conditions. These fluctuating demands can be treated as inputs to manage appropriate machine loading on production lines. Actuated sensors and data gathered through IoT sensors are connected over Internet protocol.

Educate Your Workspace

Any major enterprise-level implementation will require change management. Buy-in from the users and stakeholders is a critical component to ensure sustainable adoption. Implementation of an IoT system-based ecosystem is likely to be cross-functional with multiple layers. A critical part of the implementation involves educating and training the workforce to ensure they derive the maximum benefit from IoT. Because there are many IoT applications for different roles, it’s important that employees are educated on applications relevant to their jobs so they can gain the maximum benefit from any they use.

The power of machine learning over the IoT ecosystem is amplified by the quality of data gathering and the interaction of manufacturing line personnel. Employees will see for themselves the effectiveness and impact of these assistive technologies.

How IoT Technologies Support Real-Time Visibility

IoT monitoring platforms provide immense visibility into connected devices and applications.

They also help gain a unified view of IoT performance through real-time diagnostics and analytics for troubleshooting errors and exceptions. With the visibility leveraged through IoT systems, manufacturers can use rich, invaluable insights from sensors to further business objectives.
Asset Tracking-01

Asset Tracking

The accuracy and timeliness of data from IoT sensors over the Internet can be used to implement highly efficient asset management systems. IoT has made asset management smarter, more connected, and more capable. The data drawn from sensors can be used to configure protocols to enable seamless interoperability between connected devices. IoT enables different applications at different stages of production. Since the advent of inexpensive sensors and their ability to connect over the Internet, IoT has eliminated the need for proximity to track asset performance. Today, the power of IoT can be used to not only sense and monitor the performance and condition of expensive machinery, but it can also be used to track and identify genealogy and establish trackability and traceability for materials used in the manufacturing environment. This feature is capable of driving an elevated level of accountability, transparency, quality, and waste elimination. Asset management with IoT one of the most widely practiced use-case across manufacturing environments.
Quality Control-01

Quality Control & Testing

IoT-enabled sensors at end-of-line (EoL) and in-line can detect deviations from specifications before the product goes to finished goods. This allows for agile in-process changes in the manufacturing environment. Instead of waiting until the end of the line to identify potential scrap, IoT sensors embedded across the production line throughout jigs and fixtures can identify potential defects and eliminate the scrap that usually occurs at the end of the line. Agile in-line actions can also be taken to ensure scrap is maintained at a level lower than the allowed target or eliminated entirely in the long run. Quality control at source by having tighter control over the process parameters in real-time is made possible by IoT devices. This helps in reducing the tolerance build-up in the production process, improving overall product quality, and a scrap rate significantly lower than the set target.
Optimized Inventory

Optimized Inventory

IoT sensors can streamline the manufacturing processes in a number of ways. They can be used to develop smooth, seamless, and efficient inventory management. Every item in the inventory will transmit data to facilitate enhanced transparency and traceability. They help create a record of the location of inventory items, their status, and movements in the supply chain. Industrial IoT and data analytics use data to offer inventory insights. The outputs of IoT-based inventory management can be used in diverse ways. For instance, IoT-based inventory management architecture can help calculate the volume of raw materials required for the manufacturing cycle. The system can send an alert to the users if any individual inventory item needs to be replenished.


Traditionally, manufacturers tend to over stock inventory to compensate for quality issues, longer setups, poor machine utilization, and high scrap rate. With the advent of IoT and data analytics, optimized process parameters are effectively maintained, thereby reducing all process variations. This has led to optimized inventory levels, beginning with raw material to work-inprocess (WIP) to finished goods.

Perfect Production

Leading to Perfect Production

Industrial IoT-driven visibility delivers value through effective asset tracking, optimized inventory, and empowering quality control and testing. Through better visibility and the power of informed decisions, IoT helps move the manufacturing process towards perfect production. Reducing waste, increasing efficiency, increasing throughput, minimizing incidents to improve safety, and better yield all contribute to an ideal manufacturing line with optimal production capacity. This is what Oden describes as the Golden Run. When a plant achieves the Golden Run, it becomes more profitable, responsive to external stimuli, risk free, and efficient.

How to Overcome IoT Implementation Challenges

IoT monitoring platforms provide immense visibility into connected devices and applications.

For companies to make the most of their IoT implementations, they must address all three paradigms of a manufacturing enterprise:






Planned change management is essential to enable this integration. Change management takes a holistic view of providing solutions with the necessary tools. While these advanced technologies are often associated with job loss, proper guidelines on how the effective use of these technologies can empower employees can change this idea. Employees should be educated as to the purpose and advantages of IoT-enabled systems.

Deeply Evaluate ROI

The first step in any business is to clearly define ROI. ROI ideally must cover all tangible and intangible benefits. Investment decisions are often made on tangible elements. The buy-in and adoption from users and stakeholders is often motivated by intangibles, so there must be a clear understanding of both types of benefits. . For instance, an increase in productivity can easily justify the investment (tangible), but aspects like user-friendliness will increase adoption (intangible). Since ROI is likely to be different for different stakeholders, this makes the need for clear documentation even more critical. Consider an increase in takt time. While a high takt time may indicate an important ROI measure for line operators, throughput increase may be of higher importance to the plant manager or plant director, while asset utilization and returns per square feet may be of greater precedence to the CFO. Hence, the critical measure of success for each role should be identified.

Invest in Employee Training

With seamless adoption, investments are likely to return better yields, hence the importance of full stakeholder support. Proper training is critical to ensure that role-based user adoption is encouraged. Training exercises should not be limited to personnel understanding how to use the tool or product, but also educate every individual on its benefits so that they have the motivation to constantly pursue best practices.

Keep Security at the Core

Like all digital initiatives, IIoT is also subject to certain vulnerabilities. The pivotal factor for successful implementation and continuous operation is security. The IoT ecosystem has vital information circulating within the cyber domain that requires constant protection. The cyber domain is fraught with vulnerabilities against man-in-the-middle attacks as well as penetration attacks at various points. Data consistency and data integrity are key elements in the entire setup. It is critical to establish and maintain the right protocols and to select the best solution that secures information against attacks, while allowed legitimate access and usage.

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