IoT in Manufacturing: Connecting Every Piece in the Factory

Introduction

Disruptive technological advancements have profoundly impacted every industry, no matter how change-resistant it might be. The increasing popularity of the Internet of Things (IoT) has made this possible due to consumer interest and the desire for customization.

According to studies, nearly 70% of American adults regularly use a voice-controlled system, and nine out of ten own at least one smart device. IoT has finally found its footing in the manufacturing technology sector, which is ironic given the emphasis on facilitating the digital way of life for us humans. 

In recent years, many businesses, from retail to logistics and manufacturing, have benefited from IoT-driven process improvements. Manufacturing has, in particular, achieved substantial cost savings and efficiencies that have been passed on to us as users with the help of the IoT. 

In this piece, we'll look at how manufacturers can put industrial IoT solutions to use in their daily manufacturing operations.

1. The Industrial Internet of Things (IIoT) definition

The integration and use of interconnected smart IoT devices and safety IoT sensors in industrial processes to improve operational efficiency, productivity, and safety is referred to as the Industrial Internet of Things (IIoT). The notion of the Internet of Things (IoT) is extended to industrial areas such as manufacturing, energy, healthcare, transportation, and others.

IIoT leverages the capabilities of smart devices and real-time analytics to capitalise on the valuable data generated by dumb machines in industrial settings for years. The driving principle behind IIoT is that smart machines are not only better than people at acquiring and analysing data in real time, but they are also better at communicating crucial information that can be used to drive faster and more accurate business choices.

Connected sensors and actuators allow businesses to detect inefficiencies and problems earlier, saving time and money while also assisting with business intelligence efforts. IIoT has the potential to provide  production quality control, sustainable and green practises, supply chain traceability, and overall supply chain efficiency in manufacturing. IIoT is critical in industrial settings for activities such as predictive maintenance, improved field service, energy management, and asset tracking.

To summarise, the Industrial Internet of Things represents a paradigm shift in industrial processes, harnessing the power of connected devices, data analytics, and advanced technology to deliver efficiency, sustainability, and competitiveness advantages.
 

2. How IoT Enables Intelligent Industrial Operation

Every manufacturing companies tries to improve its production process through development to ensure a lower cost of production. This is because the competitive market demands better-quality products at a lower price, creating a race in the optimization and production of automation processes. 

The main task of production at this stage is to predict the outcome— even before production begins, we need to know when the product will be produced, how much production will cost, and what part of the defect will be. Problems that classical approaches cannot solve can already be seen here. 

In this situation, best IoT solution for factory comes to the rescue and fundamentally changes the situation. These changes are referred to as "Industry 4.0" and other terms, but in this article, we will analyze how IoT affects manufacturing floor in detail.

One Step Ahead: Predictive Maintenance

Despite frequent headlines about a new technological revolution thanks to how is IoT used in manufacturing, the integration of the Internet of Things into manufacturing has been and remains evolutionary rather than revolutionary. Considering how production requirements are expanding, solving problems that arise in any complex system is no longer enough.

The manufacturing industry has driven automation, improved processes, and fueled business growth by applying IoT technologies to almost all IoT systems.
Instead, problems must be solved before they appear, so it is vital to be aware of the possibility of a missing asset or damaged and wear-on mechanisms in advance. 

This is where IoT-based solutions come into play.

2.1 Sensor-Based Industrial Machines Conditional Monitoring

The basis of modern IoT in the manufacturing industry is a set of sensors, both for production automation and for remote monitoring the condition of devices in production. 

Production efficiency sensors have different types and purposes, including temperature, pressure, sound, distance, acceleration, and humidity. The same type of sensor performs different functions depending on its specific purpose. 

For example, temperature sensors are mainly used to monitor the condition of refrigeration or heating devices, industrial boilers, liquids, and food storage units, as well as to determine the conditions of rooms where people work. 

Similarly, thermal smart sensors can also be used to monitor the condition of bearings in which increased friction leads to increased temperature or electronics and power sources that are subjected to heavy loads and generate heat. A parameter like humidity in the room can indicate the risk of device corrosion and the danger of the growth of fungi and other pathogens.

Any production involves complex mechanical devices. These can be transport vehicles and conveyors; processing machines learning, robots, and other arrangements; compressors for pumping liquids and motors. Depending on the mode of operation and the state of bearings and other components, various types of vibrations occur during the movement of mechanical details. 

The collection, research, and processing of this data form the basis of vibration diagnostics. In our opinion, vibration monitoring is the best IoT use case in manufacturing, as it shows how measuring simple parameters of a complex system help avoid big problems.

As a result, a wide variety of sensors allow constant monitoring of the state of machines and tools, encouraging rapid problem resolution. That ensures that production is much more consistent.

2.2 Forward-Thinking Based On Data Collected In The Cloud

While the sensors allow to collect data in the Cloud, simply collecting data in great volumes will not, in and of itself, produce outstanding results. The real profit from IoT solutions for manufacturing arises when data gets into the Cloud- this is when Artificial Intelligence (AI) comes in. 

Neural networks, numerical series, and other extrapolation algorithms help predict problems that may occur in the future. When workers are able to resolve potential issues before they cause disruption, production moves to predictive maintenance. 

Furthermore, real-time data collection and AI in the Cloud reduce poor quality costs (PQC) by predicting the deterioration of mechanisms and equipment and detecting future equipment failures even before they affect the quality of production.

2.3 Building A Safe Manufacturing Ecosystem

Since most industries have always been harmful or dangerous to humans, IoT tries to solve this problem. Standards such as ISO and GMP require continuous monitoring of the state of air quality and other environmental parameters on premises where people work. 

Strict control should be based on the main parameters that determine work comforts, such as temperature, humidity, air pressure, and lighting quality. Ensuring that these parameters fall in a comfortable range for individuals helps improve the working capacity of employees and has a positive effect on the efficacy of decisions made and speed of reaction.

Moreover, IoT manufacturing solutions help identify and quickly respond to dangers that a person cannot notice instantly. This is particularly true for harmful gases or micro-particles in the air that can go unnoticed easily. In this case, smart solutions improve comfort and help keep people healthy. In fact, they can also save lives.
 

3. Improving IoT in Production Line Quality And Effectiveness Control

Changes in manufacturing with manufacturing IoT applications lead to a transition from production control to quality control, i.e., to a fundamentally new level.

3.1 Real-Time Location Tracking in Supply Chains

Information about the movement of components of products, both inside and outside the factory, is precious. Only continuous monitoring of the supply of components and optimization of logistics movements make the production of goods truly efficient and resistant to changes. 
Localization of components and resources within production using barcodes or RFID helps optimize supply chains and manage inventory positions so that assets are in the right place when they are needed. Of course, AI plays a major part in optimizing logistics tasks. 

3.2 Advanced Sensorization

The latest trend in manufacturing and technology is to put as many sensors as possible into cutting-edge gadgets and machinery. The abundance of sensors generates more operational data to be delivered, processed, and stored – consuming more power. That shows that increased sensorization negatively affects the cost of industrial equipment. 

On the other hand, advanced sensorization opens up new perspectives and use cases that are not otherwise available. The integration of seemingly superfluous sensors in wearable devices (smartphones and smartwatches) has shown that this process works. 

Below are some positive results of the first production test:
- Elements of augmented reality (AR) were used in production for asset control and management, which allowed employees to work more efficiently.
- Robotic devices with depth cameras build a 3D image around the room. The operator can use such devices with feedback for delicate manipulations in difficult or emergencies. 
- Mobile robots with thermal cameras help monitor the equipment's condition when the worker cannot do it on his own. 

3.3 Minimizing Downtime - Algorithms For Cost-Saving

Internet of Things manufacturing solutions and predictive maintenance practically eliminate production downtime and make product quality more accurate. Moreover, result-oriented algorithms help reduce service costs by providing it with exactly what is needed and optimizing logistics paths. 

Even if downtime is not completely avoidable, it can be predicted. It is important to try to make the best of the situation and prepare for downtime. For example, preparing alternative supplies or unused equipment will minimize delays.

4. Challenges for Smart Factories

The continued growth of IoT factories faces several challenges despite how far IoT in manufacturing has come and the bright future it promises. 
One of the first challenges faced is the problem of connectivity. 

Each of the IoT for factory consists of an endlessly growing number of devices that must communicate with each other and with the system. Therefore, the concentration of connections in modern productions is extremely high. Currently, this indicator is approximately two devices per square meter, but it will grow over time.

4.1 Getting Things Connected (NB IoT, 5G, BLE, etc.)

Not all IoT connections are suitable for use in manufacturing. While the IoT's guiding principles, communication channels, and sensors gather data transfer protocols have been discussed at length, the density and location of smart devices in this particular scenario pose some challenges.

Moreover, most devices in production do not require large continuous data streams, and polling of devices can be done once every second, minute, or even every hour. As for IoT in general, cellular networks are most suitable for IoT in manufacturing.
IoT is currently transitioning from 2G/3G/4G to NB-IoT and 5G. However, 2G modules are much cheaper. 

Data transmission requirements become more stringent as devices increase in intelligence and automation. Therefore, NB-IoT technology is gradually replacing others in IoT for manufacturing.

However, Wi-Fi is still used to interact with robotic manipulators, video cameras, and other devices that require large data streams, such as video or a point cloud of 3D images.

4.2 Protocols: AMQP vs. MQTT 

Data transfer can streamline many manufacturing processes, but this is not enough. Communication with devices must be stable, secure, encrypted, and efficient. All IoT purposes are fulfilled via different protocols. While some, like MQTT, were created particularly for the Internet of Things, others, like AMQP and HTTP, were adopted from other fields. 

They all use TCP/IP as a foundation, but each has its own advantages and disadvantages. MQTT, or Message Queuing Telemetry Transport, was developed specifically for machine-to-machine (M2M) communication, so its advantages are aimed particularly at this segment. The main features of MQTT are its lightness (message overhead of 2 bytes) and reliability (device connection control). 

On the other hand, Advanced Message Queuing Protocol (AMQP) has more features, is more versatile, supports queues, and offers a larger maximum message size (up to 2 GB). 
However, the choice of a certain protocol often depends on tasks, vendors, and specific devices.

4.3 Integrating Older And New (aka "Smart") Equipment

The next problem, probably the most important, is the gradual integration of IoT in manufacturing. It is vital to plan the construction of new IoT factories while considering the development of new technologies. However, the industry is already working, and more often than not, IoT solution must work effectively with legacy equipment. 

Every business struggles to reduce prices, so investing money can bring benefits and value. Even though switching to a new device had its own pros, the "smarter" the device, the more solutions the developer has integrated into it, and the more expensive it will be. 

Therefore, it is best to upgrade outdated equipment gradually while modifying and incorporating it into a single system with an IoT-based one. 
Most factories are already planning a gradual transition to IoT solutions. However, due to the market's youth, such transitions' payback is not expected. It is difficult to estimate how long it will take to pay off investments in production modification because there are still not enough long-term examples like this.

Conclusion

A vital tenet of the "new industrial revolution" is adopting cutting-edge information and communications technologies within the manufacturing sector. 

While many technologies will contribute to this goal's realization, Internet of Things (IoT) technology stands out as the medium through which machines can communicate with each other, humans, and other humans.

Currently, there is a wide range of applications for industrial IoT solutions. Maximum output, minimal expenditures, and zero waste are just some of the benefits of the Industrial Internet of Things in industry and commerce. 

Leveraging smart manufacturing IoT technologies and data allows for more accurate supply chain processes and demand forecasting, leading to a more customer satisfaction experience. Therefore, there is no bad time to start looking for Internet of Things fleet management software development services for your company.

Industrial IoT Solutions with Indeema Software

Indeema Software provides support for the Internet of Things (IoT) at every stage, from ideation to development to testing and maintenance in the manufacturing industry. We have helped increase the efficiency and growth of various companies thanks to our superior expertise. 

With our experienced staff, well-defined procedures, and meticulous management, Indeema Software is able to meet all customer's demands for IoT development with cutting-edge engineering services.

To learn what assistance we can provide to improve your manufacturing processes, connect with us through our website and have a conversation with us today!