Smart Factory and Smart Manufacturing 101
What is a Smart Factory?
The Future of Manufacturing with Smart Factories
Thanks to the changing workforce and advancements in innovative technologies, the manufacturing industry is going through significant transitions.
Finding manufacturing talent is difficult for organizations today.
Younger workers are becoming less interested in pursuing manufacturing roles, seeing them as hard work/low-paying jobs. The manufacturing sector is also an aging workforce, as 22% of workers are 55 or older in Canada (Source: Randstad). If these trends continue, it’s estimated that by 2030, the manufacturing sector might have a shortage of 2.1 million jobs (Source: Deloitte).
At the same time, industries are applying new technologies such as artificial intelligence, the internet of things, and cloud computing to grow more efficient and competitive. Whether it’s to increase production, become environmentally friendly or help workers make better decisions, technology is advancing traditional industries.
These tech advancements are now entering the manufacturing sector, and due to the changing workforce, smart factories and smart manufacturing are piquing interest.
What is a Smart Factory?
A smart factory uses highly digitized technologies to collect and send data between different machines and production systems. Designed with automation and connectivity in mind, the factories integrate a wide variety of advanced technologies, including Artificial Intelligence, Machine Learning, Industrial Internet of Things (IIoT), Big Data, and Cloud Computing.
Every machine and device in a smart factory is interconnected and communicates with one another. This interconnectedness allows them to distribute data points across the organization to increase productivity, address concerns as they arise, or adapt to new demands. Advanced connections like this enable smart factories to monitor the production process from start to finish.
How Smart Factories Tie into Smart Manufacturing and Industry 4.0
Smart factories are a small part of the digital transformation of Industry 4.0.
Industry 4.0 is the fourth industrial revolution. Previous revolutions discovered steam-powered systems, electricity, assembly-line productions, and computers. The fourth industrial revolution focuses on improving computer technologies from 3.0 and applying new information/communication technologies to digitize all manners of business and life, including manufacturing processes.
This is where the term “smart factory” comes from. Smart Factories take advantage of the developing technologies from Industry 4.0 and use them within a factory setting.
Although used interchangeably, smart manufacturing, smart factory, and Industry 4.0 mean different things. Smart manufacturing is a term that focuses on creating products with smart factories (Source: Stefanini Group). Meanwhile, Industry 4.0 refers to the new revolution that is making all the technological impact today.
Industry 4.0 is just beginning, but we’ve already seen numerous advancements in smart manufacturing. Take Whirlpool as a recent case study, where they used a smart factory setup to reduce cardboard waste.
Smart Factory Example
Originating from Michigan, Whirlpool is an appliance manufacturer that continues to use smart factory innovation to its advantage. To eliminate waste from its factories worldwide, Whirlpool decided to integrate an analytics platform across all areas of its factory to track the amount of waste they generate. This “waste” included various materials and utilities such as cardboard, electricity, and water.
Working with Schneider Electric, Whirlpool installed Industrial IoT devices across these factories along with integrated and connected dashboards to monitor how much waste was being produced.
After integrating the complex system, Whirlpool noticed areas where they could reduce waste in multiple locations at different factories worldwide. In their Ohio factories alone, Whirlpool found they were wasting over 20 million pounds of cardboard and anticipated saving more than $1 million over the next three years. (Source: Altenergymag).
So not only did smart factory technologies improve their process’ environmental sustainability, but it also cut down on costs.
Are you interested in finding out more about how 5G is contributing to environmental sustainability? Then read our “5G Climate Change: 4 Ways 5G is Helping the Environment” blog to learn about the role 5G can play in a greener future.
Technologies Used in Smart Factories
Harnessing the benefits of the smart factory requires the integration of connectivity to send information and automate actions. This involves the use of various technologies. Let’s dive deeper and see how smart factories apply a combination of different technologies.
Industrial Internet of Things (IIoT)
IIoT brings IoT technologies into the industrial sector – hence the extra “I.” The Industrial Internet of Things (IIoT) is a collection of linked sensors, machines and devices connected to industrial applications. IIoT plays a big part in smart factories, as organizations must connect almost all the devices/machines in their factory to the internet. Connecting the IIoT devices enables real-time data to be collected and sent to a database or primary control system. The data can then be monitored and analyzed in real time for automated actions or reports to decision-makers. Where IIoT usually refers to the network of devices, the analysis of collected data is most commonly referred to as Big Data Analytics.
Discover our “What is Industrial IoT (IIoT)?” blog to understand how IIoT works in a smart factory setting.
Big Data Analytics
Big data analytics plays a prominent role in the day-to-day operations of a smart factory. A term used for a suite of storage, organization, and analysis techniques for massive data sets, big data from a smart factory can include data collected from machines, devices, and operators (Source: Tulip). As data passes between machines, devices, and operators, big data helps make sense of all the information. Big data analytics analyzes all the collected data, uses advanced statistics to identify what’s happening, and then considers the following steps to take. As data sets become larger and the required analysis more complex, Big Data is relying more and more on the advancements of artificial intelligence and machine learning.
Artificial Intelligence and Machine Learning
Artificial intelligence and machine learning algorithms use advanced network capabilities to analyze all the real-time data collected throughout the factory. As data comes in from thousands of IIoT devices, the algorithms sift through this information looking for patterns or trends. Once complete, AI and ML algorithms then create predictions and recommended actions. If the factory is fully automated, AI and ML can send information back to IIoT devices with information on how to act.
Confused about the differences between artificial intelligence and machine learning? Learn more about the relationships between artificial intelligence and machine learning in our “The Difference Between AI, ML and DL” blog.
Cloud computing is the network foundation for which IIoT and Big Data Analytics can run. With all this data coming from IIoT devices, storing and processing this information is done through the cloud. Cloud computing plays a big part in smart factories because it’s usually more flexible and cheaper than on-site data storage. It also allows larger data uploads, more storage, and data that is easily accessible to provide real-time decision-making.
Now knowing the basic technologies used in a smart factory, it’s time to see the four levels of smart factory success.
Achieving Smart Factory Innovation: The Four Levels of Smart Factory Benefits
Smart Factory Benefits Level 1: Data Collection
The first step to benefit from a smart factory is to connect data to a single database that will continuously gather, track and store information from various areas in the factory. Although this stage is a lot of work, the factory isn’t quite a “smart factory” yet. The benefit of this stage is the beginning process of organizing data into a single area, so it’s easier to access information.
Level two takes it a step further by transforming the organized data into information managers can easily understand. Without level two, factories collect raw data for the sake of it.
Smart Factory Benefits Level 2: Data Analysis
The data analysis stage builds from the previous step by presenting the data through visualizations and dashboards, making it easy for operators, engineers, or other users to see what’s happening. Presenting data in a more accessible format through graphs and charts allows users to gain insights quicker, understand what’s happening in the factory, and act accordingly to solve potential problems.
Although organizing the collected data from level one is beneficial, it needs to be automated. Human supervision is still required to analyze the data, make decisions, and act.
Level 3 takes us to automated analysis.
Smart Factory Benefits Level 3: Artificial Intelligence and Machine Learning-Based Decisions
At level 3, artificial intelligence and machine learning algorithms analyze the collected data, reducing (but not eliminating) the need for human supervision. The AI and ML setup automates insights and provides users with accurate information on current vital issues, possible upcoming failures, and other valuable insights that factory workers might need to make decisions. Once the information is received, users can act with the insights provided.
The final stage of benefits takes it a step further – by automating actions.
Smart Factory Benefits Level 4: AI-Driven Actions
The final stage truly is a smart factory. After fully automating data collection, data analysis, and decision-making insights, stage four is about automating actions. At this point, all the manufacturing machines and devices in the factory are fully connected. They can execute functions based on AI-driven insights with very little need for human interaction.
For example, suppose a machine on the production line begins to slow down. In that case, data is sent to the single database we created in stage one and is structured to be easily understandable (something we did in stage two). From there, the AI and ML algorithms we made in stage three analyze the collected data to identify why the machine is slowing down and the necessary actions needed to fix it. Once the AI and ML algorithms find the problem, they send a person (or if the factory is completely automated), a robot, to the machine. The robot or person then fixes the problem and returns it to its standard speed(Source: Forbes).
Now that you know the four levels of building a smart factory, it’s time to discuss keeping it cyber secure.
Cybersecurity in Smart Factories
Maintaining security is a massive consideration for organizations looking to create a smart factory. Cyberattacks on smart factories could lead to shutdown operations, stolen data, or injured employees.
With all these technologies running simultaneously, sharing classified data, instructions, results, and feedback, smart factories are a large target for cyberattacks. Since smart factories use many different IIoT devices at once, this opens dozens of vulnerabilities. For example, suppose an IIoT device is hacked, and a virus is uploaded. In that case, the virus can begin to infiltrate further into the system affecting other IIoT machines/devices and gain access to data on the cloud.
Types of Smart Factory Attacks
Smart factory attacks come in many different forms, including:
- Exploited Vulnerabilities: Since devices/machines are interconnected, attacks on any of those devices could infiltrate into other areas of the smart factory.
- Malware Attacks: Malware is the most common cybersecurity attack, so smart factories should be prepared to handle standard techniques.
- Denial-of-Service (DoS) or Distributed-Denial-of-Service (DDoS) Attacks: DoS and DDoS attacks shut down and/or disable entire networks by sending too much information or traffic to a network or machine, causing them to crash.
- Man-in-the-Middle (MitM) Attacks: MitM attacks target communication channels between devices and machines. Since smart factories rely on these communication channels to keep operations going, security managers should be on the lookout for MitM attacks.
(Source: American Security Today)
And can lead to:
- Stolen, Tampered, or Lost Data: After an attack, data from devices and machines around the smart factory may be stolen, tampered with, or even deleted.
- Device Hacking: Attackers could hack IIoT and other devices on the factory flow, causing them to damage operations on the assembly line or harm other workers.
- Hold Operations/Data Hostage: Once infiltrated, hackers can shut down parts of the factory or hold confidential data until the organization pays a ransom.
- Information Theft: Attacks on smart factories could also steal information from customer databases or employee records, exposing people to future cyberattacks.
(Source: Trend Micro)
Reducing the Risk of a Cyberattack in Smart Factory Settings
Knowing the risks of a cyberattack is an excellent first step, but it doesn’t do anything to reduce the risk.
Smart factory managers also need to:
- Train workers on the vulnerabilities and what to do about them: Training employees is crucial to smart factory cybersecurity. Without proper training, many more vulnerabilities open.
- Keep up to date with security upgrades: Devices within a smart factory setting need updates regularly. Make sure to update security during off-hours and notify employees of these events.
- Reduce unused function gateways: Devices and machines are usually designed with more than one function in mind. Be aware of these functions and know that they create added vulnerabilities.
- Stay cautious of using too many 3rd party devices: It’s common to see different brands of devices in a smart factory. This practice can lead to more vulnerabilities, meaning security managers must take extra precautions to ensure protection from each 3rd party device on site.
- Know that adding legacy hardware might increase the risk of an attack: Legacy hardware (factory machines designed before internet technologies were created) must be updated to work within a smart factory setting. When these legacy systems are built into a smart factory, vulnerabilities and outdated security measures might reduce protection from cyberattacks.
- Maintain an updated asset inventory: Know what devices, machines, software, hardware, and other assets are used on the factory floor, so you know what to protect.
- Reduce or remove BYOD: BYOD (Bring Your Own Device) is an easy way to reduce business costs for organizations, but there’s an increased risk associated. Infected USB sticks are a common BYOD and an excellent way for hackers to cyberattack.
- Employ services to identify vulnerabilities: Hire credible organizations to simulate an attack and see where there might be vulnerabilities.
- Know where data is stored: Ensure that sensitive data isn’t stored in unauthorized locations.
(Source: Tech Target)
Smart Factories with Smart Manufacturing in Mind
Overall, organizations design smart factories with smart manufacturing in mind. Smart factories allow organizations to speed up production through automation, remove most administrative work, and reduce the number of accidents or slowdowns on the line.
Smart factories use various interconnected technologies to communicate with one another to achieve smart manufacturing goals and advance Industry 4.0. Smart factories would be impossible without all these technologies working together simultaneously.
However, when building a smart factory, there are four steps to complete the process:
- Data Collection
- Data Analysis
- Artificial Intelligence and Machine Learning-Based Decisions
- Implementing AI-Driven Actions
Finally, cybersecurity plays a prominent role in smart factories. Without the correct cybersecurity measures, smart factories are vulnerable to attacks that could cause catastrophic outcomes.
Although only partially implemented in some areas of the manufacturing industry today, smart factories play an essential role in the future of manufacturing and Industry 4.0.
Learn how other traditional sectors can harness the potential of advanced networking to become more efficient, competitive and environmentally sustainable. Download our “Next Generation Network Imperative” Whitepaper to find out what the future of next-generation technologies looks like.