A question we continue to hear from workforce development organizations and local companies is: Is our local workforce prepared for the Fourth Industrial Revolution?
This is a question educators are actively looking to answer – whether it be through strategic industry partnerships or by incorporating industry 4.0 into their programs on their own terms. How does this translate when it comes to the Smart Factory of the future?
The key tenants of Industry 4.0 smart factory training focus on automation, data analytics, cybersecurity, human-machine interaction, and continuous improvement. Educators are increasingly looking to thoroughly cover these concepts in their training programs so that they can best prepare employees to work effectively in a smart factory and contribute to its success.
Automation
Automation is the central theme of Industry 4.0. Smart factories leverage various automation technologies like robotics, artificial intelligence (AI), the Internet of Things (IoT), and machine learning to automate manufacturing processes.
By automating repetitive and time-consuming tasks, such as assembly line work, machines can operate more efficiently and with greater precision than human workers. Smart factories take this a step further by integrating all of the production processes into a single, interconnected system that can be monitored and controlled in real-time.
One of the key benefits of automation and smart factories is increased productivity. By reducing the need for human intervention in the production process, companies can manufacture products at a faster pace and with greater consistency. This can lead to significant cost savings and increased profitability.
Another benefit of automation and smart factories is improved quality control. With machines performing tasks that were once done by humans, the potential for human error is greatly reduced. Smart factories can also use sensors and data analytics to monitor the production process and identify potential issues before they become major problems.
Automation and smart factories can also help companies to become more sustainable. By optimizing production processes, companies can reduce waste and energy consumption, leading to a smaller carbon footprint and a more environmentally friendly operation.
As educators look to help smart factories take advantage of all these benefits, they need to teach to the nuances within each. For example, Amatrol’s Smart Factory Learning System utilizes a FANUC robot so that learners can gain real-world robot programming and operation experience, a key component of smart factory automation.
Also, the use of Smart Sensors, and Smart Product ID components throughout a fully-automated line order like within this training system can help learners gather real-time data so they can not only see how everything is connected, but also practice hands-on Industry 4.0 skills.
For educators looking for a convenient option for critical Smart Factory training when training space is too limited for the full Smart Factory line, Amatrol offers a Smart Factory Tabletop Mechatronics training system to introduce Industry 4.0 training to students. It allows students to analyze information including transmitter pressure, photoeye signal strength, material type for parts passing through the system, RFID tag output, and more. The system uses a selection of Rockwell Automation products to provide the most realistic industrial experience.
Data Analytics
Network communications lie at the heart of Industry 4.0 systems. Smart factories generate large amounts of data from sensors and machines, and data analytics tools and techniques are used to analyze this data and gain insights into manufacturing processes. Employees need to be trained on data analytics tools and techniques to be able to make sense of this data and take appropriate actions.
Amatrol’s Smart Factory Learning System features hands-on training for managed and unmanaged ethernet switches, wireless communication and network security, as well as software for tracking cloud-based maintenance communications, production control, scheduling, and monitoring.
The system’s smart sensors with I/O links provide flexible manufacturing, predictive maintenance, and data analytics capabilities. (Featured smart sensors include pneumatics/vacuum, ultrasonic, photoeye, stacklight, electrical current, and analog position and pressure sensors.) It also features Ethernet/PROFINET and wireless communications equipment to allow learners to utilize industrial protocols for real-time control, program transfer, data collection, and changing programs.
Cybersecurity
Smart factories are connected to the internet and other networks, making them vulnerable to cyber-attacks. The same interconnectedness that provide the benefits of increased efficiency, reduced downtime, and improved quality control also open the factory up to new threats.
To mitigate these risks, smart factories need to implement robust cybersecurity measures, such as network segmentation, access controls, encryption, intrusion detection and prevention, and regular software updates. They also need to provide employee training on cybersecurity best practices, such as strong password management, phishing prevention, and incident response. Many of today’s smart factories follow industry standards and regulations related to cybersecurity, such as the NIST Cybersecurity Framework and ISO 27001.
Employees need to be trained on cybersecurity best practices to ensure that the smart factory’s network and data are secure. That’s why Amatrol’s network security equipment within its Smart Factory Learning System teaches learners how to protect manufacturing processes and data from outside access, provide safe data communication between factory networks and the Internet, and securely extend operational data to suppliers and customers.
Continuous Improvement
Smart factories are designed to support continuous improvement by providing real-time data and insights on manufacturing processes. Sensors, IoT devices, and other technologies collect data on production metrics such as output, quality, and downtime. Advanced analytics software then processes this data, identifying patterns and trends that can help manufacturers make data-driven decisions on how to optimize their operations.
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One example of how continuous improvement is implemented in smart factories is through predictive maintenance. Sensors and IoT devices can collect data on the performance of machines and equipment, identifying potential issues before they become major problems. This allows maintenance teams to schedule repairs and replacements proactively, reducing downtime and increasing overall equipment effectiveness (OEE).
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Another example is through the use of digital twins, which are virtual replicas of physical assets or processes. By simulating different scenarios and changes in real-time, manufacturers can test and validate new production processes before implementing them on the factory floor. This can help reduce the risk of costly errors or downtime.
Employees need to be trained on the principles of continuous improvement to ensure that they are always looking for ways to optimize manufacturing processes and improve efficiency. This should be a recurring theme throughout any smart factory training curriculum, underpinned by a learner’s ability to understand the inner workings of the factory and how to best identify areas for improvement.
