Smart Manufacturing

Smart manufacturing encompasses the devices and methods used in modern, internet-connected facilities. Smart manufacturing is the cornerstone of Industry 4.0, and is made up of interconnected machines, sensors, and other devices that comprise the Industrial Internet of Things (IIoT). The IIoT allows all components of a production process, from part design to part creation to shipping, to transmit and exchange data as part of a cohesive network. This allows manufacturers to increase automation in their facilities and respond just-in-time to any issues that arise.

Smart manufacturing classes cover topics including IIoT, cybersecurity, data collection, and machine learning.


Class Functional Area Format Difficulty Department
12
Classes 1 to 10 of 13
Cybersecurity for Manufacturing Basics 101

Cybersecurity for Manufacturing Basics covers the foundational concepts of cybersecurity as it relates to the manufacturing sector. As manufacturers adopt Industry 4.0 technology to enhance the digital connectivity of facilities, a fundamental understanding of cybersecurity is becoming more critical to ...

Industry 4.0 Online Beginner Smart Manufacturing
Cybersecurity for Manufacturing: Malware Overview 102

Cybersecurity for Manufacturing: Malware Overview covers different types of malware and how each functions. Manufacturing organizations using Industrial Internet of Things (IIoT) technology and other devices with internet functionality are vulnerable to a range of existing and emerging malware threats. ...

Industry 4.0 Online Beginner Smart Manufacturing
Introduction to the Industrial Internet of Things 111

Introduction to the Industrial Internet of Things (IIoT) 111 introduces the features of the IIoT and describes its role in manufacturing. The class provides an overview of how sensors, smart devices, and the data they create can transform factory operations. ...

Industry 4.0 Online Beginner Smart Manufacturing
Data Collection Fundamentals 121

Data Collection Fundamentals provides an overview of the basic life cycle, structures, and qualities of common data used in Industry 4.0. Data collection describes the process of collecting and analyzing various types of electronic information. As the collection develops, analytics ...

Industry 4.0 Online Beginner Smart Manufacturing
Automatic Identification Technology 141

Automatic Identification Technology 141 provides an overview of the main methods used to automatically identify and inspect objects, collect data, record that data in computer information systems, and ultimately make improved operational decisions. These methods include bar codes and radio-frequency ...

Industry 4.0 Online Beginner Smart Manufacturing
Cybersecurity for Manufacturing: Hacking Overview 201

Cybersecurity for Manufacturing: Hacking Overview 201 explores the various types of hackers, some common hacking methods, and strategies for defending against hacking. Hackers are generally classified based on their level of skill and their motivations for hacking. Highly skilled criminal ...

Industry 4.0 Online Intermediate Smart Manufacturing
Cybersecurity for Manufacturing: Wireless Networks 202

Cybersecurity for Manufacturing: Wireless Networks 202 introduces common wireless technology used in manufacturing and the risks associated with using wireless networks. Common wireless networks used in manufacturing include wireless local area networks (WLANs) and wireless personal area networks (WPANs). Using ...

Industry 4.0 Online Intermediate Smart Manufacturing
Introduction to Digital Networks 221

Introduction to Digital Networks 221 covers basic concepts and components of digital networking technology. Leveraging digital information efficiently can help optimize many aspects of a manufacturing operation, such as improving production speeds, product innovation, and product quality for end users. ...

Industry 4.0 Online Intermediate Smart Manufacturing
Data Collection: Inventory and Maintenance 231

Data Collection: Inventory and Maintenance 231 provides an overview of the processes, strategies, and software for storing data and maintaining data quality in Industry 4.0. Data inventory describes a record of datasets that lists important details about the compiled information ...

Industry 4.0 Online Intermediate Smart Manufacturing
Introduction to Digital Twin 241

Introduction to Digital Twin 241 provides an overview of the features, benefits, and current uses of digital twins in manufacturing. Digital twins are dynamic virtual models of physical assets. Using smart sensors embedded in the physical asset, digital twins are ...

Industry 4.0 Online Intermediate Smart Manufacturing
FormatFunctional AreaDepartment IDDepartmentClass IDClass NameDescriptionDifficultyLanguageRelated Classes
OnlineIndustry 4.0720Smart Manufacturing720010 Cybersecurity for Manufacturing Basics 101 Cybersecurity for Manufacturing Basics covers the foundational concepts of cybersecurity as it relates to the manufacturing sector. As manufacturers adopt Industry 4.0 technology to enhance the digital connectivity of facilities, a fundamental understanding of cybersecurity is becoming more critical to preventing losses due to cyber attacks. The United States government identifies manufacturing as one of the 16 critical U.S. infrastructures. Consequently, ensuring the strength and integrity of this sector is crucial to national safety and security.Cyber threats generally involve attempts by hackers to utilize malware, such as viruses or digital worms, to disrupt or disable technology or to gain access to systems illegally to obtain sensitive information. Malicious hacking attempts may involve individuals, groups of individuals, or even other nations. This course will help manufacturers and manufacturing personnel understand and identify basic cyber threats.BeginnerEnglish
OnlineIndustry 4.0720Smart Manufacturing720015 Cybersecurity for Manufacturing: Malware Overview 102 Cybersecurity for Manufacturing: Malware Overview covers different types of malware and how each functions. Manufacturing organizations using Industrial Internet of Things (IIoT) technology and other devices with internet functionality are vulnerable to a range of existing and emerging malware threats. In addition to traditional computer worms and viruses, criminal hackers create other types of malware, such as spyware, Trojans, and ransomware, to attack digital networks. They also employ phishing and other social engineering tactics to manipulate users into performing actions that plant malware onto systems.Manufacturers should be aware of vulnerabilities associated with all their digital assets and have a basic understanding of the range of tools criminal hackers may use to compromise these assets. After taking this course, users will be able to recognize malware threats. Users will also understand the basic strategies of criminal hackers and ways to defend against them.BeginnerEnglish
OnlineIndustry 4.0720Smart Manufacturing720020 Introduction to the Industrial Internet of Things 111 Introduction to the Industrial Internet of Things (IIoT) 111 introduces the features of the IIoT and describes its role in manufacturing. The class provides an overview of how sensors, smart devices, and the data they create can transform factory operations. It also explores how cyber-physical systems (CPS) and human-machine interfaces (HMI) are changing the way people interact with the growing network of technology in the workplace. The class also introduces digital manufacturing innovations, such as the digital thread and digital twin, and addresses concerns related to cybersecurity.It is now common for smart technology to provide detailed real-time data that creates precise instructions and feedback, enabling manufacturers to improve quality and efficiency, and to anticipate supply chain and production needs. As this technology drives Industry 4.0, an understanding of the IIoT is vital to current and future manufacturers.BeginnerEnglish
OnlineIndustry 4.0720Smart Manufacturing720030 Data Collection Fundamentals 121 Data Collection Fundamentals provides an overview of the basic life cycle, structures, and qualities of common data used in Industry 4.0. Data collection describes the process of collecting and analyzing various types of electronic information. As the collection develops, analytics add value to data and provide a competitive advantage to manufacturers.After taking this class, users will be able to define what data collection is, describe how it functions and is deployed, and identify the different ways that collected data is processed and stored. Additionally, users will better understand the value and importance of the data being collected and appreciate the safety steps needed to protect it from internal and external threats.BeginnerEnglish
OnlineIndustry 4.0720Smart Manufacturing720040 Automatic Identification Technology 141 Automatic Identification Technology 141 provides an overview of the main methods used to automatically identify and inspect objects, collect data, record that data in computer information systems, and ultimately make improved operational decisions. These methods include bar codes and radio-frequency identification (RFID), among others. After completing this course, users will have a better understanding of automatic identification technology and its potential applications in manufacturing. Integrating automatic identification technology with smart manufacturing helps to increase traceability and efficiency within the supply chain.BeginnerEnglish
OnlineIndustry 4.0720Smart Manufacturing720100 Cybersecurity for Manufacturing: Hacking Overview 201 Cybersecurity for Manufacturing: Hacking Overview 201 explores the various types of hackers, some common hacking methods, and strategies for defending against hacking. Hackers are generally classified based on their level of skill and their motivations for hacking. Highly skilled criminal hackers develop malware designed to harm digital systems, while less-skilled hackers may look for ways to use existing malware. Skilled ethical hackers work to correct cybersecurity vulnerabilities in digital systems to protect them from criminal hackers.Criminal hackers present a threat for manufacturers as they can attack digital systems in a variety of ways. This threat grows more complex as manufacturers adopt smart devices enabled by the Industrial Internet of Things (IIoT) and exchange more data across digital networks. After taking this class, users will better understand the cyber threats posed by hackers as well as the tools and strategies to defend against these threats.IntermediateEnglish
OnlineIndustry 4.0720Smart Manufacturing720105 Cybersecurity for Manufacturing: Wireless Networks 202 Cybersecurity for Manufacturing: Wireless Networks 202 introduces common wireless technology used in manufacturing and the risks associated with using wireless networks. Common wireless networks used in manufacturing include wireless local area networks (WLANs) and wireless personal area networks (WPANs). Using WLAN technology can expose manufacturers to security risks not associated with wired networks, such as wardriving, piggybacking, and evil twin attack. Additionally, using older WPAN technology or outdated security protocols can allow criminal hackers to easily access digital information through wireless devices.Manufacturers using wireless technology should understand the risks and employ strategies to protect their wireless networks. After taking this course, users will understand a variety of wireless networking options and their general applications, the risks associated with these networks, and effective ways to make these networks more secure.IntermediateEnglish
OnlineIndustry 4.0720Smart Manufacturing720110 Introduction to Digital Networks 221 Introduction to Digital Networks 221 covers basic concepts and components of digital networking technology. Leveraging digital information efficiently can help optimize many aspects of a manufacturing operation, such as improving production speeds, product innovation, and product quality for end users. Efficient digital networks improve automation, allowing artificial intelligence software to send, receive, and analyze data to optimize automated tasks. However, digital networks also pose a range of cybersecurity risks.Careers in manufacturing require personnel who can navigate digital networks successfully. Manufacturing personnel must be familiar with trends in networking technology as well as how to use digital information responsibly. After completing this course, users will understand the basic functions of different types of digital networks, recognize digital networking trends in manufacturing, and understand steps for managing risks associated with digital networks.IntermediateEnglish
OnlineIndustry 4.0720Smart Manufacturing720120 Data Collection: Inventory and Maintenance 231 Data Collection: Inventory and Maintenance 231 provides an overview of the processes, strategies, and software for storing data and maintaining data quality in Industry 4.0. Data inventory describes a record of datasets that lists important details about the compiled information and how frequently it is updated. Data maintenance identifies and executes the measures required to cultivate and manage data ensuring that it will continue to be useful and accessible. Data inventory and maintenance are critical parts of data management. After taking this class, users will be able to define data inventory and maintenance, describe how it functions and is deployed, and identify the different ways it is facilitated throughout the data management process. Users will also better understand the value and importance of data integration software and appreciate some of the Six Sigma principles used to reduce defects and variation among products.IntermediateEnglish
OnlineIndustry 4.0720Smart Manufacturing720130 Introduction to Digital Twin 241 Introduction to Digital Twin 241 provides an overview of the features, benefits, and current uses of digital twins in manufacturing. Digital twins are dynamic virtual models of physical assets. Using smart sensors embedded in the physical asset, digital twins are able to provide real-time design and performance insights, helping improve operations, develop better parts and products, and test parts and machines throughout production. Artificial intelligence, machine learning, the cloud, and data sharing along the digital thread is making digital twins more powerful. As the Industrial Internet of Things (IIoT) and smart technology drives Industry 4.0, an increasing number of manufacturing applications will use digital twins. Understanding the basics of digital twin technology will help manufacturers utilize them effectively. After taking this class, users will be able to describe what digital twins are, how they function and are used, and identify the different types.IntermediateEnglish
OnlineIndustry 4.0720Smart Manufacturing720135 Introduction to Digital Thread 242 Introduction to Digital Thread 242 provides an overview of the function, software applications, and current uses of digital threads in manufacturing. Digital threads, which often work in conjunction with digital twins, represent a communication framework within a smart factory. As the digital twin develops throughout the product lifecycle, the digital thread shares data between personnel, machines, and digital storage.This class will enable users to define digital threads, describe how they function and are created, and identify the different ways they are deployed throughout the product lifecycle. Digital thread integration breaks down traditional information silos in order to send and receive critical information in real time using the same data language. Also, digital thread traceability can help manufacturers track the impact of changes and constantly improve the quality of the products.IntermediateEnglish
OnlineIndustry 4.0720Smart Manufacturing720200 Introduction to Machine Learning and Artificial Intelligence 301 Introduction to Machine Learning and Artificial Intelligence covers advances in the field of artificial intelligence (AI) enabled by machine learning. Machine learning uses complex algorithms that enable computing devices to learn from input data and produce outputs without traditional programming. Basic types of machine learning include supervised machine learning, unsupervised machine learning, and reinforcement machine learning.Machine learning AI has a growing range of potential uses in various industries, including manufacturing. Manufacturers transitioning to Industry 4.0 should develop a basic understanding of how machine learning applications can benefit a variety of manufacturing processes. After taking this course, users will understand how data is used in algorithms that enable the three types of machine learning and gain insight into how machine learning AI capabilities may benefit their own manufacturing tasks and operations.AdvancedEnglish
OnlineIndustry 4.0720Smart Manufacturing720205 Machine Learning and Artificial Intelligence Applications 302 Machine Learning and Artificial Intelligence Applications 302 discusses strategies for applying machine learning (ML) and artificial intelligence (AI) capabilities to various manufacturing processes. ML algorithms can help improve manufacturing processes throughout a product’s lifecycle, including monitoring raw material use, optimizing production processes and supply chain logistics, and improving the product delivery and service for end users. Manufacturers can use machine learning libraries to gain valuable insights from data. Developing ML models requires the use of a programming language, such as Python, and an understanding of data analysis. Leveraging ML and AI can also vastly improve the quality of manufactured products.After taking this course, users will understand how computing devices can utilize machine learning models and how machine learning capabilities can be integrated into AI systems to automate a variety of manufacturing tasks and operations.AdvancedEnglish