The Industry 4.0 Framework: Idea, Tool, & Guide (Part 1)

The Industry 4.0 Framework: Industry 4.0 is many things to many people. For our purposes, Industry 4.0 is a journey deeply involving various advanced technologies that help manufacturing operations become more reliable, productive, efficient, and customer-centric.

“Technology is the future, I have seen the third industrial revolution, and we are in the midst of the fourth industrial revolution.” – Chandrababu Naidu

Another useful definition of Industry 4.0 (among a multitude of others) is the information-intensive transformation of manufacturing and other industries. The Industry 4.0 environment digitally connects data, people, processes, services, systems, and IoT-enabled industrial assets across cyber and physical worlds. The goal is to create, use, and take full advantage of actionable information.

For some analysts, Industry 4.0 describes a future state of industry characterised by thorough digitalised production processes. For others, Industry 4.0 is already here, representing a new and higher level of organisation and control over manufacturing along entire value chains and product life cycles.

This chapter views Industry 4.0 as the development of a roadmap to establishing high-tech, digital manufacturing processes. We’ll give special attention to the framework’s reference architecture, which bridges physical industrial assets and digital technologies in cyber-physical systems.

Pillars of the Industry 4.0 Framework

There are many Industry 4.0 frameworks. Each country engaged in systematically modernising its manufacturing base has its own. As in Japan (Society 5.0), the scope of the framework might expand beyond manufacturing. National development priorities might focus on different sets of advanced technologies. However, countries engaged in Industry 4.0 programs and initiatives tend to emphasise a standard model, a set of advanced technologies, and concepts.

Technology Pillars of Industry 4.0

Industry 4.0 depends on not one but several advanced technologies. Some are familiar; others have been a commercial product for a short time. It’s the combination of these technologies in R&D, production, and post-production processes that will help make manufacturing more efficient.

Different analysts use slightly different lists of technologies. (Ours comes from a 2017 Boston Consulting Group study.) However, these are the technologies usually mentioned in Industry 4.0 frameworks:

• Big data/advanced analytics — The industrial world is filled with mountains of unanalysed product and process data. Analysing it and turning it into actionable information can optimise production quality, improve services, and enable faster and more accurate decision making.
• Advanced robotics — As robots become more flexible, cooperative, and autonomous, they will interact with one another, work safely with humans, and eventually learn from humans, too. Industry 4.0 provides a manufacturing context for these opportunities.
• Advanced simulations — In Industry 4.0 environments, 3D simulation of product development, material development, and production processes will enable operators to test and optimise processes for products before production starts.
• AI/cognitive computing — Cognitive manufacturing uses the assets and capabilities of the IoT, advanced data analytics, and cognitive technologies such as AI and machine learning. When used together these technologies will drive improvements in the quality, efficiency, and reliability of manufacturing processes.
• Industrial Internet of Things — In the IIoT, an ever-greater number of products will incorporate internet-connected devices, which link with each other with standard protocols. This approach to manufacturing will decentralise analytics and decision-making and enable real-time responses.
• Cybersecurity — Industry 4.0 environments include connectivity and communications protocols as well as sophisticated identity and access management systems. These technologies enable manufacturers to provide secure, reliable communications and data flow throughout Industry 4.0 systems.
• Additive Manufacturing — In Industry 4.0 manufacturing environments, these technologies are the best choice for producing small-batch, customised, and high-performance products.
• Cloud-based service-enabling technologies — Industry 4.0 manufacturing operations require more data sharing across sites and companies than earlier processes do. Shifting data storage and management to the cloud will drive the development of more manufacturing execution systems (MESs) that use cloud-based machine data.
• Augmented reality — AR provides an effective way to represent production processes by overlaying real-world views of production with virtual information. In ASEAN countries, the most likely role of AR lies in training future workers and technicians how production systems behave in real-time.

Figure 3-1: Emerging Technologies demonstrate the breadth of applications that make up Industry 4.0. In the world of Industry 4.0, technology doesn’t operate in isolated factories or assembly lines. In fully realised Industry 4.0 environments, technologies connect with other entities, up and down production hierarchies, along value chains, and throughout product life cycles.

Emerging Technologies

Emerging Technologies

Connectivity

In the globally interconnected world, data sent along digital networks link machines, production objects, internet-connected devices, their virtual representations, and humans. Critically, interconnected machines in Industry 4.0 systems interact with different levels of human involvement. For Industry 4.0 manufacturing and systems engineers, this ever-present connectivity has design and operational implications:

• Connectivity is related to interoperability — Shared communication protocols are not just becoming the norm. They are becoming essential parts of manufacturing process design.
• Connectivity enables cyber-physical systems — These are the systems that make smart factories possible. Cyber-physical systems connect intelligent production objects to embedded physical devices, which can store and process data.
• Humans are not always in the production control loop — Industry 4.0 production machinery no longer simply “makes” the product. The product communicates with the machinery to tell it exactly what to do.

Data that flows through Industry 4.0 systems does so in a systematic way, through production hierarchies, and along product life cycles.

Data integration: The broader Industrial 4.0 view

Integration addresses the flow of data between connected machines and devices at different parts of the product life cycle and levels of the production hierarchy.

Horizontal integration refers to the connection of and data flow through IT systems across all manufacturing-related production and business planning processes. Horizontal integration is, therefore, about digitising entire value and supply chains. From supplier to consumer, end-to-end horizontal integration maps IT systems and information flows with big data, analytics, and IoT devices.

In traditional thinking about manufacturing, the production process included all the steps that occur after components enter the factory floor and before they leave it as a finished product. Industry 4.0 concepts require a wider perspective.

Now, a product’s life cycle begins with the first product development ideas and extends horizontally through development and production steps to sales and eventual product recycling or disposal.

Vertical integration refers to IT systems connected to machines and devices that operate at different levels of the production hierarchy. In traditional terminology, these hierarchical levels include:

• Field level — in which sensors convert environmental data to signals that are analysed and to actuators, which convert signals into actions.
• Control level — in which controllers gather process data from sensors and drive actuators.
• Production process level — in which automatic devices monitor, control, and adjust specific functions in production processes.
• Operations level — which includes functions such as production planning and quality management.
• Enterprise planning level — which manages the whole production system, enabling business functions such as production planning and market analysis.
• Connected world level — where traditional hierarchy is expanded by moving beyond isolated manufacturing facilities. In this level, network assets and processes connect and support data flow throughout manufacturing systems. Industrial communications networks tie all vertically integrated levels together, sending data from one level of the hierarchy to the other.

The production hierarchy, manufacturing processes, and product life cycle are familiar concepts. In the early days of Industry 4.0, the difficulty lay in how to combine these concepts in a way that was easy to understand and use. The RAMI 4.0 data model helped overcome this problem. We will explore about the RAMI 4.0 Model in the next article. Stay tuned!

Written by Colin Koh, Senior Business Development Manager, Industry 4.0 Consultant. This Industry 4.0 Article Series is aimed to enlightened readers about everything they need to know about Industry 4.0 and its application about technologies and benefits to companies and consumers.

Industry 4.0 Portal Articles 

• What is Industry 4.0 And How It Began (Part 1) (Part 2) (Part 3)
• The Industry 4.0 Framework: Idea, Tool, & Guide (Part 1) (Part 2)
• The Smart Factory – 6 Key Principles You Should Achieve 
• The Smart Factory- All You Need to Know About The Requirements 
• Connectivity & Interoperability (Part 1) (Part 2) (Part 3)

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