Is Industry 4.0, smart manufacturing working for you?

It has been a dozen years of Industry 4.0 efforts. Are those involved moving quickly enough? Have others passed them by? Is there an Industry 5.0? How should Industry 4.0 be changing how stakeholders approach automation, controls and instrumentation? Control Engineering asked these questions and others about smart manufacturing and digital transformation to Jeff Winter, senior director industry strategy, manufacturing, Hitachi Solutions, and an industry expert on Industry 4.0 on LinkedIn.

Question: How do companies know if they’re moving quickly enough with Industry 4.0?

Winter: “Quickly enough” really depends on two things: 1) How does your company compare to its competitors? 2) How are you doing against your own Industry 4.0 goals?

For the first part, several maturity models help with evaluation of your company’s digital maturity and progress toward industry 4.0 (such as Acatech’s Industry 4.0 Maturity Index, INCIT’s Smart Industry Readiness Index, etc.). These allow companies to benchmark performances against industry standards and best practices, often times including a holistic evaluation of the company.

For the second part, companies can track key performance indicators (KPIs) specific to their Industry 4.0 initiatives to measure progress. Popular examples include overall equipment effectiveness (OEE), quality, flexibility and even innovation. World Economic Forum, partnered with McKenzie, is several years into its Lighthouse network program that aims to identify the top facilities that exemplify the leading edge of technology adoption and are implementing advanced manufacturing at scale while seeing significant gains. These gains are all publicized and can be used as a benchmark for realistic KPI improvements.

Q: Do you recommend any Industry 4.0 assessment, akin to a safety risk assessment or cybersecurity assessment?

Winter: Personally, I really like the Smart Industry Readiness Index (SIRI) by INCIT. This tool is good for evaluating and assessing Industry 4.0 progress because it provides a comprehensive, structured and systematic approach to evaluate an organization’s digital transformation journey. The index was developed by the Singapore Economic Development Board, which partnered with TÜV SÜD for certification of assessors. SIRI by INCIT is designed to help manufacturers assess and advance digital readiness. Two things I really like about the SIRI framework are: 1) There are classes to get certified as a SIRI Assessor (or the ability to search for assessors who are certified) and 2) they also provide a prioritization matrix along with the framework that helps with developing an actionable plan after the results of the evaluation.

Q: How is Industry 4.0 changing how companies approach automation, controls and instrumentation?

Winter: Industry 4.0 is the nickname given to the 4th Industrial Revolution. As its name implies, it is a revolution in the way the entire industry operates and the way people work, resulting in a complete change in society. This term was famously announced in 2011 at Hannover Fair as part of the German High-Tech Strategy, and since then it has taken hold across the world.

However, there is no universally accepted definition, as it has taken on different meanings and connotations as it spread across the world. Most would agree that industry 4.0 aims to improve productivity, efficiency, flexibility and overall competitiveness in manufacturing and industrial sectors by leveraging these advanced technologies and concepts, but few agree on the included technologies or scope and reach of the topic.

This means it is up to every company to come up with its own definition to figure out how to take advantage of all these technologies collectively to thrive in this transformative time right now.

Figure 1: Digital transformation framework requires changes to how people, processes and technologies use data. Key elements include updated digital infrastructure, system integration, digital skills and training, with appropriate leadership and vision. Courtesy: Jeff Winter, Hitachi Solutions

The three biggest ways that Industry 4.0 is changing how companies approach automation, controls and instrumentation are:

1. Data-driven decision making and adaptability: The massive amount of data generated by automation, control and instrumentation systems in Industry 4.0 provides valuable insights into industrial processes. Companies are investing in advanced data analytics and visualization tools to make better-informed decisions, optimize processes and improve overall efficiency. Additionally, Industry 4.0 encourages the development of adaptive and flexible automation systems that can respond to changing production requirements and customer demands. This includes the use of modular production lines, collaborative robots (cobots), and reconfigurable manufacturing systems, allowing companies to adjust operations quickly and efficiently.

2. Reaction to prediction: Industry 4.0 technologies have enabled a shift from reactive process to predictive and prescriptive ones. In traditional industrial settings, companies would typically rely on human intervention to monitor, analyze and control processes. This reactive approach often led to delayed responses, higher downtime and increased costs due to inefficiencies and errors. By using advanced sensors, smart devices and real-time data analytics, companies can monitor and analyze processes continuously, allowing them to predict potential issues and optimize operations based on historical data and trends.

   Predictive maintenance, for example, enables companies to anticipate equipment failures and schedule maintenance to avoid downtime and reduce costs. By employing AI and machine learning algorithms, companies can automatically adjust control parameters and make real-time decisions to achieve optimal performance. These algorithms also can recommend specific actions to operators, ensuring that the right decisions are made at the right time.

3. Enhanced connectivity and interoperability: Industry 4.0 emphasizes seamless connectivity among machines, sensors, control systems and data platforms. This enhanced connectivity allows for better monitoring, control and optimization of industrial processes. Companies are adopting open communication protocols, wireless technologies and edge computing to facilitate seamless data exchange and integration among various systems. This interconnectedness enables companies to have a comprehensive understanding of their operations, leading to more efficient and agile decision-making.

Q: Is there any official Industry 5.0, or are those using that term merely suggesting that the world isn’t moving quickly enough?

Winter: The term “Industry 5.0” does not have a specific originator, as it has been used and developed by various experts, organizations and governments to describe the next phase of industrial evolution. The definition of Industry 5.0 also has been shaped by these various stakeholders, which include practitioners, academics, policymakers and technology experts. In general, Industry 5.0 envisions a future where humans and advanced technologies like artificial intelligence (AI), robotics and automation work together in a more harmonious and efficient manner, combining the best of human creativity, empathy and judgment with the precision, speed and scalability of advanced technologies.

That being said, since we are just getting started with Industry 4.0, and relatively few people are talking about Industry 5.0 (at least according to Google Trends) in comparison to Industry 4.0, I would say we should focus on Industry 4.0 first!

Figure 2: Smart manufacturing enablers and enhancers include technologies and concepts that help manufacturers take advantage of Industry 4.0 opportunities. Courtesy: Jeff Winter, Hitachi Solutions

Q: How does smart manufacturing differ from Industry 4.0?

Winter: The terms Industry 4.0 and smart manufacturing are often used interchangeably, but I would argue they are different concepts with different areas of focus.

Smart manufacturing is an advanced approach to industrial production that leverages cutting-edge technologies, data analytics and automation to optimize manufacturing processes, improve efficiency, and enable more flexible and responsive systems. It represents a paradigm shift in the way products are designed, produced and distributed. The primary objective of smart manufacturing is to increase productivity, efficiency and flexibility while reducing waste, energy consumption and operational costs. The scope typically includes the entire manufacturing value chain including product design and development, production planning, supply chain management, production, quality control and distribution.

Joint Working group 21 (JWG21) was established as a collaboration effort between the International Organization for Standardization (ISO) and the International Electrotechnical Commission (IEC) to help formally define “Smart Manufacturing” that could be used in international standards as part of a unifying reference model. In 2021, they came up with the following definition:

Manufacturing that improves its performance aspects with integrated and intelligent use of processes and resources in cyber, physical and human spheres to create and deliver products and services, which also collaborates with other domains within enterprises’ value chains.

Note 1: Performance aspects include agility, efficiency, safety, security, sustainability or any other performance indicators identified by the enterprise.

Note 2: In addition to manufacturing, other enterprise domains can include engineering, logistics, marketing, procurement, sales or any other domains identified by the enterprise.

Industry 4.0, however, is a much broader concept that really describes the current era, the fourth industrial revolution. It refers to the ongoing transformation of traditional industries due to the increasing adoption of digital technologies. Industry 4.0 not only includes smart manufacturing but also extends to other functions, such as logistics and supply chain, transportation, energy and even healthcare and retail. The plan is for the definition to make its way into all other relevant ISO and IEC standards.

Figure 3: Industrial AI use, according to IoT Consortium, requires considering how to digitize, extract and transform data; analyze, detect and diagnose; optimize; generate; prescribe; predict; and do/act. Courtesy: Jeff Winter, Hitachi Solutions

Q: What does Industry 4.0 and smart manufacturing mean for industrial automation, controls and instrumentation for end users, machine builders/original equipment manufacturers and system integrators?

Winter: The main beneficiary of smart manufacturing is obviously manufacturers. From a controls and automation perspective, manufacturers can expect several benefits such as:

• Increased productivity: Advanced automation and control systems can optimize production processes, leading to higher output and better resource utilization.

• Enhanced process control: End users can monitor and adjust production processes in real time, ensuring consistent product quality and reducing the likelihood of defects or waste.

• Reduced downtime: Predictive maintenance enabled by advanced automation can help prevent unexpected equipment failures and minimize production downtime.

• Better data-driven decision-making: Real-time data from automated systems can help end users make more informed decisions about process improvements, resource allocation and other aspects of production.

Machine builders and system integrators jointly will experience a completely different shift in their business and operating models as a part of Industry 4.0. A few ways machine builder and system integrator businesses will adapt include:

• Value proposition shift: As customers demand more intelligent, interconnected machines, the value proposition of machine builders and systems integrators shifts from simply providing hardware to delivering smart, data-driven solutions. This requires developing new capabilities in software, analytics and connectivity.

• Servitization: Industry 4.0 enables all companies, but especially machine builders and systems integrators, an ability to offer digital services through taking advantage of remote connectivity and the ability to provide additional value from all the data insights gained. This includes things such as remote monitoring, predictive maintenance, over-the-air updates and optimization services. This can even lead to entirely new business models where subscription-based services replace larger CAPEX purchases and outcome-based contracts replace traditional scope of works.

• Collaboration and partnerships: The increased complexity and interdisciplinary nature of Industry 4.0 technologies encourage machine builders and systems integrators to form strategic partnerships with other technology providers, such as software developers, data analytics companies and IoT platform providers. Fewer companies will attempt to be the “one-stop shop” and instead show how they are part of an end-to-end ecosystem that can holistically help manufacturers transform their organizations.

Figure 4: Triangle of success for digital transformation includes working through new knowledge, skills and attitudes to create a new vision. Digital transformation is a broader concept that encompasses the strategic and organizational changes required to fully leverage digital technologies, which often involve rethinking business models, processes and customer experiences. Courtesy: Jeff Winter, Hitachi Solutions

Q: What are best practices for controls and automation engineers in the era of Industry 4.0?

Winter: The transition from Industry 3.0 to Industry 4.0 has brought significant changes to the knowledge and skills required to be a successful controls and automation engineer. Some of the biggest differences include:

• Continuous learning a growth mindset: Technological innovation and market conditions are changing so quickly failure to react quickly can be catastrophic for a company. It also can make knowledge/skill today be obsolete in a short amount of time. It is imperative to dedicate time to stay updated with the latest developments in automation, controls and Industry 4.0 technologies. This includes pursuing relevant certifications, attending workshops, reading publications and participating in industry conferences.

• Spread your wings into new disciplines: The walls between disconnected fields engineering and organizational departments are becoming very blurry. Embrace a multidisciplinary mindset by understanding the interdependencies between various technologies such as mechanical, electrical, software engineering, IT, networking and other areas. This will help you develop a more holistic understanding of the systems you work with and identify opportunities for improvement.

• Focus on cybersecurity: As Industry 4.0 relies heavily on connected systems and data exchange, cybersecurity is paramount. Familiarize yourself with cybersecurity best practices, such as secure communication protocols, encryption and access control. Also, and ensure they are being implemented in projects.

• Think like an analyst: Those that capture and harness the power of data will be the most successful in the area of Industry 4.0. Develop skills in data analysis and visualization to take advantage of all data generated by smart manufacturing systems. This will enable users to identify trends, detect anomalies and make data-driven decisions to optimize processes and improve overall efficiency. 

Q: How do cyber-physical systems, digitalization, digital transformation, digital twins and the industrial Internet of Things (IIoT) fit in?

Winter: All of these concepts and technologies are interconnected and work together to create the foundation of smart manufacturing as part of Industry 4.0. When we compare Industry 3.0 to Industry 4.0, one of the key defining differences is the ability to capture and harness the power of data, which is mostly generated through combining IoT when combining the digital and virtual worlds together.

Cyber-physical systems (CPS) refer to types of technologies that integrates digital and physical systems to enable real-time communication and control. They involve embedded computers and networks that monitor and control physical processes, with feedback loops where physical processes affect computations and vice versa. The concept applies well beyond manufacturing, including health care and medical devices, smart cities, smart buildings and other areas. Often times, this concept is used for description purposes and understanding, rather than any specific solution, product or strategy used as part of smart manufacturing.

Digital twins and IoT are two of the many technologies that would fall under the umbrella of Industry 4.0. A digital twin is a virtual replica of a physical asset or system that can be used to simulate, analyze and optimize its performance. In Industry 4.0, digital twins enable manufacturers to better understand their production processes, predict maintenance needs, optimize asset performance and reduce downtime. The IIoT refers to the interconnection of industrial devices, machines and systems via the internet, enabling these systems to collect and exchange data. In the context of smart manufacturing and Industry 4.0, the IIoT helps create a connected production environment where data can be collected and analyzed in real time, leading to better decision-making, improved efficiency and reduced operational costs.

Digitalization and digital transformation are not technologies, but rather concepts to describe processes related to the use of digital technologies.

Digitalization refers to the process of converting analog information or processes into digital formats. It is a narrower concept, primarily focused on the technical aspects of adopting digital tools and technologies. Digital transformation is a broader concept that encompasses the strategic and organizational changes required to fully leverage digital technologies, which often involve rethinking business models, processes and customer experiences.

Figure 5: Relationships between the physical and digital worlds vary depending on if manual or automated data flows are used and can include digital model, digital shadow and digital twin. Courtesy: Jeff Winter, Hitachi Solutions

Q: Is there a difference between digital transformation and industrial digital transformation?

Winter: Yes. Digital transformation is a broader concept that encompasses the integration of digital technologies into all aspects of a business or organization, while industrial digital transformation specifically focuses on leveraging digital technologies to optimize and transform operations in the manufacturing and industrial sectors. Most people think of industrial digital transformation as “Industry 4.0.” While there may be some overlap in the technologies used in digital and industrial digital transformation, the focus and applications of these technologies can vary. Both may involve the use of IoT devices, data analytics and AI. In industrial digital transformation, these technologies may be applied to monitor production equipment, predict maintenance needs or optimize energy consumption in a factory setting.

When looking at manufacturing, several interactions make an industrial digital transformation more challenging than other industries.

• Complexity of manufacturing processes: Manufacturing involves numerous stages, such as product design, raw material procurement, production, assembly, quality control, packaging and distribution. Each stage has its own set of processes, tools and equipment, which makes it challenging to implement digital technologies in a way that addresses the entire value chain effectively.

• Integration with physical systems: Unlike banking, which mostly deals with digital data and transactions, manufacturing involves transforming physical materials into finished goods. This requires connecting these physical assets with digital technologies, such as IoT devices, sensors and actuators. This integration can require advanced engineering solutions, unique cybersecurity measures and real-time data- processing capabilities that aren’t experience in other industries.

• Skilled workforce: The successful implementation of digital transformation in manufacturing requires a workforce skilled in both traditional manufacturing processes and advanced digital technologies. Theis need for a “dual-skilled” workforce can present unique challenges in terms of training and upskilling employees. The talent pool for the skills required is much lower than other industries. Typically, people with newer skills in data analytics, AI or application development aren’t flocking to the manufacturing industry. Not only will companies need to focus on culture and brand changes to attract the right type of talent, but they will most likely have to spend more time and resources on upskilling and reskilling employees than other industries to fill the gap.

Q: Where can people go for more information?

Find more information at www.hitachisolutions.com along with the following and other LinkedIn posts:

Jeff Winter is senior director industry strategy, manufacturing, Hitachi Solutions, and an industry expert on Industry 4.0 on LinkedIn; edited by Mark T. Hoske, content manager, Control Engineering, CFE Media and Technology, mhoske@cfemedia.com.

KEYWORDS: Industry 4.0, smart manufacturing, digital transformation

CONSIDER THIS

Are you meeting your Industry 4.0 metrics for success?

Do you have experience and expertise with the topics mentioned in this content? You should consider contributing to our CFE Media editorial team and getting the recognition you and your company deserve. Click here to start this process.