Industry 4.0 revolutionizes how companies manufacture, improve, and distribute their products. Manufacturers are integrating new technologies, including the Internet of Things (IoT), cloud computing and analytics, and AI and machine learning, into their production facilities and operations. 64% of surveyed CxOs from outperforming industrial product companies already have it.
They have begun investing in AI/cognitive capabilities. At the same time, 67% of surveyed industrial products CxOs expect AI/cognitive abilities to play an essential role, and 89% of watched CxOs from outperforming industrial products companies say they plan to invest in AI/cognitive for quality control. Generally speaking, the industrial products industry is awash with data.
Instrumentation, sensors, machinery, automation systems, production and operation, maintenance records, and health and safety applications collectively produce a constant data flow. Industrial product enterprises need technology that supports the vertical delivery of insightful data throughout the organization to meet consumer needs and aim for continuous process improvement.
To address operating and market concerns—and deliver on the promise of Industry 4.0—a small group of financial outperformers uses the cognitive abilities of Artificial Intelligence (AI) to do things differently. This article will explore how developing smart factories provides an incredible opportunity for the manufacturing industry to enter the fourth industrial revolution.
Understanding What Industry 4.0 (The Fourth Industrial Revolution) Entails
Synonymous with intelligent manufacturing, Industry 4.0 is the realization of the digital transformation of the field, delivering real-time decision-making, enhanced productivity, flexibility, and agility. Realistically, these intelligent, technology-driven factories are equipped with advanced sensors, embedded software, and robotics that collect and analyze data, allowing for better decision-making.
From steam-propelled (the original industrial revolution), electricity-powered (the second), preliminary automation and machinery-engineered (the third), to cyber-physical systems—or intelligent computers—they are all shaping the Fourth Industrial Revolution to empower the new age industries. Even higher value is created when data from production operations are combined.
Especially when combined with operational data from ERP, supply chain, customer service, and other enterprise systems. It creates new levels of visibility and insight from previously siloed information. These digital technologies lead to increased automation, predictive maintenance, self-optimization of process improvements, and a new level of efficiency and responsiveness.
There are also improvements in robotics. Augmented reality, machine automation, and more: the 21st-century industrial revolution is digital. These new customer experiences were not previously possible. Industry 4.0 brings these inventions beyond the previous realm of possibility with four foundational types of disruptive technologies that can be applied throughout the value chain.
They are as follows:
- Connectivity, data, and computational power: cloud technology, the Internet, blockchain technology, sensors
- Analytics and intelligence: advanced analytics, machine learning, artificial intelligence
- Human-machine interaction: Virtual Reality (VR) ) and Augmented Reality (AR), robotics and automation, autonomous vehicles
- Advanced engineering: additive manufacturing (such as 3D Printing Technology), renewable energy, nanoparticles
Analyzing the large amounts of big data collected from sensors on the factory floor ensures real-time visibility of manufacturing assets. It can provide tools for performing predictive maintenance to minimize equipment downtime. Using high-tech IoT devices in smart factories leads to higher productivity and improved quality. We can replace manual inspection business models with AI.
As such, it reduces manufacturing errors and saves money and time. With minimal investment, quality control personnel can set up a smartphone connected to the cloud to monitor manufacturing processes from virtually anywhere. By applying machine learning algorithms, manufacturers can detect errors immediately rather than at later stages when repair work is more expensive.
This is increasingly vital as disruptive technologies transform job requirements, but the outlook on reskilling differs geographically. In Europe, 94 percent of surveyed executives believe the balance between hiring and reskilling should be equal or tip toward reskilling, compared with only 62 percent of US respondents. For your information, the end-to-end skill transformation has three phases.
Including:
- Scout—Analyze the skills required to achieve a company’s ambitions
- Shape—Identify talent gaps that must be addressed and design the program infrastructure to handle them
- Shift—Develop and implement content and delivery mechanisms to train workers at scale
A conversation with Francisco Betti (head of the Platform for Shaping the Future of Advanced Manufacturing and Production, launched by the World Economic Forum in 2017) and the CEOs of Flex, Protolabs, and Western Digital offers perspective and real-world insights on building workforce capabilities and shifting mindsets for successful digital transformations in manufacturing.
The benefits can go far beyond business outcomes. In the words of Western Digital CEO David Goeckeler, “It’s not just about our company being better and us being prepared for the future; it’s about all of our employees being ready for that future—keeping them at the center, having them highly engaged, all of the reskilling, getting them excited about what the future holds.”
From Steam To Sensors: The Historical Context For Industry 4.0 Businesses
Of course, synonymous with intelligent manufacturing, Industry 4.0 is the realization of the digital transformation of the field, delivering real-time decision-making, enhanced productivity, flexibility, and agility. Industry 4.0 concepts and technologies can be applied across all industrial companies, including discrete and process manufacturing, oil and gas, mining, and other segments.
Technology, however, is only half of the Industry 4.0 equation. Companies must ensure that their workers are adequately equipped to thrive in the Fourth Industrial Revolution, primarily through upskilling and reskilling and hiring new people when necessary. Upskilling means that employees learn new skills to help them in their current positions as the skills they need evolve.
Reskilling is the real challenge: workers are retrained with new skills that will enable them to fill different positions within their companies. Industry 4.0—also called the Fourth Industrial Revolution or 4IR—is the next phase in the digitization of the manufacturing sector, driven by disruptive trends, including the rise of data and connectivity, analytics, and human-machine interaction.
Industry 4.0, the Fourth Industrial Revolution, and 4IR all refer to the current era of connectivity, advanced analytics, automation, and advanced manufacturing technology that has been transforming global business for years. This wave of change in the manufacturing sector began in the mid-2010s and holds significant potential for operations and the future of production.
A. First Industrial Revolution
Starting in the late 18th century in Britain, the first industrial revolution helped enable mass production by using water and steam instead of purely human and animal power. Finished goods were built with machines rather than painstakingly produced by hand.
B. Second Industrial Revolution
A century later, the Second Industrial Revolution introduced assembly lines and the use of oil, gas, and electric power. These new power sources, along with more advanced communications via telephone and telegraph, brought mass production and some degree of automation to manufacturing processes.
C. Third Industrial Revolution
The third industrial revolution, which began in the middle of the 20th century, added computers, advanced telecommunications, and data analysis to manufacturing processes. The digitization of factories began by embedding programmable logic controllers (PLCs) into machinery to help automate some processes and collect and share data.
D. Fourth Industrial Revolution
We are now in the fourth industrial revolution, also called Industry 4.0. Characterized by increasing automation and the employment of intelligent machines and factories, informed data helps produce goods more efficiently and productively across the value chain. Flexibility is improved so that manufacturers can better meet customer demands using mass customization—ultimately seeking to achieve efficiency with, in many cases, a lot size of one. An intelligent factory can achieve information transparency and better decisions by collecting more data from the factory floor and combining that with other enterprise operational data.
Why The Fourth Industrial Revolution Matters To Futuristic Businesses
Generally speaking, organizations in the global industrial products industry face significant challenges: cost pressures, increased regulations, disruptive technologies, and the increasingly costly delivery of raw resources. High volatility in commodity prices has put severe pressure on company margins and can quickly expose inefficient operations. Processes, workflows, and procedures are vital.
Notwithstanding, the understanding of performance is dramatically changing. Functions can no longer work in linear execution or isolation of other functional work streams such as engineering, maintenance, and planning. Instead, the value chain must be integrated to support the fluctuating demand cycles and higher-cost supply activities. New AI technologies can make sense here.
Especially in terms of the abundance of data through systems that can adapt and learn. By expanding digital intelligence adoption, AI technologies can help executives translate data into insights to drive more incredible innovation and better operational and financial decisions. To understand how organizations can better plan for AI adoption, consider the IBM Institute for Business Value (IBV).
In collaboration with Oxford Economics, they surveyed over 6,000 C-suite members and heads of functions worldwide, including 300 industrial product respondents. The goal was to understand better their considerations, expectations, and objectives in applying Artificial Intelligence technology and machine learning solutions to the most pressing business challenges and opportunities.
The Most Common Advanced Technologies Driving Industry 4.0 Businesses
As mentioned, Industry 4.0 means more intelligent manufacturing. As a result, manufacturers can initiate a new wave of efficiency without significant investments by integrating AI, IoT, analytics, and other connected technologies into factory operations. Technically, manual inspection is more complicated as electronic components have become more complex, and systems get denser.
Technicians working at a station can become fatigued inspecting complex assemblies. This can lead to defects being missed or caught later when repair costs increase. Traditional automated inspection systems, generally rules-based, aim to capture all faults, but they often generate false positive calls. These then require extra manual inspections.
Generally speaking, workforce engagement is vital to a successful 4IR transformation. Indeed, even a company with the best tools, newest technology, and immense resources is unlikely to successfully scale up a 4IR change if the workforce is not engaged. A concerted focus on people has also helped organizations build resilience by assisting workers to develop new skills.
In particular, so that the business can respond more flexibly to change. In practice, this could entail rethinking training and skill development pathways and making structural changes for the longer term. Preliminary data indicate that successfully scaling 4IR technology makes supply chains more efficient and working hours more productive, reduces factory waste and has other benefits.
1. Cybersecurity
Manufacturing companies have not always considered the importance of cybersecurity or cyber-physical systems. However, the same connectivity of operational equipment in the factory or field (OT) that enables more efficient manufacturing processes also exposes new entry paths for malicious attacks and malware. When undergoing a digital transformation to Industry 4.0, it is essential to consider a cybersecurity approach that encompasses IT and OT equipment.
2. Internet of Things (IoT)
The Internet of Things (IoT) is a critical component of intelligent factories. Machines on the factory floor are equipped with sensors with an IP address, allowing the engines to connect with other web-enabled devices. This mechanization and connectivity enable large amounts of valuable data to be collected, analyzed, and exchanged.
3. Cloud Computing
Cloud Computing is also a cornerstone. Realizing smart manufacturing demands connectivity and integration of engineering, supply chain, production, sales and distribution, and service. Cloud helps make that possible. In addition, the typically large amount of data being stored and analyzed can be processed more efficiently and cost-effectively with the cloud. The tech can also reduce startup costs for small- and medium-sized manufacturers who can right-size their needs and scale as their business grows.
4. AI And Machine Learning
Artificial Intelligence Complete and Machine Learning (ML) allows manufacturers to take full advantage of the volume of information generated not just on the factory floor but across their business units and even from partners and third-party sources. AI and machine learning can create insights, providing visibility, predictability, and automation of operations and business processes. For instance, Industrial machines are prone to breaking down during production. Data collected from these assets can help businesses perform predictive maintenance based on machine learning algorithms, resulting in more uptime and higher efficiency.
5. Edge Computing
Real-time production operations demand means that some data analysis must be done at the “edge”— that is, where the data is created. This minimizes data latency if produced when a response is required. For instance, detecting a safety or quality issue may require near-real-time action with the equipment. The time needed to send data to the enterprise cloud and back to the factory floor may be too lengthy and depend on the network’s reliability. Edge computing means data stays near its source, reducing security risks.
6. Digital Twin
The digital transformation offered by Industry 4.0 has allowed manufacturers to create digital twins that are virtual replicas of processes, production lines, factories, and supply chains. A digital twin is created by pulling data from IoT sensors, devices, PLCs, and other objects connected to the internet. Manufacturers can use digital twins to help increase productivity, improve workflows, and design new products. By simulating a production process, for example, manufacturers can test changes to the process to find ways to minimize downtime or improve capacity.
7. Ultimate Learning
The Fourth Industrial Revolution could create products and services accessible and transmissible for businesses, consumers, and stakeholders throughout the value chain flow. There is also some form of improved learning and development. For example, with extended competencies and skills through hard, soft, and digital skills and apprenticeship. As well as empowerment and ownership. For instance, outcome and results-oriented steering or encouraging workers to make their own decisions.
8. Seamless Communication
Next are seamless collaborations and limitless connections (say, by working with cross-functional and multi-skilled teams or developing extended networks in the organization and beyond). This leads to impact and recognition (for example, by creating accountability for achievements or celebrating successes). There is also the worker’s voice (for instance, by using digital channels and data to gather input from workers’ voices or by seeking to understand their hidden needs).
How Industry 4.0 Technologies Are Changing The Manufacturing Industry
Industry 4.0 revolutionizes how companies manufacture, improve, and distribute their products. Manufacturers are integrating new technologies, including the Internet of Things (IoT), cloud computing and analytics, and AI and machine learning into their production facilities and operations. These intelligent factories have advanced sensors, embedded software, and robotics.
These tools and applications collect and analyze data, allowing for better decision-making. Even higher value is created when data from production operations is combined with operational data from ERP, supply chain, customer service, and other enterprise systems to create new levels of visibility and insight from previously siloed information.
Still, these digital technologies lead to increased automation, predictive maintenance, self-optimization of process improvements, and a new level of efficiency and responsiveness to customers not previously possible. Developing smart factories provides an incredible opportunity for the manufacturing industry to enter the fourth industrial revolution.
Analyzing the large amounts of big data collected from sensors on the factory floor ensures real-time visibility of manufacturing assets. It can provide tools for performing predictive maintenance to minimize equipment downtime. Using high-tech IoT devices in smart factories leads to higher productivity and improved quality. Below are a few roles of Industry 4.0 Technologies in the industry.
1. Errors Reduction
Replacing manual inspection business models with AI-powered visual insights reduces manufacturing errors and saves money and time. With minimal investment, quality control personnel can set up a smartphone connected to the cloud to monitor manufacturing processes from virtually anywhere. By applying machine learning algorithms, manufacturers can detect errors immediately rather than at later stages when repair work is more expensive. Industry 4.0 concepts and technologies can be used across all industrial companies, including discrete and process manufacturing, oil and gas, mining, and other industrial segments. There are various characteristics of a Smart Factory technology.
2. Data Analysis
Embedded sensors and interconnected machinery produce significant big data for manufacturing companies. Data analytics can help manufacturers investigate historical trends, identify patterns, and make better decisions. Smart factories can also use data from other parts of the organization and their extended ecosystem of suppliers and distributors to create deeper insights. Manufacturers can make production decisions based on sales margins and personnel by looking at human resources, sales, or warehousing data. A complete digital representation of operations can be created as a “digital twin.”
3. IT-OT integration
The intelligent factory’s network architecture depends on interconnectivity. Real-time data collected from sensors, devices, and machines on the factory floor can be consumed and used immediately by other factory assets and shared across enterprise software stack components, including Enterprise Resource Planning (ERP) and other business management software.
4. Custom Manufacturing
Smart factories can produce customized goods that meet customers’ needs more cost-effectively. Manufacturers aspire to achieve a “lot size of one” economically in many industry segments. By using advanced simulation software applications, new materials, and technologies such as 3D Printing Technology, manufacturers can easily create small batches of specialized items for particular customers. The first industrial revolution was about mass production, but Industry 4.0 was about mass customization.
5. Supply Chain
Industrial operations depend on a transparent, efficient supply chain, which must be integrated with production operations as part of a robust Industry 4.0 strategy. This transforms how manufacturers resource their raw materials and deliver their finished products. By sharing some production data with suppliers, manufacturers can better schedule deliveries. If, for example, an assembly line is experiencing a disruption, deliveries can be rerouted or delayed to reduce wasted time or cost. By studying weather, transportation partner, and retailer data, companies can use predictive shipping to send finished goods at just the right time to meet consumer demand. Blockchain is emerging as a critical technology to enable transparency in supply chains.
Industry 4.0 Digitization And Opportunities For Businesses Sustainability
As technology becomes denser, manufacturers may have to replace outdated automated inspection equipment to meet the needs of new products. Our experience is a plus for clients. Those who need computer vision get help from Visual Inspection experts who have implemented the solution through the best plants. Their real-world expertise helps clients achieve fast time to value.
The deep learning model, specific to each use case, typically takes hours to train by analyzing known images and videos. After connection to a camera, the model is ready for production and can be run on various systems or from the cloud. Analysis of operator feedback helps the model become more intelligent over time. The Fourth Industrial Revolution drove opportunities for sustainability.
And more importantly, these advances are inherently more sustainable than current business practices. Some people think productive operations are hard to square with environmental responsibility. Still, sustainable lighthouses challenge that notion: 4IR transformations facilitate a viable eco-efficiency that intrinsically meshes sustainability with competitive excellence.
Eco-efficiency includes three dimensions of digital technology:
- enabling data-informed actions in production and the broader end-to-end value chain
- realizing improvements across performance indicators, such as cost, agility, convenience, and quality
- driving sustainability gains by limiting consumption, resource waste, and emissions
There are a few examples of how Industry 4.0 technologies maximize efficiency and minimize waste.
Consider the following:
- One Singapore lighthouse decreased its scrap output from building semiconductors by 22 percent in an intelligent factory enabled by the industrial Internet of Things, or IIoT. (See a related Explainer, “What is the Internet of Things?” for more.)
- Schneider Electric’s smart factory in Lexington, Kentucky, combined IoT connectivity and predictive analytics to lower energy use by 26 percent, CO2 emissions by 30 percent, and water use by 20 percent.
- Sixty percent of the 103 lighthouses identified by the Global Lighthouse Network include sustainability among their top five Fourth Industrial Revolution use cases.
More broadly, lighthouses demonstrate how 4IR technologies can promote responsible growth in the long term. How?
Basic Actions:
- Environmental: Taking care of our planet and the surrounding environment. Areas of focus for lighthouses in this category include energy, water, waste, greenhouse gas emissions, and the circular economy.
- Social: Building a more robust workforce and community. For lighthouses, focus areas might include human capital development, the worker’s voice, health and safety, and labor standards.
- Governance: Establishing a set of practices, controls, and procedures to govern, make decisions, and meet the needs of stakeholders. This can encompass focus areas such as ownership, accountability, business ethics, and governance structure.
The Overall Industry 4.0 Impacts On The Majority Businesses Economy
Building a hybrid multicloud IT infrastructure is critical in digital transformation for manufacturers seeking to use Industry 4.0. Hybrid multicloud is when a company has two or more public and private clouds to manage its computing workloads. This allows them to optimize workloads across all their cloud shells, as some environments are better suited.
Especially to or more cost-effective for specific workloads. Manufacturers looking for digital transformation and a secure, open environment can move their existing workloads from their on-premises location to the best possible cloud environment. Industry 4.0 will continue to have a significant impact on the economy. The greatest economic boons will go to the fastest-acting companies.
According to a 2018 McKinsey Global Institute analysis, Industry 4.0 front-runners—facilities well on their way to adopting AI and other advanced technologies by 2025—can expect a 122 percent positive cash flow change. Follower companies can expect just 10 percent, while companies that wholly fail to adopt AI could see a 23 percent downturn.
Industry 4.0 is also projected to transform the workforce’s skill sets by shifting the standards for sought-after talent. Over the coming decade, we will see these changes as more and more companies embrace robotics.
There is a demand for:
- Physical and manual skills in repeatable tasks, like those on assembly lines, will decline by nearly 30 percent.
- Basic literacy and numeracy skills will decline by almost 20 percent.
- Technological skills such as coding will rise by more than 50 percent.
- Complex cognitive skills will rise by about 33 percent.
- High-level social and emotional skills will rise by more than 30 percent.
In 2025, the value creation potential of Industry 4.0 for manufacturers and suppliers is expected to reach $3.7 trillion.
How The Fourth Industrial Revolution Is Transforming Business Operations
Every industry will be transformed during the Fourth Industrial Revolution, but some to a greater degree than others. The nature of the Industry 4.0 transition will differ by the specific types of technology being adopted and organizations’ existing infrastructure and skills. The transformation can be broken down into three archetypes of adoption pathways for successful businesses.
Including:
- Accelerated. Regardless of a company’s existing tech infrastructure (whether advanced or nonexistent), specific inexpensive digital, augmented reality, and automation solutions are rapidly adoptable without transition headaches.
- Differential. The existing tech infrastructure will affect how quickly some technologies are adopted. Companies with less foundational information technology (IT), operations technology, and data infrastructure will need time to transition. More advanced companies are better equipped for quick implementation.
- Deferred. Even in companies with an advanced tech infrastructure, adopting the most cutting-edge innovations (such as full end-to-end automation) will be slow because of the high level of required capital expenditure and the unclear long-term payback.
Operationally intensive sectors, such as manufacturing, transportation, and retailing, will experience the most significant change because many companies employ massive numbers of people for tasks suited to automation or digitization. Operations-intensive sectors have 1.3 times more automation potential than others do. Analysis indicates up to 58% automated work activities.
They are automated with current technology in these operations-intensive sectors. Education, by contrast, is projected to undergo the slightest change during Industry 4.0; only 25 percent of the sector’s work is automatable.
Summary Notes:
The solution’s intuitive toolset lets subject matter experts without coding or deep learning expertise manage the models and train new ones. This reduces clients’ personnel costs and encourages them to explore new applications in inspection, worker safety, maintenance, video editing, sample analysis, and other areas. More competent manufacturing helps fulfill the promise of Industry 4.0.
From augmented reality, cloud hosting, and Natural Language Processing (NLP) to machine automation, the 21st-century industrial revolution is digital. Industry 4.0, the Fourth Industrial Revolution, and 4IR all refer to the current era of connectivity, advanced analytics, automation, and advanced manufacturing technology that has been transforming global business for years.
This Industry 4.0 wave of change in the manufacturing sector began in the mid-2010s and holds significant potential for operations and the future of production for many businesses. Furthermore, before 2014, the Google search term “Industry 4.0” was practically nonexistent, but by 2019, 68 percent of respondents to a McKinsey global survey regarded Industry 4.0 as a top strategic priority.
Whereby 70% said their companies were already piloting or deploying new technology. On that note, 4IR builds on the inventions of the Third Industrial Revolution—or digital revolution—which unfolded from the 1950s to the early 2000s and brought us the beloved computing technology—we so much use today—electronics, the Internet, or the World Wide Web (WWW), and much more.
