Industry 4.0 Versus 5.0: What’s the Difference?
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Envisioning a world without the mechanization of labor, mass production of goods, and connected transportation—cornerstones of the First Industrial Revolution—is challenging. Nearly 200 years later, manufacturing has advanced significantly, from 3D-printed homes and collaborative robots (cobots) to augmented reality for job training.
In this article, we cover the pivotal technologies and concepts from both Industry 4.0 and Industry 5.0, and their implications for the future of manufacturing.
What Is Industry 4.0?
Industry 4.0, also known as the Fourth Industrial Revolution, is defined by the emergence of digital industrial technology, notably cyber-physical systems. This evolution has facilitated highly innovative and efficient collaboration between humans and machines, which has in turn enabled the creation of smart, integrated factories and operations. The ultimate goal of Industry 4.0 is to create tailored, versatile manufacturing solutions by leveraging data-driven insights.
Industry 4.0 was first unveiled in 2011, and it has gradually gained traction with manufacturing professionals throughout the decade. Many of Industry 4.0’s cutting-edge technologies work together to create a cohesive manufacturing environment. For example, Internet of Things integration and AI are only made possible through cloud computing. Below are several of Industry 4.0’s key technologies.
Additive Manufacturing (3D Printing)
Additive manufacturing, commonly known as 3D printing, has transformed production processes. It has tremendous benefits that are appealing to employees, company leaders, and organizations as a whole, such as minimized waste, streamlined supply chains, and extended product lifespan. The aerospace industry greatly benefits from this method due to the sector’s rigorous standards and limited production volume.
There are some obstacles to incorporating additive manufacturing into processes. Organizations who do not have individuals with sufficient knowledge and skills in additive manufacturing will struggle to incorporate it. Additional obstacles include the caliber of printed goods and a lack of cross-industry best practices.
Artificial Intelligence (AI)
Artificial intelligence, which includes machine learning, machine vision, and deep learning, has many uses in the manufacturing industry, including conducting quality assurance and sorting packages.
Manufacturers are launching generative AI with some trepidation due to the risk of misleading outputs. Though 70 percent of leaders indicated that they have invested in costly commercial AI models, more affordable open-source solutions may become the trend once their effectiveness is demonstrated.
Big Data & Data Analytics
Big Data organizes the information collected from manufacturers and forms meaningful diagnoses to help enhance operations in a variety of ways, like streamlining warehouse procedures, diagnosing performance issues, and forecasting demand.
Overcoming common roadblocks in data analytics, such as poor accuracy and security, is paramount to using Big Data for decision making.
Internet of Things (IoT)
The Internet of Things employs smart sensors and other gadgets to track things like machine functionality and environmental factors on a minute-by-minute basis.
Universally rolling out smart sensors in manufacturing is complicated by compatibility challenges between older and modern systems, the need for effective staff training and preparation, and data privacy and security considerations.
What Is Industry 5.0?
The Fifth Industrial Revolution, or Industry 5.0, was introduced in 2021 as a set of tools and technologies that build upon Industry 4.0. Industry 5.0 emphasizes using and developing advanced technologies while ensuring that production adheres to the welfare of both workers and our planet. The European Union’s push towards sustainability has been a major driver for Industry 5.0, aligning with global goals like climate neutrality by 2050.
Setting Ethical Guidelines
Ethics come into play in many aspects of the Fifth Industrial Revolution, such as:
- Bias in algorithms: AI and algorithms must be carefully reviewed, monitored, and overseen to mitigate biases.
- Shifting employment landscape: With technological advancements comes a reduced need for traditional roles, such as assembly line jobs. It’s important to train employees in new areas to address the changing needs of organizations.
- Ecological footprint: Organizations should incorporate green materials and sustainable operation strategies, and they should work to move to a circular manufacturing system to cut back on waste.
The global Industry 5.0 market is projected to increase from $65.8 billion in 2024 to $255.7 billion in 2029, reflecting a 31.2 percent compound annual growth rate.
Industry 5.0 in Action
Some of the top companies embracing and furthering the Fifth Industrial Revolution are:
- ABB
In 2023, ABB unveiled an automated flexible miniature circuit breaker (MCB) production line, which uses leading-edge artificial intelligence, automation, and digital methods. The line features seven robots and 16 custom automation devices that boost reliability and effectiveness. - Emerson
Emerson was named the 2024 “Industrial IoT Company of the Year” by IoT Breakthrough—making it Emerson’s sixth time winning this honor. This pioneering corporation is working to help manufacturers reach their environmental objectives through Ovation™ Green, a suite of software and automation solutions. - Honeywell
An important feature of Industry 5.0 is ensuring that workers have the ongoing education they need to work with rapidly advancing technologies. Honeywell advises leveraging virtual reality (VR) and simulation applications for training. - Rockwell Automation
Rockwell Automation seeks to improve human-machine interactions by increasing productivity and worker safety. The enterprise suggests that manufacturers can harness various approaches to advance to Industry 5.0, such as developing AI-native architecture and adopting converged integrated development environments (IDEs).
How to Prepare for Industry 5.0
The Rutgers University online Master of Engineering in Industrial and Systems Engineering prepares students for advancement in the evolving manufacturing industry. The program’s comprehensive curriculum consists of three required core courses and a number of technical elective course options, including in the areas of AI in decision making, engineering management and innovation strategy, and AI-enabled manufacturing.
Effects on Next-Generation Manufacturing
97 percent of industrial manufacturing CEOs indicated that continuing digital and technology transformation to deliver growth and operational advantages is either an important near-term priority.
Industry 4.0 and 5.0 will shape the future of manufacturing, driving expansion and boosting performance with technological advancements like artificial intelligence, digital twins, and machine learning. To elevate their businesses and meet their goals, manufacturers will need to develop organization-wide action plans.
While we don’t know exactly when Industry 6.0 will arrive or what it will entail, experts hypothesize that some machines will reach autonomy by 2050. Other key features may involve extraterrestrial manufacturing and the use of drones or flying factories in the industry.
In the meantime, Industry 5.0 concepts and Industry 4.0 technologies will continue to advance as human roles are redefined. Amidst digital advancements and increasing regulations, manufacturers will need to adopt new approaches to stay competitive, agile, and environmentally conscious.
Shape the Future of Industrial and Systems Engineering at Rutgers University
Unlock your potential with Rutgers’ online Master of Engineering in Industrial and Systems Engineering. You’ll gain cutting-edge skills in data analytics, AI, and optimization, preparing you to lead innovation across industries. With a flexible curriculum taught by industry experts, you’ll be ready to tackle complex challenges and advance your career in today’s data-driven world.
Rutgers School of Engineering is a place of possibilities—for students seeking success, for researchers seeking to create new technologies, and for faculty members and industry leaders seeking to form powerful and productive partnerships.
Rutgers University’s School of Engineering is a vibrant academic community whose richly diverse students and faculty are committed to globally sustainable engineering. Its mission is built on a commitment to fostering the integration of education and research to achieve transformational innovation that is ethically responsible and sustainable.
Download a brochure to learn more, or get started on your application today.
Key Strategies for Achieving Sustainable Supply Chains
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Supply chain operations have a major impact on our planet, contributing to the greenhouse gas (GHG) emissions that directly lead to biodiversity loss. Both individuals and companies rely on a flourishing environment, which is why many organizations are taking steps to mitigate their supply chain’s negative effects on biodiversity, such as Kering’s pledge to restore one million hectares of its supply chain by 2025.
Beyond environmental impact, maintaining a sustainable supply chain is important for continued growth and success: 97% of investment managers review a business’ supply chain sustainability standards when determining where to invest. Furthermore, with the Securities and Exchange Commission’s (SEC) recently established sustainability reporting rules and consumers’ increasing commitment to sustainable lifestyles, now is a crucial time to implement or improve green supply chain practices.
What is supply chain sustainability?
Supply chain sustainability is the conscious effort to incorporate integrity-driven behavior and green initiatives into all aspects of operations.
Source: SAP
Industrial and systems engineers play a pivotal role in supply chain design and process improvements. In this article, we discuss how you can strengthen your organization’s supply chain and ensure it is environmentally and socially sustainable, including key strategies such as utilizing a systems thinking approach, digital twin technology, resilience planning, and artificial intelligence and metaheuristics.
Systems Thinking
Systems thinking in supply chain involves considering the interconnectivity of the supply chain when analyzing and making optimizations, rather than focusing on each piece individually. For example, one area of a company may be working to reduce inventory levels to increase cash flow, while the goal of another department is to improve customer service. Since these goals are conflicting, it can be difficult to reach both, so they must be examined together.
By taking a look at the whole picture, companies can better understand their impact on the environment, take measures to prevent unforeseen outcomes, and brainstorm new ideas and processes.
One difficulty with the systems thinking approach is a lack of visibility. In some organizations, individuals may not have access to enough data to form a holistic view of their supply chain. In the 2024 Supply Chain Priorities and Challenges report, some of the top issues cited by respondents were a lack of cross-functional collaboration and poor data management.
“Every single company or organization needs employees with data analysis and optimization skills, whether it’s working on Wall Street, for a credit card company, or for telecommunications. This whole idea of optimizing a system or improving efficiency–who doesn’t want to do that?”
David Coit, Professor, Department of Industrial and Systems Engineering
Life Cycle Assessment
One example of systems thinking is life cycle assessment (LCA), which involves calculating the ecological footprint of a product or service from production to disposal. By completing a life cycle assessment, you can identify ways to make your offerings more sustainable.
The full product life cycle, also known as cradle-to-grave, consists of five phases:
1. Raw material extraction
2. Manufacturing and processing
3. Transportation
4. Usage and retail
5. Waste disposal
Source: Ecochain
To conduct a life cycle assessment, you’ll work through the following steps:
1. Objective and Purview: determine what you’re trying to glean from the assessment and how much data you’ll collect.
2. Life Cycle Inventory Analysis: collect the data you need for your analysis.
3. Life Cycle Impact Assessment: measure impact in selected categories.
4. Life Cycle Interpretation: evaluate your study, draw conclusions, and make recommendations.
Completing life cycle assessments manually can be time-consuming, but there are existing tools and software options to make it easier.
Completing life cycle assessments manually can be time-consuming, but there are existing tools and software options to make it easier.
Digital Twins
A digital twin is a virtual recreation of a physical process. Since the invention of the concept in the 1960s and its popularization in 2002, digital twin technology has been used in fields like healthcare, urban planning, and even aerospace engineering.
Now, companies are seeing the value of digital twins in the supply chain. This technology enables organizations to test various hypothetical situations and monitor their effects, allowing them to predict disruptions and utilize a centralized platform to make business decisions.
Digital twins can help identify opportunities to make your supply chain more sustainable, including:
- Reducing greenhouse gas emissions in facilities and transportation
- Cutting back on waste
- Improving water efficiency
- Making forecasts and data-driven decisions
Resilience Planning
Supply chain disruptions are on the rise. Companies should anticipate disturbances lasting one month or more every 3.7 years, making resilient system design increasingly important.
Diversifying suppliers is one way to improve resilience. Instead of relying on just one supplier, having a variety of options to fall back on can help in the event of a disruption. This practice also gives companies the opportunity to select the most eco-friendly suppliers.
Another approach is nearshoring, which involves a company moving its operations or manufacturing closer to their main markets as a way to reduce costs, streamline production, and enhance market potential. By shortening the supply chain, companies can build resilience and react more quickly to changing conditions.
In 2022, international shipping emissions reached a new high of 710 million metric tons. Nearshoring makes the supply chain more sustainable by cutting back needless waste and excess transportation, which reduces carbon emissions. Additionally, smaller, localized facilities are typically more environmentally friendly. Nearshoring can also contribute to a circular economy and a more collaborative business model by acquiring materials from nearby sources.
Gartner’s Supply Chain Top 25 list for 2024 features the best supply chains based on financial information, corporate and social responsibility measures, and public consensus. Among the focuses for these companies is going a step beyond resiliency, and taking measures to make their supply chains “antifragile.”
Artificial Intelligence and Metaheuristics
AI is a major force in supply chain, which companies are investing in so they may optimize and innovate their operations, and become more sustainable. Coca-Cola has entered a $1.1 billion partnership with Microsoft to utilize its strategic cloud and AI platform to revamp its supply chain operations. Environmental goals from this collaboration include waste reduction and minimized ecological effects from supply chain activities.
Generative AI can assist with sustainability efforts by proficiently pulling and examining data to find trends and inconsistencies. It can also help companies choose sustainable suppliers, prepare for disturbances, and enhance product design.
Metaheuristics, or optimization algorithms, can be useful in enhancing sustainable supply chain management due to their ability to solve intricate problems and achieve a state where operations are both eco-friendly and lucrative. Algorithms can be used to inform sourcing decisions, manage logistics, oversee stock, reduce energy consumption, and more. Some of the ways that metaheuristics are being used in sustainable supply chain management include:
- Utilizing hybrid algorithms to solve complicated problems
- Combining metaheuristics with the power of blockchain and the Internet of Things (IoT)
- Accounting for unpredictability
- Building algorithms to support synergism between all components in the supply chain
The steps businesses take today toward green supply chain management will not only protect our environment and future, but strengthen operations. Organizations still have a lot of ground to cover in executing sustainable supply chain practices, but taking advantage of some of the tools and processes we’ve discussed can help.
Prepare for the Future of Supply Chain
Students in the 30-credit Rutgers University online Master of Engineering in Industrial and Systems Engineering build skills in data science, optimization and AI, probability and statistics, logistical systems and supply chains, engineering project management, and sustainable systems.
“By taking a systems approach to analyzing and solving problems, and strengthening students’ knowledge of AI, data science, additive manufacturing, and optimization the degree program provides critical skills for those working within the supply chain,” says Mohsen Jafari, Rutgers Engineering professor and chair of the Department of Industrial and Systems Engineering.
The program includes a technical elective, Supply Chain Engineering, which focuses on operations research and its applications in the design and analysis of marketing and distribution systems, including sales forecasting, inventory optimization, and logistics management.
About Rutgers University School of Engineering
Rutgers School of Engineering is a place of possibilities—for students seeking success, for researchers seeking to create new technologies, and for faculty members and industry leaders seeking to form powerful and productive partnerships.
Rutgers University’s School of Engineering is a vibrant academic community whose richly diverse students and faculty are committed to globally sustainable engineering. Its mission is built on a commitment to fostering the integration of education and research to achieve transformational innovation that is ethically responsible and sustainable.