Industry 4.0 is the fourth industrial revolution: factories where machines, products and business systems are connected and share data, so production decisions are made from live information and, more and more, carried out by software. The term was coined in Germany in 2011 and follows the three revolutions before it, which ran on steam, then electricity, then electronics and computers.
Fifteen years on, the idea is mainstream and unfinished. The World Economic Forum counts 223 factories in its Global Lighthouse Network as of January 2026, and Rockwell Automation’s May 2026 survey of 1,560 manufacturing decision makers finds 59% actively using smart manufacturing technology while only 43% of the data they collect is used effectively. This guide explains the term in plain words, then shows where real plants get stuck.
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In this guide
What is Industry 4.0 in simple terms?
What are the four industrial revolutions?
What is the difference between Industry 3.0 and Industry 4.0?
When did Industry 4.0 start, and who coined it?
What are the nine pillars of Industry 4.0?
What are the four design principles of Industry 4.0?
How does Industry 4.0 work in a plant?
What is the difference between Industry 4.0, smart manufacturing and a smart factory?
What is an example of Industry 4.0?
What are the benefits of Industry 4.0?
How many manufacturers have adopted Industry 4.0?
What are the challenges of Industry 4.0?
Why do Industry 4.0 programs stall at dashboards?
What are the stages of Industry 4.0 maturity?
Is AI part of Industry 4.0?
What is Industry 5.0?
How does a mid-size plant get started with Industry 4.0?
Where does Morsa fit in Industry 4.0?
What is Industry 4.0 in simple terms?
Industry 4.0 means the machines, the products moving through the plant and the software that runs the business are all connected, so what happens on the floor is known as it happens and can change what happens next. A press reports its own cycle count. A pallet knows which order it belongs to. A late shipment shows up in the schedule before the line runs dry. What changed is that the information moves.
The definitions most often quoted say the same thing from three angles.
Who | Definition | What it stresses |
|---|---|---|
acatech and the Industrie 4.0 Working Group, final report, April 2013 | “The first three industrial revolutions came about as a result of mechanisation, electricity and IT. Now, the introduction of the Internet of Things and Services into the manufacturing environment is ushering in a fourth industrial revolution.” | Networked machines and products; a national industrial strategy |
NIST, the US standards body, NIST IR 8107, 2016 | “Industrie 4.0 is a key initiative in Germany containing a technical strategy for achieving SMS” (smart manufacturing systems), aiming at “smart products, smart production systems, smart factories, and smart logistics.” | The American view: Germany’s program for what the US calls smart manufacturing |
PwC, quoted by the NIST Manufacturing Extension Partnership, 2019 | Industry 4.0 “connects machines, people, and physical assets into an integrated digital ecosystem” that generates, analyzes and communicates data “and sometimes takes action based on that data without the need for human intervention.” | Data generated, analyzed, communicated, and sometimes acted on |
The last words of the PwC version are the honest ones: the system “sometimes takes action.” Most Industry 4.0 technology is about seeing; the definition itself says acting happens only sometimes. Henning Kagermann, the acatech president who co-authored the concept, made the same point in the foreword to acatech’s maturity index: “Just as lean production is about far more than simply preventing waste, Industrie 4.0 is not merely a matter of connecting machines and products via the Internet.”
What are the four industrial revolutions?
The 2013 acatech report opens with a chart of four stages, and most later timelines trace back to it (acatech, 2013, Figure 1, citing DFKI 2011).
First (Industry 1.0)
When: End of the 18th century
What powered it: “Water- and steam-powered mechanical manufacturing facilities”
The marker: The first mechanical loom, 1784
Second (Industry 2.0)
When: Start of the 20th century
What powered it: “Electrically-powered mass production based on the division of labour”
The marker: The first production line, Cincinnati slaughterhouses, 1870
Third (Industry 3.0)
When: Start of the 1970s
What powered it: “Electronics and IT to achieve further automation of manufacturing”
The marker: The first programmable logic controller (PLC), Modicon 084, 1969
Fourth (Industry 4.0)
When: Today
What powered it: Cyber-physical systems: machines, products and software that sense, compute and communicate
The marker: The term Industrie 4.0, 2011
The periods, the quoted descriptions and the first three markers are acatech’s. acatech gives the fourth revolution no dated marker; the 2011 naming and the fourth row’s description are ours.
What is the difference between Industry 3.0 and Industry 4.0?
Industry 3.0 automated tasks; Industry 4.0 connects them. The PLC, the ERP (enterprise resource planning, the system that holds orders, inventory and purchasing) and the MES (manufacturing execution system, the software that tracks work through the floor) are all third-revolution technology. acatech’s description: machines “took over not only a substantial proportion of the ‘manual labour’ but also some of the ‘brainwork.’”
What Industry 3.0 systems did not do was talk to each other. That is why a plant with a modern ERP and a PLC on every machine can still learn what the night shift made from a clipboard at 7 a.m. A fully automated line that reports nothing to the schedule is Industry 3.0. The same line, sharing its counts, stops and quality results with the ERP, the planner and the supplier, is Industry 4.0. The machines can be identical. The difference is whether the information travels, and whether anything changes when it arrives.
When did Industry 4.0 start, and who coined it?
The term was born in Germany in April 2011. acatech’s own account, in German (our translation), says the concept “was first presented to the general public at the 2011 Hannover Messe,” the industrial trade fair, by Henning Kagermann, then president of acatech, the computer scientist Wolfgang Wahlster, and Wolf-Dieter Lukas of the Federal Ministry of Education and Research. Chancellor Angela Merkel “adopted the new term ‘Industrie 4.0’ on April 3 in her opening speech at the 2011 Hannover Messe” (acatech, April 2021).
A working group co-chaired by Siegfried Dais of Robert Bosch and Kagermann then wrote the implementation recommendations, handed to the Chancellor in April 2013; that report gave the field its vocabulary. The English-language spread came from Klaus Schwab, then executive chairman of the World Economic Forum, who introduced “the Fourth Industrial Revolution” in a 2015 Foreign Affairs article and made it the theme of the 2016 Davos meeting (Wikipedia). Schwab’s version is broader, covering biotechnology and autonomous vehicles. The word came in 2011, the program in 2013 and the global label in 2016.
What are the nine pillars of Industry 4.0?
The nine pillars are the nine technologies a Boston Consulting Group report named on 9 April 2015 as the building blocks of Industry 4.0: big data and analytics, autonomous robots, simulation, horizontal and vertical system integration, the industrial internet of things, cybersecurity, the cloud, additive manufacturing and augmented reality (Rüßmann, Lorenz and others, BCG, 2015). None of the nine is Industry 4.0 by itself. The revolution is the data moving between them.
Technology (BCG’s name) | What it is in plain words | What it does in a mid-size plant |
|---|---|---|
Big data and analytics | Collecting data from machines, systems and people in one place and finding patterns | Shows the press slows every time one resin lot is loaded |
Autonomous robots | Robots that work next to people and adapt | A cobot loading a CNC machine on the night shift |
Simulation | A virtual model of a machine, line or plant fed with real data; the digital twin is this idea with a newer name | Trying a line rebalance before touching the floor |
Horizontal and vertical system integration | Systems talking up and down (machine to ERP) and across (supplier to customer) | The machine’s actual count reaches the ERP; the supplier’s ship notice reaches the schedule |
Industrial internet of things (IIoT) | Sensors and gateways that put machine and product data on the network | A 1998 press reports cycle counts and downtime reasons without an operator writing them down |
Cybersecurity | Protecting machines and data once they are connected | Separating the plant network from the office network |
The cloud | Software and data on servers outside the plant | One picture of three plants |
Additive manufacturing | 3D printing for parts, fixtures and tooling | Printing a jig on Monday instead of waiting three weeks for a machined one |
Augmented reality | Information overlaid on what a worker sees | Work instructions on the part in front of the operator |
Since 2015, artificial intelligence has grown out of “big data and analytics” into a category of its own, and edge computing now keeps a “reject this part” decision from waiting on a data center. The digital twin has the widest gap between belief and use: a 2024 McKinsey survey cited by the World Economic Forum in January 2026 found “while 86% of companies view digital twins as relevant, only 44% have implemented them and just 15% plan to do so.”
What are the four design principles of Industry 4.0?
The four design principles come from a widely cited 2016 paper by Hermann, Pentek and Otto (HICSS 2016, behind IEEE’s paywall). IBM’s guide, updated 16 September 2026, gives them as interoperability, information transparency, technical assistance and decentralized decision-making:
Interoperability (also called interconnection). In IBM’s words, “the ability of machines, devices, sensors, systems and people to connect and communicate with one another.” In a plant: the press, the ERP and the supervisor’s phone see the same work order.
Information transparency. Data from the floor builds a virtual picture of the physical process, so people can see what is happening. In a plant: plan versus actual on one screen, without a walk.
Technical assistance. “Industry 4.0 uses data and digital tools to help people make better decisions and perform tasks more safely and efficiently.” In a plant: a cobot on the dull job, a checklist that knows which part is on the fixture.
Decentralized decisions. Machines and software make routine decisions within set limits. Wikipedia’s summary of the smart factory: “Only in the case of exceptions, interference, or conflicting goals, are tasks delegated to a higher level.”
The fourth principle is the one to watch. In a working plant, the exceptions are the job. A late supplier, a failed inspection, a customer pulling a date forward: every one is an exception, and every one is where a decentralized decision turns back into a person with a phone.
How does Industry 4.0 work in a plant?
Industry 4.0 works through three kinds of integration, which the 2013 acatech report names as its “overarching aspects” (acatech, 2013):
Vertical integration is the machine talking to the business, across the levels from “the actuator and sensor” to “corporate planning.” Those levels are the ISA-95 stack; MES vs ERP walks through the two most plants confuse.
Horizontal integration is the plant talking to suppliers and customers: the ship notice and the forecast moving between companies without being retyped.
End-to-end engineering is the product carrying its own data from design to service, so the routing on the floor matches the drawing.
In practice a signal travels one path: the floor is sensed, the data lands in one place, analytics work out what it means, the plan changes, and an action goes back to the floor as a new sequence, an expedite or a call to a supplier. Plants have spent a decade building the first half of that path. The return leg is where people still carry the signal by hand.
What is the difference between Industry 4.0, smart manufacturing and a smart factory?
Industry 4.0 is the era, smart manufacturing is the practice, and a smart factory is the place.
Industry 4.0, the era. The fourth industrial revolution: the internet of things and cyber-physical systems reaching every industry. Named in Germany, Hannover Messe, 2011.
Smart manufacturing, the practice. Running manufacturing on data that moves across design, production, suppliers and customers. It is the US term; NIST treats Industrie 4.0 as Germany’s program for it.
Smart factory, the place. One plant that runs that way: its machines, systems and people connected, so it can see a change and respond without waiting for someone to notice.
A plant can live in the era, adopt parts of the practice and still have no smart factory. Digital transformation is the program a company runs to move along that path.
What is an example of Industry 4.0?
The best-documented examples are the World Economic Forum’s Global Lighthouse Network, recognized with McKinsey since 2018. It counted 132 sites in January 2023 and 223 sites across more than 30 countries by January 2026, with “1,150+ solutions from more than 40 industries.” Read every number below as what a well-run site reported, not as an average.
Electronics: Siemens, Amberg, Germany
What they did: The factory that makes PLCs is run by about 1,000 of them; machines and computers handle 75% of the value chain on their own, and it makes one control unit per second
Reported result: Production quality of 99.9988%; volumes up eightfold on the same 10,000 square meter floor with about the same headcount
Appliances: LG Electronics, Clarksville, Tennessee
What they did: Deep learning, automation and an intelligent injection molding system at a plant opened two years earlier
Reported result: Injection molding OEE (overall equipment effectiveness) up 21%; field failure rate down 61%
Source: WEF, 2023
Electrical components: Rold, Cerro Maggiore, Italy, about 250 people
What they did: Machine alarms sent to operators’ smartwatches, live OEE dashboards, sensor-based reporting; off-the-shelf technology and three programmers
Reported result: OEE up 11%; revenue growth of 7% to 8% from 2016 to 2017
Source: WEF, 2019
Data storage: Hitachi Vantara, Norman, Oklahoma
What they did: AI across supply chain, manufacturing and configure-to-order; named a Global Lighthouse Factory in July 2026
Reported result: Order-to-shipment lead time down 77%, inventory down 50%, forecast accuracy up about 19%, new-worker training time down 80%
Source: Hitachi, 15 July 2026
The results that matter are operational (OEE, lead time, quality, on-time delivery), and the smallest company on the list got there with off-the-shelf tools and three programmers. Laura Rocchitelli, Rold’s president, told the WEF: “The opportunity to monitor in real time our manufacturing processes turned out to be essential to reach better results both in terms of machine utilization and performance of each machine.”
What are the benefits of Industry 4.0?
The measured benefits are more output from the same plant, more productive people and faster response. Deloitte’s survey of 600 executives at large US manufacturers, fielded August to September 2024, found smart manufacturing initiatives delivered “a 10% to 20% improvement in production output, a 7% to 20% improvement in employee productivity,” and 10% to 15% more capacity, and 88% expected investment to continue or increase (Deloitte, May 2025).
The Lighthouse sites show the upper range. Across the sites audited for the 2019 report, factory output rose 10% to 200%, OEE 3% to 50%, lead time fell 10% to 90% and changeover time 30% to 70% (WEF, 2019). The 12 sites named in September 2025 reported on average “a 40% labour productivity increase and a reduced lead time of 48%,” and their AI use cases showed results such as “a 41% decrease in product defects, 28% decrease in energy consumption and 44% decrease in cycle time” (WEF, 16 September 2025).
The benefit that goes underreported is response time. The acatech index says Industrie 4.0 capabilities “help manufacturing companies to dramatically reduce the time between an event occurring and the implementation of an appropriate response” (acatech, 2017). Every figure above is downstream of that one.
How many manufacturers have adopted Industry 4.0?
Most say they need it, about six in ten say they use it, and few run the floor on it at scale. Rockwell Automation’s 2026 State of Smart Manufacturing Report, 1,560 respondents in 17 countries, finds that “90% of manufacturers now say digital transformation is essential to staying competitive,” 59% “report actively using smart manufacturing technologies,” and “only 18% remain in pilot mode.” Every respondent’s company had revenue of $100 million or more.
At floor level the picture is thinner. IoT Analytics estimates that 54% of plants globally still managed operations with pen, paper or spreadsheets in 2024, and that just 8% use a commercial MES. Where the floor system exists, Rockwell’s July 2026 follow-up found 93% have an MES but just 23% report full integration with ERP, PLM, quality and OT systems.
Money is following: in Deloitte’s 2026 Manufacturing Industry Outlook, 80% “plan to invest 20% or more of their improvement budgets in smart manufacturing initiatives.” The US Census Bureau put AI use at 37% of firms with 250 or more employees from December 2025 to May 2026 (Census, May 2026).
What are the challenges of Industry 4.0?
The main challenges are long pilots, data nobody uses, cybersecurity, old machines, and too few people to run it. The history, in order:
2018: pilots that never ended. A WEF and McKinsey survey found “more than 70% of industrial companies still in ‘pilot purgatory’.” Only 29% were deploying at scale, and only 15% reported pilots under a year (WEF, 2019).
2023: a leadership gap. Only 7% of production networks outside the Lighthouse group were rated advanced, against 20% inside it; non-Lighthouses named “a lack of leadership commitment and investment” as the main obstacle (WEF, 2023).
2026: data and risk. Of the data manufacturers collect, “only 43% is being used effectively,” and 46% “experienced at least one cyber incident in the past year” (Rockwell Automation, May 2026). In Deloitte’s 2025 survey, 65% ranked operational risk as their first or second concern, which in a plant means the fear of disrupting production.
Old machines. acatech notes “it is not unusual to see machines that are 50 or more years old still in use on the shop floor,” which is why clamp-on sensors exist.
People. The Manufacturing Institute and Deloitte project that “as many as 3.8 million additional employees could be needed in manufacturing between 2024 and 2033,” with 1.9 million possibly unfilled (The Manufacturing Institute, April 2024).
The people who install it are blunter. A commenter in a 2024 r/PLC thread: “Everyone talks this but provides little to no support to make it work. No money. No labor. No training.” Tony Hemmelgarn, CEO of Siemens Digital Industries Software, told IndustryWeek in June 2026: “It’s not the tech, it’s the people in the process.”
WHERE PROGRAMS STALL
The pilots ended and the data arrived. Most of it goes unused.
56%
of respondents ran Industry 4.0 pilots of one to two years, and 28% ran them for more than two
WEF and McKinsey, January 2018 report
7%
of production networks outside the Lighthouse group rated advanced, against 20% inside it
World Economic Forum, January 2023
65%
of executives rank operational risk as a first or second concern about smart manufacturing
Deloitte, May 2025
43%
of the data manufacturers collect is used effectively
Rockwell Automation, May 2026
READ TOGETHER
Fewer than half the plants use what they collect, and the risk they name first is disrupting production. The gap is who acts on it.
Sources as labeled. The 2018 figure is reported in the World Economic Forum's January 2019 Lighthouse report.
Why do Industry 4.0 programs stall at dashboards?
They stall in the two delays after the data arrives: deciding and acting. acatech’s maturity index opens with a diagram of what happens after an event in a plant. Four delays follow in sequence: insight latency, until someone knows; analysis latency, until someone understands; decision latency, until a countermeasure is approved; and action latency, until it takes effect (acatech, 2017, Figure 1).
The nine technologies attack the first two delays. Sensors cut insight latency to seconds; analytics cut analysis latency to minutes. Then the signal lands on a dashboard or in a group chat, and the decision and the action run at the speed of whoever reads it next. The purchase order waits for the morning meeting. The schedule change waits for the planner to get back from the floor. That is the dashboard stall: a plant at stage 3 or 4 that bought stage 6 and got a screen. The World Economic Forum’s January 2026 report gives the same diagnosis in its own words: “The challenge is not a lack of technological potential, but the absence of stable operating conditions required to translate that potential into durable, enterprise-level value.”
ACATECH'S FOUR LATENCIES
Two of the four delays are closed by technology. Two still run on people.
A machine stops. A supplier slips. An order is pulled in. Between the event and the countermeasure sit four delays: insight, analysis, decision and action.
CLOSED BY TECHNOLOGY
Insight and analysis
Sensors and IIoT cut insight latency to seconds. Analytics and AI cut analysis latency to minutes. This is what nine technologies and a decade of investment bought, and it works.
SECONDS TO MINUTES
STILL RUNS ON PEOPLE
Decision and action
The alert lands on a dashboard or in a group chat. The purchase order waits for the morning meeting. The schedule change waits for the planner. The done message arrives, and nobody checks whether the parts did.
HOURS TO DAYS
acatech, Industrie 4.0 Maturity Index, 2017, Figure 1. The split between technology and people is Morsa's reading.
What are the stages of Industry 4.0 maturity?
The clearest published answer is the acatech Industrie 4.0 Maturity Index, led by Günther Schuh and colleagues at RWTH Aachen, published in 2017 and updated in 2020 (acatech, 2017; 2020 update). It defines six stages across four areas: resources, information systems, culture and organizational structure. It also says “digitalisation does not itself form part of Industrie 4.0,” so the first two stages are the entry fee.
Computerization (prerequisite). IT used in isolation. The CNC has a controller and the quality station has a PC; neither talks to the ERP.
Connectivity (prerequisite). “The isolated deployment of information technology is replaced by connected components.” The ERP and MES exchange orders.
Visibility: “What is happening?” A digital shadow of the plant, “so that management decisions can be based on real data.”
Transparency: “Why is it happening?” Root causes found in the data: which supplier lot, shift or machine drives the misses.
Predictive capacity: “What will happen?” The plant simulates scenarios and sees next Tuesday’s shortage, but measures “still have to be carried out manually.”
Adaptability: “How can an autonomous response be achieved?” The plant uses its data to decide and “implement the corresponding measures automatically.”
No published survey places plants on these stages. The step to stage 6 depends on whether anything happens, with an owner and a deadline, when reality departs from the plan.
Is AI part of Industry 4.0?
Yes. In BCG’s 2015 list AI lives inside “big data and analytics”; today it does most of the analyzing in the other eight. Rockwell’s 2026 survey finds “one-third of operations (34%) are AI-augmented today,” with manufacturers expecting more than half to be AI-supported by 2030. Among the Lighthouses, the Forum’s January 2026 report finds “analytical AI and machine learning account for roughly 62% of Lighthouse solutions in 2025,” generative AI reached “23% of top-five solutions in 2025, up from 9% in the prior year,” and “AI agents are also beginning to emerge, enabling 5% of solutions in 2025.”
The distinction that matters is between AI that predicts and AI that acts. Predictive maintenance, vision inspection and schedule optimization are stage 4 and 5 capabilities: they shorten the insight and analysis delays. The newer use is AI that reads the signals, works out what they affect, and drives the response across systems and people, which is stage 6. The AI in manufacturing guide covers the use cases with sourced results.
What is Industry 5.0?
Industry 5.0 is a European Commission policy idea, not a new set of technologies. Its January 2021 report says Industry 5.0 “complements the existing Industry 4.0 paradigm by highlighting research and innovation as drivers for a transition to a sustainable, human-centric and resilient European industry” (European Commission, 2021). The Commission’s Industry 5.0 page names three elements: human-centricity, which puts workers’ wellbeing and skills at the center of production; sustainability; and resilience against global disruptions.
Read it as a correction of emphasis. Industry 4.0 was written as a productivity program. Industry 5.0 says the same connected plant should also be judged on what it does for its people and how it holds up when a supplier, a port or a pandemic fails. For a US plant the workforce is the live constraint: the Forum’s January 2026 report projects a 23% labor deficit in US manufacturing by 2030. Technology that lets the people you have cover more ground is the version of Industry 5.0 a plant can act on.
How does a mid-size plant get started with Industry 4.0?
Start from the last ten times the plan broke, not from a technology list. Of 239,265 US manufacturing firms, “all but 4,177” have fewer than 500 employees (NAM, citing 2022 Census data), and in NAM’s third-quarter 2026 survey, 80.8% named increased raw material costs among their biggest challenges. NIST’s Manufacturing Extension Partnership, with “nearly 1,400 trusted manufacturing advisors and experts at more than 450 MEP service locations,” puts it plainly: “technology adoption isn’t all or nothing” (NIST MEP; MEP Industry 4.0 services). Aaron Fox, president of the Oregon MEP center, on the NIST blog: “Your facility is probably using more Industry 4.0 technologies than you think.”
List the last ten breaks. A late supplier, a press down, a short shift, a pulled-in order. For each, write when somebody first knew and when the plant responded. That gap, in hours, is your baseline.
Place the plant on the six stages, honestly. If the ERP and the floor do not share data, you are at stage 1 or 2, and no analytics purchase will move you.
Fix the record, then connect what you own. Clean the BOMs and routings for one line, then connect the ERP, MES, CMMS and planning spreadsheet (which system owns which record).
Pick one technology for one problem. Sensors on the machine that keeps stopping, not “the digital factory.”
Treat the floor’s conversations as data. Photos, messages and handovers are the richest signal in the plant.
Write the response rules first. For each signal: who acts, by when, and what counts as done.
Measure event-to-response time, plus schedule adherence and on-time delivery, then copy what works to the next line.
Plan on the first workflow taking most of a year: in the 2018 survey, 56% of respondents ran pilots of one to two years. The quarter-by-quarter version is in the digital transformation roadmap, and the systems a plant can connect are mapped in the twelve types of manufacturing software.
Where does Morsa fit in Industry 4.0?
Morsa is the AI that operates the factory for you: it runs the daily operations work that makes a plant more money, in procurement, supply chain, logistics, scheduling, quality and coordination, on top of the systems the plant already runs. In Industry 4.0 terms, Morsa handles the two delays the technology leaves open, decision and action, so the data a plant already collects turns into work that gets done.
What Morsa runs. For a plant at stage 3 or 4, Morsa reads the ERP, MES, CMMS and spreadsheets, and the channels where people talk, such as WhatsApp, Teams, email or whatever the plant runs on. It works out which order, machine, supplier and owner a change touches, acts within rules the plant approves, and closes work only on proof. Depending on where the plant loses money, it starts with supplier follow-up, schedule recovery, expediting or shift handovers. Morsa works alongside the ERP and MES and replaces neither; it is not a dashboard and not a chatbot. See what autonomous manufacturing looks like day to day.
Who runs it. At J4S, a 120-person glass plant, on-time completion of operational commitments went from about 30% to about 75% in the first four weeks. J4S runs Morsa and went live in two days (Connect, Configure, Live) with no new software, no migration and no training. Anil Kohli, Production Head at J4S: “Our people don’t have to learn any new software. People just message the way they always have. Morsa coordinates all the messages in the background.” Read the J4S story.
How it is deployed and priced. Cloud, private cloud or fully on-premise, including the AI models and databases. A pilot on one live problem comes first. It is free when no implementation work is needed; otherwise there is a minimal implementation cost, refunded if the pilot shows no value. Morsa’s fee is a share of the value created, agreed after the pilot. There is no public price list.
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Sources
acatech and Forschungsunion, “Recommendations for implementing the strategic initiative INDUSTRIE 4.0,” final report of the Industrie 4.0 Working Group, April 2013. din.de
acatech, “Industrie 4.0 feiert 10-jähriges Jubiläum,” 12 April 2021. acatech.de
acatech, Schuh, Anderl, Gausemeier, ten Hompel, Wahlster (eds.), “Industrie 4.0 Maturity Index,” 2017, foreword by Henning Kagermann. acatech.de
acatech, “Industrie 4.0 Maturity Index, UPDATE 2020,” 22 April 2020. en.acatech.de
NIST, Lu, Morris, Frechette, “Current Standards Landscape for Smart Manufacturing Systems,” NIST IR 8107, February 2016. nist.gov
Boston Consulting Group, Rüßmann, Lorenz, Gerbert, Waldner, Engel, Harnisch and Justus, “Industry 4.0: The Future of Productivity and Growth in Manufacturing Industries,” 9 April 2015 (verified against the Internet Archive copy). bcg.com
Hermann, Pentek, Otto, “Design Principles for Industrie 4.0 Scenarios,” HICSS, January 2016. doi.org
IBM, Josh Schneider and Ian Smalley, “What is Industry 4.0?”, updated 16 September 2026 (design principles, main goal; read 24 September 2026). ibm.com
Wikipedia, “Fourth Industrial Revolution” (Schwab 2015 and Davos 2016; the smart-factory delegation sentence; read 24 September 2026). wikipedia.org
NIST MEP, Aaron Fox, “Why You Know More About Industry 4.0 Than You Think” (quoting PwC), 2 December 2019. nist.gov
NIST MEP, “Manufacturing Extension Partnership” and “Advanced Manufacturing Technology and Industry 4.0 Services,” updated 14 July 2025. nist.gov/mep, nist.gov
World Economic Forum with McKinsey, “Fourth Industrial Revolution: Beacons of Technology and Innovation in Manufacturing,” January 2019. weforum.org
World Economic Forum with McKinsey, “Global Lighthouse Network: Shaping the Next Chapter of the Fourth Industrial Revolution,” January 2023. weforum.org
World Economic Forum, “Global Lighthouse Network 2025,” press release, 16 September 2025. weforum.org
World Economic Forum with McKinsey, “Global Lighthouse Network: Rewiring Operations for Resilience and Impact at Scale,” January 2026. weforum.org
Siemens AG, “Fact sheet: Amberg Electronics Plant,” 23 February 2015. siemens.com
Hitachi, “A Hitachi Group site selected as Global Lighthouse Factory by the World Economic Forum,” 15 July 2026. hitachi.com
Deloitte, “2025 Smart Manufacturing and Operations Survey,” 600 executives, published 1 May 2025 (re-read 24 September 2026). deloitte.com
Deloitte Insights, “2026 Manufacturing Industry Outlook,” 13 November 2025. deloitte.com
Rockwell Automation, 2026 State of Smart Manufacturing Report press release, 19 May 2026, 1,560 respondents in 17 countries (re-read 24 September 2026). rockwellautomation.com
Rockwell Automation, “93% of Manufacturers Have MES, But Only 23% Have Fully Integrated It,” 14 July 2026 (re-read 24 September 2026). rockwellautomation.com
IoT Analytics, Anand Taparia, “MES vendors replace pen, paper, and spreadsheets,” 15 December 2025 (re-read 24 September 2026). iot-analytics.com
US Census Bureau, “Large Firms With at Least 20 Employees Biggest AI Users,” 26 May 2026. census.gov
European Commission, “Industry 5.0: Towards a sustainable, human-centric and resilient European industry,” January 2021, and the Commission’s Industry 5.0 page. op.europa.eu, research-and-innovation.ec.europa.eu
The Manufacturing Institute and Deloitte, “Manufacturers Need as Many as 3.8 Million New Employees by 2033,” April 2024. themanufacturinginstitute.org
National Association of Manufacturers, “Facts About Manufacturing,” 2022 Census data. nam.org
National Association of Manufacturers, “2026 Third Quarter Manufacturers’ Outlook Survey,” 14 September 2026, 220 responses. nam.org
IndustryWeek, Dennis Scimeca, “Custom Software Doesn’t Differentiate Manufacturers,” 10 June 2026 (Tony Hemmelgarn). industryweek.com
r/PLC, “Tell me more about industry 4.0,” April 2024 (anonymous commenter). reddit.com
Morsa, J4S customer story. morsa.ai/customers/j4s
Changelog
24 September 2026: retargeted the guide at the question “what is Industry 4.0.” New title, answer-first opening, and question headings for the nine pillars, the four design principles, Industry 3.0 versus 4.0, examples, benefits and challenges. Merged three sections on stalled programs into two, shortened the maturity stages and the starting plan, cut the practitioner-quotes section and the Gutchess Lumber example, and rewrote the Morsa section. Re-read the Rockwell, Deloitte and IoT Analytics figures. Morsa is now described as the AI that operates the factory for you, and its section and FAQ say what Morsa runs rather than what it builds.
20 September 2026: updated the Lighthouse count to 223 sites, added the adoption section, and corrected the BCG byline and the Industry 5.0 attribution.
