Industry 4.0 - the new industrial revolution

If you went to bed last night as an industrial company, you'll wake up today as a software and analytics company.

Jeffrey Immelt, former CEO of General Electric, "industry 4 .0"

industry 4

Industrial companies are feeling increasing pressure to adapt to a changing environment. They are experiencing the shift to new business models and the need to implement new technologies. After steam, electricity and computers, there is now a huge wave of new technologies shaping the industrial sector, generally described as cyber-physical systems. This includes cloud computing, IoT, and bringing the physical, digital, and biological worlds together.

New concepts and technologies are evolving thanks to Industry 4.0

In recent years, several new concepts have evolved and changed the industrial value creation: from the R&D phase to the manufacturing and assembly processes, up to the shipment of the product to the final customers. Some of the most interesting are:

Lights out factory:

When I first heard about this concept, I was surprised that the first lights out factory was in operation since the 1980s. The term is basically a synonym for autonomous factory; meaning that the factory runs 24/7 without any human being involved.


With the pace of progress in AI, many people are talking about the jobs that will be replaced by robots. Instead of machine versus human, Cobots leverage the collaboration of both. These robots are often highly adaptable and can support humans in repetitive tasks. 

In-memory computing:

It is important for IoT to collect and analyze data in memory on a single copy of data on platforms such as Google cloud platform.

Edge computing:

Invented by Cisco, Edge computing allows companies to process data as close to the data source as possible and not in the cloud. The benefits are less data transmission latency to the cloud and greater security.

Machine learning and AI:

This one is obvious. Countless data streams throughout the production process provide a solid foundation for predictive information that goes far beyond any traditional manufacturing execution system (MES).

Industry 4.0 enables the transition to a service-based business model

There are increasing signs that products in the industrial world are being sold as PAAS rather than SAAS. This sounds familiar if we look at the shift from on-premises software to SaaS. Why does this make sense and what are the benefits in the industrial world?

For vendors:

Like SaaS, companies can benefit from increased customer lifetime value and a lower barrier to entry. Plus, they can generate revenue even in a downturn, if no one wants to invest in new machines or assets.

For buyers:

They enjoy greater convenience and more services such as predictive maintenance or condition monitoring.

This shift is occurring globally, but regardless of this trend, it is becoming more difficult for Western industrial companies to differentiate themselves through quality; as manufacturing companies in China and elsewhere are catching up. This begs the question, how do you differentiate yourself and win over competitors who can generally produce at lower costs?

  • Customer reactivity allows for a faster time to market and a quicker adaptation to changing demand. Customer orientation and individualization to increase product variety.
  • End-to-end solutions throughout the process, from R&D to post-sales. Create interfaces, APIs, share data with suppliers and customers to work collaboratively on more efficient processes and reduce costs and time.
  • Leverage automation and robotics to achieve labor costs similar to those in low-income countries.

Application examples:

  • Engineering tools: 3D modeling, prototyping tools and simulation platforms for product design.
  • MaaS / 3D printing: rapid prototyping using 3D printing, tailored sourcing platforms, manufacturing as a service and vertically integrated factories.
  • IoT / Middleware: Get data from machines, connect offline devices with online services. Connected devices capable of collecting and sharing data that can be used for real-time monitoring or deeper analysis.
  • Shopfloor Guidance / Apps: Improve work instructions for complex processes; process safety and ensure production quality. It often focuses on smartphones, tablets and modular workstations.
  • Robotics: software to program robotic behavior, AGVs and other types of robots. Investments in robotics have recently taken off.
  • Wearables: Touch interfaces are ubiquitous in B2C and people are used to personal devices. This trend is recognizable in the industrial world.
  • Analytics / Efficiency: for a 360° overview and total control of the entire production process. Measure and analyze human workers and machine work on the shop floor, including monitoring machine condition and energy consumption.
  • Inspection: companies that help discover problems on the assembly line, e.g. with the help of computer vision.
  • Predictive maintenance: solutions for condition monitoring, performance optimization and downtime reduction.
  • Asset tracking / location analysis: Gain transparency across the supply chain with tracking and predictive/prescriptive analytics.

The big industrialists are not as outdated as one might think

Take Germany as an example, where 23% of GDP value added comes from manufacturing and 48% comes from the global market leaders - the so-called hidden champions. While it's true that they don't take as much risk and invest in new projects as heavily as the GAFAs do; they do invest in digital initiatives and adapt their business model. One could argue that if it's incremental improvements, the incumbents will do it - if it's disruptive or 10x better, the incumbents might go too slow. 

Here are some examples:

Kärcher - the cloud first:

They have been working with AWS since 2012. Their cleaning machines have a telematics box that sends machine data to the cloud, such as location for more efficient scheduling and management of maintenance services.

Viessmann - a healthy appetite for risk: the heating and refrigeration manufacturer has its own venture capital fund, a Berlin-based business builder and is trying to create a community around IoT with Maschinenraum. The whole company is experimenting with a lot of new business models and ideas and is one of the most forward-thinking German companies in the Mittelstand in my opinion.

Kaeser - changing its business model: the air compressor manufacturer installed sensors in its compressors a few years ago and changed its business model from selling compressors to selling air as a service. Now, customers only have to pay for the amount of air they need.

BMW - the automated factory: The BMW i3 factory in Leipzig is quite advanced and has a high degree of automation.

And they need to be active. It will probably be much easier for software companies to enter new industries (e.g. Google → Automotive) than for traditional industrial companies to hire top-notch developers.

Viessmann - a healthy appetite for risk:

The heating and refrigeration manufacturer has its own venture capital fund, a Berlin-based enterprise builder and is trying to create a community around IoT with Maschinenraum. The whole company is experimenting with a lot of new business models and ideas and is one of the most forward-thinking German companies in the Mittelstand in my opinion.

Kaeser - change its business model:

The air compressor manufacturer installed sensors in its compressors a few years ago and in doing so changed its business model from selling compressors to selling air as a service. Now, customers only have to pay for the amount of air they need.

BMW - the automated factory:

The BMW i3 factory in Leipzig is quite advanced and has a high degree of automation.

And they need to be active. It will probably be much easier for software companies to enter new industries (e.g. Google → Automotive) than for traditional industrial companies to hire top-notch developers.

Implications for founders of new Industry 4 .0-oriented companies

Clearly, all of this development opens up a huge window of opportunity for entrepreneurs who want to transform the industrial sector. Some things I would recommend to keep in mind:

Customer orientation:

Work closely with customers and pilots from the beginning. Develop the product based on their feedback, try to have short iteration cycles. It's only fair to spend time with them if they use the product and give you feedback. Compared to SaaS companies that sell to other software vendors; you can't do A/B testing. Help them try your solution, e.g. Start with one production line instead of the whole shop floor.

Avoid unpaid pilots:

JI feel like the bar for making a pilot is pretty low. Many companies are willing to test your solution, but often they don't want to pay for the pilot. I know it's a pain sometimes; but I'm sure to say no. There are several SaaS companies that could grow from theirs once they make the first enterprise agreement - that is, sign the first contract. Also, focus on one or two use cases for pilots instead of having a pipeline full of small pilots of different use cases.

Sell a single use case:

Sell a single, clear use case that people in the industry easily understand. Instead of selling a "dashboard," sell them a "control room." Tailor your language to the industry to your best understanding and sell the ROI first.

Try to sell high:

It's good to talk to workers in the R&D department or on the assembly line, but in many cases, try to sell the product as high as possible. Call C-level management, the head of production planning or the director of manufacturing. The worst thing that can happen is that they pass you on to someone in the hierarchy.

Understand the company's sales:

Try to understand the company's sales process. Who is the user and who is the decision maker? Who has the budget? What does the procurement process look like?

Second platform:

Instead of trying to build a platform first, try to start with a narrow use case and develop the product with the goal of having a long-term platform, especially for IoT. People don't buy IoT, they buy a solution to a problem.

Avoid aimless pitches:

Due to the increased interest in the industry, many companies are inviting startups to present and there are many events with pitch opportunities. Think again if your time is well spent there before you accept it. It's often a one-sided knowledge transfer rather than an interest in funding or collaboration.

Lean manufacturing and industry 4.0

Like previous industrial revolutions, new technological developments are driving Industry 4.0 forward. The most relevant of these new technologies for manufacturers are cyber-physical systems and the Industrial Internet of Things (IIoT).

Fear of automation and other manufacturing workforce challenges make it easy to ignore the potential positive cultural impact of these technologies.

For Lean manufacturers, this new technology is an opportunity to access the fundamental goals of lean manufacturing: empowering people to make improvements.

Definition of industry 4.0 oriented technologies

Cyber-physical systems facilitate the connection and collection of production data via a network - typically the cloud. In a cyber-physical system, there are three main ways to collect data: human to machine, machine to machine, and data acquisition and processing.


Human to machine

Human-machine data collection comes primarily from operators via a digital interface. The CPS can collect information via traditional data entry, methods such as typing on a computer or selecting options on a tablet. Operators can also share information through advanced technology. For example, computer vision can collect data from specific gestures or movements that have assigned meaning.

The consumer world has digitized much faster than the industrial world. Many of these information input methods are already familiar to operators. Common UI / UX design principles make it easier for users to adapt to new HMI technologies. For example, select red digital "buttons" for negative feedback and green digital "buttons" for positive feedback.


Machine to machine

Machine-to-machine communication historically meant one machine pushing data into another machine. These machines were typically connected via an Ethernet connection. The full potential of M2M communication was limited by proprietary and siloed technology.

IoT is transforming machine-to-machine communication in two significant ways. First, it often involves two-way communication, rather than just a push from one machine to another. Second, the addition of the cloud provides greater opportunities between machines. With the IoT, buyers want more connection options, which leads to a shift from point-to-point communication built into the hardware to open up communications between devices.

This provides potentially unlimited integration options. These changes translate into additional information and options for manufacturers.

Data acquisition and processing

Many manufacturers already prepare and collect data in other software systems. They use enterprise resource planning (ERP) software to manage purchasing, financial planning, employees and other aspects of their business. They use MES or manufacturing execution systems to track and trace materials, resources, etc.

These systems often contain production-critical data, but they are massive, compartmentalized and often difficult to access or maneuver.

Finally, this data can be combined to deliver a holistic and interconnected view of production.

Lean Manufacturing

The value of Lean manufacturing is that it helps manufacturers reduce operational complexity, eliminate waste and improve productivity by allowing shop floor workers to make necessary, ongoing adjustments.

The human element is a key principle of lean manufacturing. Human analysis and flexibility produce the majority of the effectiveness of Lean principles.

A traditional Lean toolkit can include a variety of methods and principles. Manufacturers should not necessarily apply every tool in every plant. However, the toolbox provides options for all plants. Together, they can be combined and applied to produce continuous improvement.

Towards Lean 4.0

Industry 4 .0 technologies are tools that can make manufacturers more flexible, efficient and cost-effective.

Simple adjustments, such as converting paper work instructions to digital work instructions, can generate savings with little or no cultural adjustment. Manufacturers are generating efficiency improvements of 10 to 15% by incorporating digital labor and robotics into their production lines. This is a stand-alone Industry 4 .0 project.

As a result, stand-alone digitization efforts can reduce operational costs by an average of 10-15%. However, these projects must be implemented and designed correctly to produce these improvements. In addition, they can be difficult to change if they are highly customized.

Industry 4.0 + Lean Manufacturing

If manufacturers adopt both a Lean methodology and Industry 4 .0 tools, they can accomplish more than if they tried these initiatives separately. CPS and IoT can make a shop floor truly Lean. Real-time data and communication between people; machines and systems provide a holistic view of production and allow frontline workers to make adjustments in real time.

therefore, companies that combine lean and Industry 4 .0 can achieve a 40% cost reduction. This means that the combination of lean and Industry 4 .0 provides a 100% increase in cost savings compared to implementing each separately.

Return of experience

Despite the best intentions, 84% of digital transformation projects fail. Causes vary, but include long proof-of-concept periods, high implementation costs, and general ambiguity in pre-project performance data and improvement goals.

With these numbers in mind, manufacturers should be wary of full digitization projects. They can reduce the risk of the process by starting with a specific application of the technology that has a clear business objective and a short time to value.

Difficulties in implementing "Lean 4.0

Taking an analog process and converting it to digital can be counterproductive.

Layering new technology can make a production line more expensive to operate. Adding custom software may require re-qualification. It may also require hiring new team members with more technical expertise.

This is a major concern for manufacturers, as many manufacturers are struggling to hire qualified employees on a contract basis. Manufacturers must compete with other technology companies for the same pool of scarce talent. If they don't hire internally, they will have to rely on outsourced expertise to maintain these systems. Both have high associated costs.

How to stay Lean with new technology

Manufacturers who want to adopt Lean 4.0 should start small. Recognize that engineers, plant managers and executives don't know what they don't know, but that's not a problem!

Designing to learn

The first step is to design a digital process that will collect data. The design process in Lean 4.0 is underway. Benchmarking the data to gain insight into the current state may reveal flaws in the existing process.

This is why flexible development is important for manufacturers. In addition to having a clear, data-driven approach, manufacturers should start where there is a clear use case and benefit. This approach provides a quantifiable measure of whether or not the implementation is successful.

Test and collect data

Put the initial test into production. As with any test, try to control the variables as much as possible. Be sure to collect data that gives information about what needs to be adjusted for the test to succeed. 

For example, identify cultural and conditional challenges. If operators are having trouble adapting to the new technology, find out why and whether this is a long-term or short-term challenge. 

To discover this challenge, you will need to track productivity in a process by the operator.

Iterate and scale

With Lean 4.0, the testing doesn't stop. Technology enables continuous improvement, but iteration is what makes the process truly continuous. Apply test learnings to other lines and apply conceptual learnings to other areas for extended testing at the pilot plant.

Benefits of Lean 4.0

A gradual, data-driven, use-case-centric implementation that presents value along the way will facilitate buy-in from operators and other internal stakeholders. This buy-in decreases the risk of implementation failure.

With Industry 4.0, the greatest benefits are realized by unleashing the analytical power of manufacturers' greatest asset: their employees.

Improved results and engagement in the workshop

Remember, lean manufacturing is a human-centered cultural framework. Integrating Industry 4.0 tools can enable your employees to generate efficiency and creativity previously unrealized on the shop floor by giving them real-time data and visibility into the machines, processes and people involved in production.

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