We have already touched on many developments in this review of Industry 4.0. You can see some of key developments in Industry 4.0 if you look at Boston Consulting Group’s presentation and results.
Recall that BCG refers to advanced robotics, additional development, growing fact, simulation, horizontal/vertical convergence, industrial Internet (of things), cloud, cybersecurity, and lastly broad data & analysis.
Many of them really are paragon words for different technologies. We have discussed horizontal and vertical convergence, cyber and industrial Internet of things. As genuinely big realities with a large range of technology and components. In the aforementioned integration and implementation of 9 digital industrial techniques. We have literally hundreds of papers about additional innovations as named by the BCG.
A pre-condition for success in Industry 4.0 is protection that covers physical and digital field as well as respective processes and communication between these areas. The protection that is only enforced alone is easily circumvented and will be counterproductive.
However, instead of sharing with you other pages, we will look at a few of the more common aspects in industrial markets and manufacturing, taking into account the particular aspects of certain developments in an industrial context. Those which are less common (the convergence of IT and OT, manufacturing additives, industrial robots, etc.) Might be the ones you look at today: IoT, big data, the cloud, maybe 3D printing, etc. These are the innovations that we encounter with change pillars and innovation accelerators on IDC’s so-called third platform.
Technologies as enablers of (new) capabilities and improvements
But what is Industry 4.0 really about the main technologies? It depends, however, on the Internet, as it is what makes possible the most so-called Industry 4.0 levers (see below).
The vision of Industrie 4.0 also includes protection. Most of the technologies listed are in reality necessary since they are interdependent and eventually related. So, where are we beginning?
You can better start by looking at your priorities, challenges, and skills on your 4.0 journey in the industry.
In terms of the adaptability, versatility, modularity, scalability, and rapid implementation and integration capability. Which we would like to see in Industry 4.0, big data, analytics, cloud (and fog), AI, and simulation, to name a few. These capabilities present in many of the tools in Industry 4.0 that we have already mentioned (such as Gartner’s page).
Be aware that many consultancies and analysis firms are zooming in as Industry 4.0 enablers in other emerging technologies. One example is mobile devices and technology. More sophisticated interfaces in human-machine interactions are another (or better: new interfaces in the relationship between human and technologies as machines makes us overlooks the critical software dimension in a world where software, as they say, is eating that world. Think artificial intelligence agents and bots or in another context phenomena such as Robotic Process Automation or RPA).
Industry 4.0 technologies in value drivers and in a scope of levers
Obviously, not all technologies can and should not be implemented at once. We have previously looked at and will continue to focus on the strategic dimension of Industry 4.0.
You may want to see the so-called digital compass created a few years ago by McKinsey. Particularly the value drivers therein, to get a more value-driven and targeted overview of the technological journey.
It might be a little daunting for many companies that are still at start of their 4.0 industry tour. But it isn’t when you look closer.
We all know and touch on 8 areas: time to market, balancing supply and demand, quality, inventory, function, usage of assets, resource/process, and after-markets. The main emphasis is the value drivers.
These are also some of areas in which one or more stakeholders can grant value in scope of that box. And, of course, it is not simply these 8 dimensions. But the question is how different interactions of those who have a direct link with tangible value can strengthen.
The second part of the box shows the 4.0 levers connected to the value drivers from the industry. For instance, remote monitoring, control, and predictive maintenance can help achieve this goal to make better use of your assets.
From a technology point of view, we are looking at technologies such as big data analysis, and Internet of Things, of course. You cannot collect data from the assets for monitoring/maintenance purposes unless they are linked to the target. In this case, it is about the technology that we know which technology is required.
While companies like McKinsey and many others are absolute leaders in Industry 4.0, after evaluating and drawing up a strategy and roadmap for your company, it is important to start with your individual objectives and means to achieve them.
Before looking at technology: dealing with complexity and strategic holistic need of prioritization
We say the same as we did in the digital transformation with Industry 4.0, in this sense: technology is feasible, and even more needs to be looked at.
It may sound like a common sense of business but is often overlooked. So pay attention to “the real technologies that you ought to have” and also pay attention to the many models, frames, and bridges that exist.
The reality of Industry 4.0 ad supply chains looks like a large complex mesh with a load of moving links, nodes, and dimensions. However, technology and industry 4.0 minimize our uncertainty in a priority and phased way and that of our systems, partners, consumers, and supply chains. In this phase of looking at our complexity, we build capacity to improve and develop capacities and versatility that are fundamentally designed to resolve and to remove complexities by taking advantage of the possibilities we detect in a dynamic reality by using new ways of approaching our various stakeholders.
Even with many similar lessons and techniques that we can learn from, we need a different approach for each organization.
However, there’s never a single size that suits everybody. For example, check out McKinsey’s digital compass again. Maybe you want customer service to improve; the dark green compass. That doesn’t mean that the solutions to make it work are predictive maintenance, remote maintenance, and virtually managed self-service. In customer care, for instance, the job part is also key. And that is the piece of inventory. And time and consistency, what about? Or the right to use your money.
They all lead to improved customer service. The best ways of working with your customers and your organization rely upon how all of these lever and other service problems. Which are not necessarily listed, connect with what your customers want and are today and maybe tomorrow, are not part of this Industry 4.0.
This is why, just like digital transformation, Industry 4.0 is a holistic figure and cannot be captured by definition in an example, whether it is a compass we developed McKinsey’s digital compass or any system. Take them for what they are, tools and boxes for thinking about uncertainty, offering ideas or approach to the challenges and opportunities of industrial change and technology which we can exploit in our own, increasingly digital, practical reality.
Ubiquitous Technology-enabled innovation and Industry 4.0
It is also clear that a lot is happening with information technology (IP and analysis technology as well as AI), IoT, technological research and innovation, and technology advancements at nearly all levels at production (and the supply chain) technology, in the context of operational technologies and conventional manufacturing technology.
Who would ever think that one day a tool holder would allow data collection from processes that are then sent to a dashboard to provide an insight into the sluggish tubular components of the operator? Who would ever think that an aviation data platform like Airbus would one day be developed and marketed?
The thing that goes in all directions of technical advances in Industry 4.0. If it’s named IT or OT doesn’t matter. For example, we switch from an ERP into an intelligent ERP. Which provides the backbone for large-scale processes to automate executable times by as much as 25 percent. In line with IDC manufacturing forecasts in 2018 and further. That’s a healthy backbone, and by 2021 there will be a 5th of the world’s largest (World 2000) producer. That would incorporate IoT, cognitive (artificial intelligence, and machine learning), also a blockchain, technology.
The list is long and evolving of next-generation presses and tooling equipment, production device innovations, modern CAD and CAM technologies, shaping products, digital networks and cloud industries, smart properties, virtual reality customer-oriented conception possibilities, multi-sourcing, and product virtualization. As normal, though, not all items will be important to all.
From where do Technologies Executives Expect most from in Industry 4.0
After the nine industry 4.0 innovations were compiled by Boston Consulting Group, others soon followed and continued to incorporate technology. We also saw independent cars as a technology for Industry 4.0.
It’s not all that important. As the annual Deloitte Industry 4.0 Annual Report for the year 2020 shows again, “The 4th Industrial Revolution: The Crossing of Control and Readiness” (PDF opens), the big four developments are anticipated still to have the most significant impact on interview management organizations (which really don’t serve small and medium-sized companies).
One may be shocked to see how low 3D printing, enhanced reality, and edge computing are not shocking yet. Many managers still struggle to wrap their heads around Industry 4.0. Evidently, there is a gap between what sellers claim and what customers want to sell and only a few companies have a very consistent and long-term Industry 4.0 plan.
The rest is self-speaking. Note, however, that the role of nanotech is much higher than, for example, the increased truth.
Beyond the automation pyramid: disrupting application levels
Although the conventional picture of the automation pyramid (as we want to keep referencing the DIKW model to clarify things) frequently referres to with its beautiful and simple look of the hierarchical level taking center stage in the vertical integration of Industry 4.0.
Although Industry 4.0 and Industrial IoT are far from being a reality for many businesses, plans for industrial transitions have a negative effect on hardware, industrial development software, technology, processes, and their integration, communication, and interoperability.
The blurring of borders on the level of solutions and hierarchies
As our traditional automation pyramid blurs in boundary with various technology, data, communication, and systems silos do not shift.
The shift in the landscape of solutions in continuing IT and OT integration is evolving as a result of movement through the cloud. The increased value of IoT, and the need to link systems to the correct emerging technology that we see in Industry 4.0, the 3rd platform and its innovation accelerators. It poses numerous challenges, including value creation, linked data, and security.
In the radically evolving architectures of the different industrial solutions. We know they play a key role in design concepts of Industrie 4.0, including interoperabilisation, virtualization, decentralization, real-time capabilities, a service-oriented approach, and modularity.
But somewhere you have to start. And many times you start at the edge, the organization, and the technology stack. Consider conventional automation pyramid, where sensors, actuators, and cyber-physical devices place and meet the level of PLC power. It is this journey that begins with the integration or better interconnection with more and more modular methods and in SCADA systems.
This is also a problem for many from the viewpoint of software suppliers alone. Production processes and systems for SCADA, to name only two, have been in existence and are not designed for these innovations for a long time. It also leads to an approach that consumers don’t really like. Radical changes in ERP applications, manufacturing processes, SCADA systems, and even ‘lower’ levels of architecture are unavoidable. In the future, they go far beyond what are today’s ‘platform’ and ‘service-oriented’ models.
This is a perfect analogy for the example of ERP moving into smart ERP with AI, IoT, and blockchain.
As said, there is still something many companies blockchain have never learned or known about the point of view of virtual currency alone.
Although Industry 4.0 and Industration IoT are far from a reality for many companies. Plans for industrial transformations are negatively impacting the integration, connectivity, and interoperability of hardware, industrial production software, technical development, processes.
Other applications in the wider field of development become one of many questions about the long-term futures of SCADA, MES, and so on with edge computing and AI once again. Wait for a landscape in which neither the plant nor the plant alone matters. There is a growing need for multiplant orchestration, intelligent supply chain management, and servicing approaches for the entire value chain. It is including features that include service and we eventually move towards intelligent components that interconnect at every level.
Consider Industry 4.0’s design principles: interoperability, virtualization, decentralization, real-time capability, a service-driven approach, and modularity. They all play a part in the radically evolving architectures of the different solutions.
Look at some of the improvements in the top 3 levels of our classical automation pyramid. As devices begin to speak the same industrial protocol and IIoT languages.
The changing standard of business resource management (Enterprise Resource Planning level ERP)
At ERP, the above-mentioned growth into ERP with an important function for artificial intelligence is taking place without even understanding it in all applications for this reason.
The leveraging of blockchain, master education, advanced research, and so on to effectively cover all aspects of all still to unlocked intelligent ERP transactional, contractual, administrative, predictive, autonomy, analysis, and many more. It would lead to unexplored levels of process automation and acceleration with an emphasis on performance. In reality, as Excel Runs output, this is something other than ERP.