The Internet of Things consists of objects with embedded or attached technologies that enable them to sense data, collect them and send them for a specific purpose. This data as such is just the beginning, the real value starts when analyzing and acting upon them, in the scope of the IoT project goal.
All this applies to cyber-physical systems as well, which are essentially connected objects. There are more similar characteristics but you see how much there is in common already. Moreover, the new capabilities which are enabled by cyber-physical systems, such as structural health monitoring, track and trace and so forth are essentially what we call Internet of Things use cases.
In other words: what you can do with the Internet of Things. Some of them are used in a cross-industry way, beyond manufacturing. Below are two examples of CPS-enabled capabilities we tackled previously and how they really are IoT uses cases. Track and trace possibilities in practice lead to multiple IoT use cases in, among others, healthcare, logistics, warehousing, shipping, mining and even in consumer-oriented Internet of Things use cases.
There are ample applications of the latter with numerous solutions and technologies. You can track and trace your skateboard, your pets, anything really, using IoT.
Structural health monitoring is also omnipresent, mainly across industries such as engineering, building maintenance, facility management, etc. With the right sensors and systems you can monitor the structural health of all kinds of objects, from bridges and objects in buildings to the production assets and cyber-physical assets in manufacturing and Industry 4.
The new capabilities, of which we just mentioned two and which are possible thanks to CPS in the Industry 4. What is a core enabler of smart logistics and so forth? You can perfectly compare this with the Internet of Everything view of connected objects, people, processes and data as the building blocks of smart applications. It is another key similarity between the CPS view of industry 4. To conclude: in fact, you can call cyber-physical systems the albeit advanced things in the Industrial Internet of Things in manufacturing.
RAMI 4. Even if some EU countries use different terms such as intelligent factory, future industry, digital production or smart manufacturing, the European Commission EC is also intervening. The 3-dimensional RAMI 4. An overview of the ongoing acceptance and leverage of Industrie 4. What are some of the key aspects you need to know about RAMI 4. First, know that there are two documents which laid out the foundations of Industry 4. The hierarchy dimension consists of 7 aggregation levels , being 1 the connected world, 2 the enterprise, 3 work centers, 4 stations or machines , 5 control devices, 6 field devices sensor and actuators and 7 products.
In the pyramid that shows Industry 3. The hierarchy dimension is what we covered several times in our articles on ubiquitous connectivity and digital transformation but in a different scope of hierarchy with smart products and smart factories as part of this connected world.
It also about technologies where we similar decentralizations all across the board IT and especially OT and about the ubiquitous interaction of participants across hierarchy levels, whereby the product is seen as part of the network. The life cycle and value stream dimension, as the term already describes, covers the various data mapping stages across relevant life cycles in RAMI 4. The idea: the more data early on, the more value later on.
The third dimension, the architecture layers, consists of 6 components: business, functional, information a , communication, integration and asset. Bring all three dimensions together and, on top of a nice visual, you have a 3D service-oriented architecture. After this introduction to RAMI 4.
These were established in the report in which the Industrie 4. Despite the fact that there is a difference between horizontal and vertical integration the goal is the same: ecosystem-wide data information between various systems and across all processes, using data transfer standards and creating the basis for an automated supply and value chain.
Horizontal integration refers to the integration of IT systems for and across the various production and business planning processes. In-between these various processes there are flows of materials, energy and information. Moreover, they concern both the internal as external partners, suppliers, customers but also other ecosystem members, from logistics to innovation flows and stakeholders.
In other words: horizontal integration is about digitization across the full value and supply chain, whereby data exchanges and connected information systems take center stage. As you can imagine this is not a small task. For starters, within organizations there are still quite some disconnected IT systems. This is a challenge for all organizations, industrial or not. If you start looking at seamless integration and data exchange with suppliers, customers and other external stakeholders, the picture becomes even more complex.
Also keep in mind the life cycle and value stream dimension of RAMI 4. Nevertheless, it is critical for Industry 4. The benefits and drivers for this need for horizontally connected information systems are pretty comparable to those we find in information management, as are the disadvantages if systems are not integrated. Ask any organization in any industry. These hierarchical level are respectively the field level interfacing with the production process via sensors and actuators , the control level regulation of both machines and systems , the process line level or actual production process level that needs to be monitored and controlled , the operations level production planning, quality management and so forth and the enterprise planning level order management and processing, the bigger overall production planning etc.
Typical solutions and technologies in this vertical integration include PLCs which control manufacturing processes and sit on the control level, SCADA which enables various production process level and supervisory tasks and is de facto commonly used in industrial control systems, MES or manufacturing execution systems for the management level and intelligent ERP for the enterprise level, which is the highest level in this hierarchical picture.
As mentioned previously, the MES manufacturing execution system plays a central role in the first stages of Industry 4. As mentioned previously the opportunities which are offered by Industry 4.
As the people behind Industrie 4. The true opportunities of Industry 4. Although that is easier said than done for many companies reaching these stages and goals is a virtually impossible task, certainly now, one of the reasons why they mainly focus on a staged approach or smaller steps as you can read in our article on industrial transformation , it is the true goal: new business models based on data, new ecosystems and new ways to service customers, meet demands in novel ways and create new revenue streams.
These more aspirational goals of industrial transformation mainly revolve around the service dimension of the so-called automation pyramid. Below is a nice example of such an automation pyramid, courtesy of the people at invilution. Indeed, it looks like the vertical integration image above. What we do have now is the growing importance of the Internet of Things.
And Industry 4. And, yes, it also looks a bit like the DIKW pyramid, a model that has existed forever to show the path from data to information to knowledge to wisdom and in some depictions to action , in the end it is all very much related. That automation pyramid is really just a depiction of the implementation of Industry 4.
The automation pyramid for the implementation of Industry 4. Do also think about the layers of network models such as OSI and others when looking at them as obviously there is a technological dimension and IT and IoT people will — of course — recognize a lot too.
Just as other aspects of Industry 4. The first layer of the automation pyramid concerns sensors and actuators. The first layer essentially consists of product and manufacturing assets and components which become information carriers as they can be addressed, localized and identified through sensors and are connected.
Built upon that connected layer of sensors, actuators and essentially data sits a layer of services and systems that enables the new ways in which the value chain is organized and managed. Here we meet applications such as energy monitoring and the monitoring and management of systems and conditions of assets such as machines, buildings, infrastructure and so forth.
In other words: mainly monitoring and managing, albeit it with the next step in mind: we do monitor for a reason — to enhance, understand and build new capabilities. Initially these maintenance, tracking and other applications are often focusing on internal operations but of course some can become additional revenue sources when deployed and offered in a customer ecosystem context, for example by offering maintenance contracts that could bring in new revenues or be offered as a service with the equipment you sell, while lowering costs for yourself service and support and your customers less downtime.
These could range from applications enabling consumers to tailor the goods they order and sell advanced services to come up with new revenue streams, certainly when developing services within ecosystems of data and possible partners. But again, it looks easier than it is in practice of course. Going from less paper and legacy systems to simply connecting assets and leveraging IoT, bridging IT and OT integration challenges in the first layer and being able to monitor and manage whatever needs to be monitored and managed, from energy to structures and beyond is already a huge step for many.
There has been an awful lot of academic work into those design principles so you might find other terms and potentially four instead of six design principles. In essence they are relatively simple — and should allow to explain what Industry 4.
These relatively well-known Industry 4. In order to move to intelligent manufacturing, smart factories, or connected industries, you need to bridge things such as real things, people, standards, work processes man and machine and more. And to bridge all that you need data and networks.
They must all inter-operate and inter-connect. You need to bridge IT and OT, you need to have assets such as machines that can connect and communicate thanks to sensors and other equipment and you need to connect people, data, machines and so on. This is indeed mainly about the Internet of Things and, in a broader perspective an Internet of Services, Internet of People, Services and Things, Internet of Everything, whatever name you prefer.
Interoperability is also about collaboration, the ability to have many really many standards talk to each other so data from various sources can be leveraged why we use Industrial IoT gateways, IoT platforms and talk about IT and OT integration, which goes beyond technology and is about human collaboration too, namely IT and OT teams.
Interoperability means connected devices, connected communication technologies, connected people, connected data, people connected and collaborating with machines, machines working with machines, an interoperable unified and holistic information, security and data layer and so forth.
Inter-operating and inter-connecting and in more than one sense connected with vertical and horizontal integration. Information transparency or virtualization might be a bit harder to explain to a friend as it is not about the transparency of information. Without interoperability, information transparency and virtualization are not possible as the information needs to be put in context and systems are context-aware, combining information from other sources too.
In the cyber-physical lingo of Industry 4. Finally do note that we speak about context-aware information. This essentially means two things: 1 information is not data, remember the DIKW model so analytics and moving from data to information and so forth is key here and 2 context-aware also means that the information can differ, depending on not just the actual context in which it is gathered and enriched but also in the context of its scope which can mean real-time information and so forth.
The easier way to explain it to a friend is probably to say that there is a virtual copy for pretty much everything. As mentioned earlier one of the core goals of Industry 4.
Only then the agility and flexibility needed to be able to deal with uncertainties, respond to demands of personalization, the concept of the smart factory and its place in an inter-connected ecosystem, the required data analytics and the various logistics can be enhanced, meeting the need for speed. We tackled this aspect of autonomy and semi- autonomous decisions and intelligence more in depth in our article on Logistics 4.
Decentralization is not just a given in Industry 4. In fact, the IoT de facto is a decentralized given as such. We are talking about a distributed reality. However, in the scope of Industry 4. Decentralized and autonomous decisions are not just key in the technologies and cyber-physical systems of Industry 4.
The end of the discussion on decentralization and autonomy is far from over, certainly from the human and decision-making perspective. In Industry 4. However, in practice this is not always achievable, let alone desirable. If you strive towards more autonomy on the machine and cyber-physical system level you do so for increased efficiency and to meet the demands of an increasingly real-time economy.
Advanced analytics, the IoT and the information and production systems in a smart manufacturing environment in its broader context of collaboration and ecosystems already are all about the development of real-time capabilities. Without interoperability, information transparency and virtualization are not possible. Flexibility, predictive maintenance, being able to quickly replace assets in case of failures and the IoT all are important in this perspective which also touches the previously mentioned design principles and the data to decision aspects tackled previously.
Moreover, a real-time capability is essential for the last two design principles, service orientation and modularity. The service orientation is related with the as-a-service economy, the Internet of Services and the obvious fact that manufacturing needs to be more tailored to the demand of customers for services and products with value added services e.
Yet, the service orientation is also related with the need for manufacturers and other industries to develop new services that are de facto based upon data, turned into intelligence, and seek new service-based revenue models.
Moreover, technical assistance and, more specifically maintenance, is a core principle as IoT and data analytics simply allow the transformation of services and maintenance. There are plenty of companies who changed their service models by simply adding levels of intelligence and connectivity with IoT to the equipment they sell.
And here we also meet Human-Machine Interaction. Finally, the service aspect is also related with the development of new as-a-service-models based upon data but also based upon the evolution towards a Machines as a Service model. Modularity means many things, depending on how you look at it: the various individual modules within the broad smart factory environment or simply as the end result when it becomes agility and flexibility.
You could say that modularity has everything to do with a shift from rigid systems, inflexible models and linear manufacturing and planning to an environment where changing demands from customers, partners in the overall supply chain, regulators, market conditions and all other possible elements causing the need for transformation and flexibility are put in the center.
The modules are locally controlled without hierarchy. Previously in this overview of Industry 4. Most of them are really umbrella terms for several technologies. We already tackled horizontal and vertical integration, cyber-physical systems and the Industrial Internet of Things as really vast realities with many technologies and components before on this page and elsewhere.
We also have literally dozens of articles on other evolutions in the mentioned convergence and application of nine digital industrial technologies as BCG calls them. Security that spans the physical and digital domain, the respective processes as well as communication between these areas is a prerequisite for the success of Industry 4. Security that is implemented only in an isolated way is easily bypassed and would be ineffective. Those that are less typical with typical ones being the integration of IT and OT, additive manufacturing, industrial robots and so forth are probably the ones you are looking at today: IoT, Big Data, the cloud, maybe 3D-printing etc.
So, what technologies are really key to Industry 4. It depends but the Internet of Things is clearly critical as it is what makes most so-called Industry 4. Security is also an inherent part of the Industrie 4. In fact, most of the mentioned technologies are essential as they are inevitably connected and interdependent. So, where do we start?
The best way to start is by looking at your goals and challenges and at the capabilities you need on your Industry 4. Big Data, analytics, the cloud and the fog , AI and simulation, to name a few, are about the adaptability, flexibility, modularity, scalability and rapid deployment and integration capabilities that we want to see with Industry 4. These capabilities come back in many of the Industry 4. Do note that several consulting firms and analysts zoom in on other digital technologies as enablers of Industry 4.
Mobile devices and technologies are just one example. More advanced interfaces in the relationship between human and machine 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. We looked at the strategic dimension of Industry 4. If you want to have a more value-oriented and purpose-driven view at the technological journey, you might want to check out the so-called digital compass which McKinsey made a few years ago, especially the value drivers in it.
For the many organizations who are still in the beginning of their Industry 4. So, these are really some main areas where, in the scope of that compass, you could create more value towards one or more stakeholders at the same time. The second part of the compass shows the Industry 4. As an example: in order to better utilize your assets, remote monitoring and control and predictive maintenance can help you achieve that goal. Although companies such as McKinsey and many others are absolute leaders in Industry 4.
In that sense we say the exact same thing regarding Industry 4. While that might sound like common business sense it is often forgotten. The reality of Industry 4. Yet, technologies and Industry 4. And that requires a different approach for each organization, even if there are many common lessons and strategies we can learn from. Yet, there is never a one size fits all.
With only ten years left to achieve the Sustainable Development Goals, world leaders at the SDG Summit in September called for a decade of action and delivery for sustainable development, and pledged to mobilize financing, enhance national implementation and strengthen institutions to achieve the Goals by the target date of , leaving no one behind.
The UN Secretary-General called on all sectors of society to mobilize for a decade of action on three levels: global action to secure greater leadership, more resources and smarter solutions for the Sustainable Development Goals; local action embedding the needed transitions in the policies, budgets, institutions and regulatory frameworks of governments, cities and local authorities; and people action , including by youth, civil society, the media, the private sector, unions, academia and other stakeholders, to generate an unstoppable movement pushing for the required transformations.
At the core of the decade is the need for action to tackle growing poverty , empower women and girls , and address the climate emergency. More people around the world are living better lives compared to just a decade ago. More people have access to better healthcare, decent work, and education than ever before. But inequalities and climate change are threatening to undo the gains. Investment in inclusive and sustainable economies can unleash significant opportunities for shared prosperity.
And the political, technological and financial solutions are within reach. Then why would you want to use them? A third-class lever is beneficial when speed and a larger load arm movement is desired. The hand shown in this photo is applying the effort force over a very small effort arm distance to move the chopsticks up and down a larger load arm distance to pick up food.
The food in this example is providing the load force. Keep in mind, a third-class lever is used when speed is desirable. This is why chopsticks make a perfect machine to use for eating.
A pulley is a member of the lever family and is a simple machine that has a rope which passes over a wheel that rotates around a central fulcrum. The diagram below illustrates why a pulley is considered part of the lever family. Do you notice any differences between these two pulleys? What is the load force? Where is the effort force located? Are the fulcrums located in the same location for each pulley? We simplify our analysis by ignoring the mass of the pulleys.
The pulleys in each of these photos have fulcrums located in two different locations. Pulley A is an example of a second-class lever and is free to move when an effort force is applied upwards on the rope. The weight of the apple provides the load force and the fulcrum is located at the end of the pulley closest to the fixed end of the rope. Pulley B is an example of a first-class lever. Both the effort force and load force are on opposite sides of the fulcrum.
Where are the effort arm and load arms for each pulley? This is not the same for pulley A. An effort force is applied to the wheel to rotate the axle or vice versa. A load is often attached to the axle using a rope or chain. For this learning task, you will find examples of levers in your own home and determine the location of the fulcrums, effort force, load force, effort arm, and load arm for each.
Torque is a measure of the rotational force of a rigid body about an axis of rotation fulcrum caused by a force, F, applied a distance, d, from the fulcrum. As you observed in the assignment above, the magnitude of the torque i. These relationships can be represented mathematically as:. The wrench diagram illustrates that the component of the distance, d, varies according to the angle at which the force is applied on the wrench rigid body. The photo above shows a common pipe wrench that is generally used to tighten and loosen pipe fittings that require much more torque than can be applied by hand.
Our effort force of , will remain constant. If the effort arm, is 24 inches and the effort arm, is half of that, determine the torque caused by the effort forces, and respectively. We are asked to determine the torque for and. Both effort forces will cause the wrench to rotate clockwise around the fulcrum. We need to convert the effort arm to S. Next, we will calculate the torque for each effort arm location.
The torque at is and the torque at is. As what is expected, the torque doubled as the effort arm distance doubled so long as the effort force remained constant; therefore, we can conclude that as effort arm increases, the amount of torque increases by the same factor so long as effort force remains the same.
Our calculations have demonstrated that more torque is created the farther the effort force is applied from the fulcrum; therefore, the wrench should be held near the end of the handle. Recall your Minds On reflection at the beginning of this activity.
What similarities and differences did you notice about the two pictures? What did you suggest would cause both of them to collapse? Archimedes of Syracuse c. Archimedes determined for a lever to remain at rest or at static equilibrium balanced , the torque caused by the effort force must be equal to the torque caused by the load force.
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