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Industry 4.0: Breathing life into the cyber-physical factory

Industry 4.0 is the wave of the future for the manufacturing of things.

Originally conceived as a vision of the German government in 2006 as part of its High-Tech Strategy 2020 Action Plan, Industry 4.0 is frequently lauded as the fourth Industrial Revolution. The impact could well surpass that of the first Industrial Revolution that began in Britain in the late 1700s and took us from an agrarian economy on to a path for mass-producing affordable goods using steam power, electricity and, eventually, computers and automation. In other words, we’ve progressed from the horse and buggy to the Model T, and now we’re on to self-driving cars!

What will power the smart factories of the Industry 4.0 era? The internet of things, cloud computing and cyber-physical systems (CPS) technologies. Cyber-physical systems are powered by enabling cloud technologies which allow intelligent objects and cloud-based programmatic modules to communicate and interact with each other. These new cyber-physical manufacturing facilities use robotics, sensors, big data, automation, artificial intelligence, virtual reality, augmented reality, additive manufacturing, cybersecurity systems and other cutting-edge technologies to deliver unprecedented flexibility, precision and efficiency to the manufacturing process.

Yet while the Industry 4.0 revolution is forming, it’s important for companies aiming to be at its forefront to carefully consider which platforms are best positioned to deliver the promise of this exciting future, and what capabilities those platforms should possess.

Developing products, business processes and apps within an Industry 4.0 framework requires thinking beyond what any single product or system can be expected to do. In fact, the most exciting aspect of the Industry 4.0 vision is open and evolving industrial systems that can rapidly take advantage of the latest technological innovations. Imagine what the future could hold for an IoT product that has a complementary ecosystem build around it.

Intelligence sharing for smart factories

Up until now, the manufacturing automation landscape consisted of technology and data silos, based on hardware vendors. Companies with a global footprint of factories often end up with a heterogeneous and incompatible mix of automation technologies. And while these individual systems may each collect and transmit, they are not designed to easily make this valuable data available to other manufacturing systems, either within the same factory or perhaps located in another state or country.

IoT cloud platforms provide a powerful solution for harmonizing incompatible connected devices. On the factory floor, IoT compatible gateways provide a mediation layer between the proprietary protocols used by many vendors’ automation systems and the open internet-based protocols that are the foundation of IoT. Data from disparate manufacturers can be normalized in the gateways before transmission to an ingestion queue in the IoT cloud, while edge logic can be pushed to the gateways for local control of connected devices.

Mining potential of the cloud for healthy complex systems

But the real potential lies in the cloud. When cloud-based cybernetic intelligence is linked to global manufacturing operations, machine learning algorithms can identify patterns and extract insight that can optimize operations. As a factory in one region creates more optimized workflows that improve efficiency, those benefits can be rapidly exposed and propagated throughout the global operation. As predictive algorithms identify signs of potential system or subsystem failure in one factory, other factories can act quickly to avoid catastrophic incidents that can ripple through the entire business.

It’s useful to think of modern manufacturing environments as complex and interconnected living organisms, similar to the human body. Ensuring optimal health depends on the ability to:

  1. Rapidly identify exposure to pathogens
  2. Efficiently analyze root causes and potential secondary effects
  3. Develop effective remediation strategies

The first step requires diagnostic tools to visualize data across such interconnected systems, or steps two and three are very difficult to accomplish. And, if it is too costly or time-consuming to employ these tools, the patient is likely to get worse instead of better. So, what tools are necessary to realize an Industry 4.0 vision that will take smart factories to the next level?

The missing link: Programmer-less visual design

One of the most significant impediments to realizing the Industry 4.0 vision is implementing the necessary tools and applications to holistically visualize operations, identify opportunities for improvement and implement changes. Even in an IoT environment, applications must be created to take advantage of all of the data available in the cloud.

The traditional approach calls for hiring an army of programmers to build a “solution.” Not only is this approach costly and time-consuming, but it’s highly inflexible. Living organisms are constantly adapting to their environment; businesses and manufacturing operations are no different. As the environment changes, they must react rapidly. Business optimization is not a once-and-done event, but a constant battle to bring all the forces within a business into equilibrium. If every change to a cyber-physical system costs a million dollars and takes a year to implement, the promise of Industry 4.0 will never be fully realized.

But what if programmers can be removed from the equation? Okay, an entirely programmer-free approach to automation is still some distance off. But an approach that minimizes the use of programmers and maximizes the use of business analysts and subject matter experts is starting to emerge. The key is visual modeling, analytics and orchestration.

Visual modeling tools allow the elements of the system (and the data associated with those elements) to be modeled by the people who understand them best. Models can be refined and expanded without programming effort as the complexity of the system grows. The inter-relationships and dependencies of the component parts of any system are as important as modeling the components themselves. Any visual modeling tool should provide the capability to easily define these relationships.

Once a system has been modeled and the data is ingested to the cloud, that data should be exposed for decision making. Depending on roles, different stakeholders will see different slices of the data to inform their understanding. An Industry 4.0 development platform will allow easy extraction and normalization of data from a wide variety of sources (both real-time and non-real-time), with useful dashboard views and alerts using drag-and-drop technology. Platforms will allow data to be fed to machine-learning pipelines and emergent patterns easily viewed.

Orchestrations that influence behavior of the entire system will be created. These visual orchestration tools will allow drag-and-drop workflow design, built from a palette of programmatic components. These workflows can be tested and deployed as micro-services using a DevOps methodology.

Finally, with cloud platforms of the future, visual design services will be consumed as a service, and applications can be deployed on the public or private cloud of choice.

With tools such as these, the work of defining and evolving the efficiency of the system will be controlled by the people who know it best.

From IoT clouds to Industry 4.0 clouds

The vision of industry 4.0 is a long way from the days of producing cloth by laboring over spinning wheels by the hearth. Modern IoT clouds are now beginning to deliver the tools needed to make the Industry 4.0 concept a reality. Platforms running on popular IoT clouds are already delivering on this vision of visually designed factory automation to catalyze the transformation of the manufacturing landscape. These new technologies promise to unleash a virtual tidal wave of change throughout the manufacturing industry. And that rising tide promises to lift all boats, as businesses become increasingly capable of rapidly adapting their manufacturing to meet the needs of an ever-changing competitive landscape.

All IoT Agenda network contributors are responsible for the content and accuracy of their posts. Opinions are of the writers and do not necessarily convey the thoughts of IoT Agenda.

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