Industrial Evolution

What is Industrial Evolution?

The current stage of industrial revolution is punctuated by the introduction and expansion of a few key technologies across many industry verticals.

Internet of Things (IoT), Artificial Intelligence (AI), and next generation computing technologies are all poised to transform industrial operations. While every market segment will ultimately benefit, a few leading industry verticals are anticipated to realize early and substantial benefits.

Industrial Evolution involves exploitation of emerging technologies such as IoT, data analytics, and AI to continually improve solutions for producing and servicing products.

Industrial IoT (IIoT) technologies will facilitate a connected manufacturing environment in which production becomes increasingly more efficient. In addition, IIoT will radically change Product Lifecycle Management (PLM), bringing producers much closer to consumers, and transforming many products into services via the cloud services “as a service” business model.

What is Industrial Evolution?

The current stage of industrial revolution is punctuated by the introduction and expansion of a few key technologies across many industry verticals.

Internet of Things (IoT), Artificial Intelligence (AI), and next generation computing technologies are all poised to transform industrial operations. While every market segment will ultimately benefit, a few leading industry verticals are anticipated to realize early and substantial benefits.

Industrial Evolution involves exploitation of emerging technologies such as IoT, data analytics, and AI to continually improve solutions for producing and servicing products.

Industrial IoT (IIoT) technologies will facilitate a connected manufacturing environment in which production becomes increasingly more efficient. In addition, IIoT will radically change Product Lifecycle Management (PLM), bringing producers much closer to consumers, and transforming many products into services via the cloud services “as a service” business model.

Current Trends and Market Outlook

Industrial Evolution Stages

Industry is constantly evolving, moving through developmental stages. One of the most high impact stages of evolution to date has been the industrial revolution that began in the 1700’s and involved transition from a predominantly agrarian and rural society to a more urban and industry focused culture in Britain and the United States. This would lead to ultimately to the introduction of specialized machines in factories for mass production of goods.

The world is now experiencing its fourth stage of industrial evolution, which involves a marriage of physical and cyber systems for even greater productivity as well as new business models that were heretofore incomprehensible. This 4th stage (also known as Industry 4.0) builds upon the evolution from the previous three stages, which can be roughly described as follows:

Phase 1: Mechanization driven by industrial steam-powered machines
Phase 2: Assembly Lines for mass production of goods powered by electricity
Phase 3: Automated production enabled via computers and software controlled processes
Phase 4: Internet-based control and convergence of physical and cyber systems

The fourth stage, also referred to as Industry 4.0, depends upon the maturation of a few important technologies including adaptive manufacturing, AI, big data analytics, IoT, and advances in robotics. Industry 4.0 solutions will benefit many industries including traditional manufacturing as well as any other industry verticals which rely upon efficient and effective business automation.

Industrial IoT Data

Industrial IoT DataData is generated in IoT networks/systems by various sensors, gateways and devices. The volume of data generated in IoT is directly proportional to the number of devices connected in the network as well as usage.

IoT data comes from many sources. Major IoT data source segments include Smart Systems (systems interacting with other systems via automation), Ambient Systems (data from the business and/or consumer environment), Personal Assistants (intelligent agents that act on behalf of users), and Quantified Self (self-improving products) to name a few.

Identifying value from large amounts of IIoT data is a major challenge

Data generated in IoT will be primarily machine generated and hence will be generated continuously, providing real-time data output. In other words, volume and velocity of the data generated in IoT will be massive compared to consumer IoT.

For example, an aircraft can generate more than 500GB data in a day which is 6 times more than data generated by Twitter.

Mind Commerce Point of View

Industrial Internet of Things

IIoT will bring improved efficiency and effectiveness to businesses such as operational visibility and process improvement that could result in cost savings to the consumers.

IIoT will transform entire industrial operational processes

As part of the 4th industrial revolution, IIoT will provide the glue and controls to connect physical-to-cyber systems, and as a result, will create inter-system communications.

This cyber to physical connection and communications is transforming industrial processes beyond mere software control to achieve semantic control based on inclusion of data-analytic-driven decision making supported by artificial intelligence.

In the industrial IoT report, Physical and Cyber Industrial Convergence: AI, Cloud Robotics, Industrial IoT, and Virtual Twinning 2017 – 2022, Mind Commerce assesses the transformation of various industries through integration and convergence of IoT with many emerging technologies.

Industrial IoT and Cloud Services Model

Cloud Support of Industrial IoTCloud computing will be extremely important, both as a central repository of data, as well as a distributed processing element (e.g. edge computing) for real-time data. Consequently, major investment areas for many industrial companies will be in embedded sensors and actuators and integrating software applications with data analytics in a cloud environment.

Mind Commerce believes that the notion of “products” will evolve as many companies seek to offer Products as a Service within the cloud framework of delivery and support. The “as-a-service” approach will take hold as products are offered as services.

In other words, IIoT will transform goods and services beyond the production and logistics (e.g. supply side) to tie together supply and demand. This will be enabled by various technologies that allow for constant monitoring and communication between product, user, vendors, and suppliers.

In the industrial IoT report, Cloud Computing in Industrial IoT 2017 – 2022, Mind Commerce evaluates the technologies, players, and solutions relied upon for cloud computing in IIoT including edge computing, data management, and more.

Industrial IoT and Broadband Wireless

Unlike its predecessor LTE /4G, fifth generation (5G) cellular technologies represent a purpose-built technology, designed and engineered to facilitate connected devices as well as automation systems.

One of the primary drivers for 5G is to support massive IoT, which is to say high band-width for an anticipated tremendous amount of communications between devices, machines, systems and organizations.

5G will be an accelerator of industrial applications. IIoT is all about industrial automation and 5G is designed to meet the communication requirements for any high bandwidth, low latency, and untethered application use cases.

5G is expected to ensure Gbs standard connectivity in one millisecond latency that will act as key enabler achieving IIoT standards such as real time response, haptic feedback, remote controlling etc.

In the industrial IoT report Industrial IoT and 5G: Emerging Technologies, Solutions, Market Outlook and Forecasts, Mind Commerce evaluates the market outlook and business opportunities for IIoT that will be facilitated by deployment and operation of 5G systems. In the IIoT report, Leading 5G Applications and Services: Industrial Automation, Robotics, Haptic Internet, and Virtual Reality, Mind Commerce assesses the prospects for specific applications and services that are anticipated to benefit the most from 5G operations, many of which involve industrial automation and process improvement.

Industrial IoT and Robotics

The field of robotics is greatly expanding as it converges with ICT and includes service robots, unmanned ground vehicles, unmanned underwater vehicles, military robots and remote control system through wireless communication.

There is a need for an open platform for robotics that would include a development environment. This environment must support robotics R&D functionality including various interfaces and execution semantics for robot software, editing and composing the components/tasks, and the ability to easily develop, test and implement various applications.

Industrial IoT and Robotics

For industrial robotics, Mind Commerce sees an accelerating trend towards “de-humanizing” the manufacturing environment. For example, Nike has announced it will develop a plant that is 100% automated. This type of effort will have a profound impact across production-oriented companies. USA based companies leveraging robotics to this degree can impact the balance of trade as China’s low cost labor pool advantage is diminished.

In juxtaposition to this trend, Mind Commerce also anticipates that there will be increasingly more human-robotic interaction leading towards more autonomous robotics acting on behalf of humans. For example, there will be robotics and automation programs for continuous user tracking and person following robots.

In the industrial IoT report, Next Generation Smart Factories: Industrial Robotics, IIoT, 3D Printing, and Advanced Data Management, Mind Commerce evaluates the impact of industrial robotics and other technologies upon the manufacturing as well as other product and service creation industries.

Industrial IoT and Teleoperation

The area of Teleoperation and IoT is also significant. By its commonly understood definition, Teleoperation indicates operation of a machine at a distance. It is similar in meaning to the phrase “remote control” but is usually encountered in research, academic and technical environments.

Teleoperation is remote control of machines

It is most commonly associated with robotics and mobile robots but can be applied to a whole range of circumstances in which a device or machine is operated by a person from a distance. With IoT, Teleoperation takes on an expanded meaning as processes become optimized and automation is much more efficient.

Telerobotics combines teleoperation and telepresence to provide remote control of robotics in a manner in which the control is virtually present, yet remote from the machine. Combining additional technologies such as 5G, edge computing, and virtual reality will allow the controller to virtually become the robot, moving as it does.

Telerobotics for Dangerous Tasks

These technologies have many industrial applications such as providing the benefits of both worlds for a human/robot combination such as human intelligence and articulation with robotic strength and durability. One example in which this would be particularly useful is disaster clean-up such as in the wake of the tsunami in at the nuclear power plant in Japan.

In the industrial IoT report, Internet of Things (IoT) Digital Twinning: Market Outlook for IoT enabled Physical to Virtual Mapping and Management 2017 – 2022, Mind Commerce evaluates Digital Twin technology, solutions, use cases, and how digital twinning relates to IIoT and teleoperation.

Deriving Value from Industrial Data

By its very nature, most of the data collected from industrial systems and processes will be unstructured and in very large quantities. Transforming this raw IIoT data into insights, predictions, and recommendations via big data analytics represents a value-add to the industry.

This transformed data also represents a form of “derived data” (new data that contains information about the raw data), an entirely new layer of data that is derived from the original raw data gathered from machines and/or humans. Raw, unprocessed IIoT data many be transformed into valuable information through analytics, analysis, and ultimately decision-making.

Whereas IoT data (not solutions, products, or services) is arguably not a value-add, IoT data analytics may definitely be viewed as a value-added asset. IoT data service providers will be challenged to identify how they can add value to raw IoT data. One way to add value is analytics and/or decision support services.

The greatest value is not in raw IoT data, but rather data analytics and decisions derived from the original IoT data

Monetizing IoT Data

Many experts assert that the economic impact of IoT data be substantial, perhaps more valuable than the networks, systems, and equipment from which the data is derived. Mind Commerce sees derived IoT data in the form of analytics and specific decision services as a major value area for industrial data monetization.

However, it is important to note that there are many aspects to ascribing value IoT data, just as there are many approaches to value for any product or service.

In the industrial IoT report, Industrial IoT, Data Analytics, and Artificial Intelligence in Connected Manufacturing 2017 – 2022, Mind Commerce evaluates technologies, companies, and solutions involved in next generation manufacturing.

Industrial IoT Data Mediation

While initial IoT networks and system are often designed and run as silo operations, the future of IoT will be inter-connected and inter-dependent systems. These interconnected systems will need to verify data transactions of various types.

They will also need to verify the identity of entities requesting data to ensure security. Identity for IoT refers to verifying the authenticity of an entity, which could be a device, sensor, asset, or someone/something providing and/or asking for data.

Mind Commerce therefore sees a need at the M2M/IoT level to support identification and verification for devices in support of IoT. Identification will go beyond the obvious IP address, MAC address, etc. and will include unique RF signatures of end-points and other uniquely identifying machine level criteria.

With Edge Computing continuously gaining importance in IoT, many transactions and processing will occur at the edge. There will be a need for flexible architecture to support identification and authorization at edge nodes so as to not “ping” central databases continuously and thus slow down the overall system. Therefore, distributed intelligence is necessary to decide in real-time what data is relevant for immediate action and what data should be stored or archived in the cloud.

Industrial IoT Data as a Service

IoT data will increasingly become the new currency as machine data in particular is more efficiently captured, analyzed, and acted upon (often in real-time).

Mind Commerce sees a Data as a Service (DaaS) model emerging for IoT in which data associated with industrial systems and operations will be exchanged with partners and customers. IoT Data as a Service (IoTDaaS) is a subset of DaaS in general, which is defined as any service offered wherein users can access vendor provided databases or host their own databases on vendor managed systems.

IoT Data as a ServiceIoTDaaS is unique in that it focuses solely upon data that is directly, or indirectly, related to IoT networks, systems, devices, software, etc. This is to say that IoTDaaS is supported by those technologies that enable IoT.

Mind Commerce anticipates that IoTDaaS for IoT will be an especially important growth area for data services companies, IoT companies, and Enterprise IoT Customers that require data to make decisions about their operations, changes in products and services, CRM, and many more areas.

Eventually, we see the advent of an IoT Data Exchange in which data is shared, pooled, and used by various parties based on their agreements (bilateral, group, company/organization, etc.) as well as strong vetting of authenticity (genuine identify of entity), authorization (allowance of entity to access), accounting (how much and what type of data), and policy (what data shall be used to do, shall it be share with others, etc.).

These are all considerations that fall within the scope of what Mind Commerce refers to as IoT Data Mediation (which is a subset of IoT Mediation as a whole) discussed above. IoT data service providers will be challenged to develop a new set of applications and tools for non-IT companies to capitalize on their data generated through IoT.

In the industrial IoT report, IoT Data as a Service (IoTDaaS) Market Outlook and Forecasts, Mind Commerce assesses the market opportunities for storing and analyzing industrial IoT data, managing data on behalf of data owners, and selling industrial data and information to customers.

Industrial Technology Convergence

There is a rapid merging of technologies occurring with IIoT at the center of this convergence. Key technology areas include broadband wireless (especially cellular with ongoing evolution of LTE and 5G), artificial intelligence, big data and analytics. Mind Commerce anticipates that this convergence will be highly transformative across virtually every industry vertical from enterprise automation to traditional manufacturing businesses.

Industrial Technology Convergence

One illustrative area is “personalized manufacturing” through various technologies including 3D printing, big data, and predictive analytics. Technologies in the areas of real-time filtering technology to quantify personal information and personal data management and analysis systems will emerge to support “personal” or “small manufacturing” (also known as massive customization).

Another area is telerobotics, which combines various technologies such as robotics and telepresence supported by broadband wireless, virtual twin technology, and virtual reality. This combination will be especially powerful in certain industry scenarios in which there is a need for human decision-making and choice of movement with the strength and durability of a robot.

Some Specific Mind Commerce industrial convergence reports include:

  • Industrial Convergence Revolution: Smart Cities, Industry 4.0, Big Data in Manufacturing, and Industrial IoT
  • Industrial Convergence: 5G, Industrial IoT, Smart Infrastructure, Big Data, IoT Data Management and Analytics
  • Connected Manufacturing Convergence: IIoT, Data Analytics, and Artificial Intelligence in Manufacturing 2017 – 2022
  • Distributed Manufacturing Revolution: Convergence of 3D Printing, Cloud Robotics, IoT, Teleoperation, and Virtual Twinning
  • Physical and Cyber Industrial Convergence: AI, Cloud Robotics, Industrial IoT, and Virtual Twinning 2017 – 2022