This is smart manufacturing (part 2 of 3) article where I am explaining the barriers and automation impact.
IIoT is the growing thread of connectivity between objects equipped with the ability to gather, store, process, and send data either though communication protocols to the Internet, or directly to other things or to an Internet gateway.
The IIoT becomes a full ecosystem when software, cloud computing (or in-house servers), and analytics tools combine to turn raw data into meaningful information or predictions—and when it’s presented on easy-to-use interfaces (such as dashboards or mobile Apps) enabling users to monitor, and in some cases, automate response actions or remotely control equipment or systems.
Several barriers will need to be overcome before next generation IIoT systems are widely adopted across manufacturing industries. These include the establishment of industry standards around IIoT, cyber security protection, and workforce adaptation to new sets of skills.
Standards are required to allow smart connected products, machines and assets to interact in a transparent fashion. This goes beyond the simple communication protocols, and involves the creation of standard semantics and mechanisms that will allow smart devices to discover each other and interoperate.
The advent of IIoT is accelerating the need for cyber security in industrial control systems. The complexity of IIoT will mean that cyber security must be designed into the components that make up the automation system.
The adoption of industrial security standards with certification will be essential to the advancement of IIoT because it will ensure the security not just of individual assets but also of the larger systems and systems of systems.
Adherence to the certification means that the elements of a system hold the key security building blocks. The elements are combined in a secure way by security certified teams and are operated as a secure system by security trained operators.
The skill-sets required to design and operate an IIoT-based system are somewhat different from those needed to run a classic automation system. A significant amount of re-training will be required for existing operators and maintenance staff to manage such systems.
The main challenge for automation suppliers will be to design and supply diagnostics/debug tools that can rapidly identify the root cause of problems.
Information driven architectures
As smart manufacturing enterprises start implementing smart enterprise control and asset performance systems managed by augmented operators, automation vendors will respond by implementing IIoT at all levels of the automation hierarchy. This will allow easy integration with next generation IIoT systems.
The increasing power of embedded electronics, connected intelligence will migrate down to the lower levels of the automation hierarchy – to the control level and to the sensors and actuators. As a result, operations technology (OT) systems will merge with information technology (IT) systems and the automation hierarchy will evolve to be a much flatter and more information-driven architecture.
The architecture consists of two distinct layers.
- A time-sensitive layer
This layer is often referred to as “fog” or “edge” and is for real-time deterministic control.
The OT devices that comprise this time sensitive layer (sensors, actuators and controllers) will be cloud-ready and capable of interfacing transparently with the IT business systems of the second layer. Those same devices will also have a high degree of intelligence.
- A cloud enterprise layer
This layer is where enterprise systems (ERP, PLM, SCM, CRM, etc.) and next-generation functions including asset management and energy management interoperate with each other and with the time-sensitive cloud-ready systems.
Networked automation architectures
Networks will see an exponential increase in the number of smart connected devices. These devices will exploit a time-sensitive IIoT-Ethernet backbone to interoperate with each other and with devices residing in other enterprise systems.
The large number of networked devices present many new challenges not only in the area of network management and performance but also in the area of managing the overall configuration of the distributed control system and its application software.
In smart manufacturing, the monolithic, single-source, hierarchical approaches and architectures of the past will not work in the future.
Advances are still required in the area of standards to fully realize the potential of IIoT. Nevertheless, despite the slow adoption rate, the impact of IIoT on manufacturing will be far reaching. Suppliers and users must start adopting IIoT technologies in their products and operations if they wish to remain competitive in the marketplace.
In part 3, I will be explaining about IIoT perspectives.
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