Nobody said revolutions and transformation are easy, they require moving forward into the unknown - something us engineering have a really hard time with. Good news, there is no need to stress or move right now, but it is important to understand what it is. Especially when balancing existing needs served with exiting technologies while at the same time moving into the new paradigm. This is a common topic that I have been talking to many of you out in industry and hear the same frustrations: "We have to help the manufacturing operations today with technologies that we work while trying to figure out which digital technologies are ready for prime tome now and which will take some more time to mature". Not sure how many people read this blog, but I wanted to try and give you my perspective.
Although the main focus when talking about digital transformation is on people and use of emerging digital technologies such AI, Big Data, IoT, AR/VR, etc. It is important to understand that there is also a fundamental structural shift going on from a hierarchical systems approach to a distributed and collaborative human centered approach. The traditional approach to manufacturing systems design based on ISA-88 and ISA-95 hierarchical architectures which stem from a functional decomposition of the activities required for a manufacturing operation and process. These have served us well but in the future manufacturing operations landscape we will have a dynamic landscape of interconnected and collaborative edge or IIoT devices. They will not be top-down, command and control type architectures, which also put a question to the applicability of the current ISA standards to new digital manufacturing world!
In a Smart Factory the manufacturing system architecture will be more distributed yet not completely "flat". Digital technology takes a human centered approach that augments and support activities on the shop floor. The resulting architecture will be something that is called Heterarchy which in simple words mean a dynamic hierarchy. It is a networked structure that moves and changes with what is going on the production floor. Sounds real theoretical but in fact it is not, it is the same type of structure that we humans operate in every day. A system of independent components that work collaboratively toward a common goal or task. The figure below shows this in a simple graphic, notice the network of collaborative components in the "Internet of Things" model.
|(from: The "Internet of Things" for industrial applications, Technical University of Munchen)|
So why is it called "Fog", they analogy comes from low clouds that make fog, i.e. bringing the Cloud closer to the edge you get fog - get it? So in the future IIoT and edge devices will not operate completely independently. They will collaborate and form local interconnected networks while using the Cloud as a form of supervisory level and a place to get a perspective on overall manufacturing states, long term predictions, and tasks that require more computing power. These dynamic networks in the "Fog" provides storage and applications that are distributed efficiently between the edge data source and the Cloud. Manufacturing data and information will be stored not only in the cloud but on the IIoT and edge devices in this "Fog". This is very important because in the new digital factory productivity gains will happen by making more intelligent decisions, and these decision will happen at the edge, i.e. on the production floor and not in the Cloud. Data in the Fog can be more accessible, more granular more real-time. Technologies will also allow use of this data, distributed as it may be, without needing to move it or transform it. Probably in the same way that we can visualize data that's in the Cloud today.
Like I explained in the post about taking manufacturing back to the future the value is in the adaptability of the manufacturing operation that the Fog paradigm supports. Since the process behavior is dynamic and ever changing the only way to get consistent performance is by having adaptive control. Not only can adaptive control manage the ever-changing nature of the process’ internal and external factors, but it can also continuously learn, improve and thereby consistently increase performance and quality.
So this "Fog" concept seems scary and uncomfortable - and fog is in fact wet, cold and uncomfortable. Honestly, i am not that fond of the term either but I think its going to stick for a while. Maybe Holonic is a better term - dynamic and collaborative manufacturing systems and automation networks?