What is the Fog, and why does it matter?

Its not Karl the fog, but the industrial Fog! In news recently is the joining forces of the Industrial Internet Consortium® (IIC) and the OpenFog Consortium® (OpenFog). While manufacturers are still grappling with new technologies related to the new digital world (i.e Industry 4.0 and Smart Manufacturing) here comes another concept out of left field. So I guess the question is what is it and why does it matter right now, how will this bring me to the order of magnitude productivity increase.

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?

A Picture of MBO Misuse

I was reading “Organizational Sabotage - The Malpractice of Management By Objective” on the Deming Files and I am once again I am dumbfounded by how it is continuously being practiced or misused. It is a topic that I have written about before on the L2L blog and here. Although I liked the article it seemed lacking some real world examples. Needless to say I have experienced these continuously over my career and sometimes when reading these types of articles I just feel like shouting the proverbial “Hello”!

Anyways since I prefer visual interpretation I thought about trying to come up with a simple graphic to convey Deming’s and Drucker’s real message about MBO. I also thought I would add some description in the form of pairs of antonyms to emphasize the visual. Here is what I came up with:

Short-term / Long-Term

Disarrayed / Aligned 

Untidy / Tidy 

Conflicting / Collaborative

Kind of simplistic and vague – I know, yet open to interpretation? The notion is that if you set a short term goal it drives a specific behavior that is not always what you want, and probably not if it is a business strategy. Drucker wrote that “Objectives are the fundamental strategy of a business. Objectives must be derived from what our business is, what it will be, and what it should be.” Clearly he meant long-term objectives? 

I was with my kids at the beach the other way and they were learning to use a stand up paddle board. The 18 year old instructor gave them a simple tip. Always look at the horizon when paddling it helps keep your balance, look down at your feet and you will fall.

Applying "Monkeynomics" To Manufacturing Solutions

Once again I am involved with a company that is being steered by the “ERP is all you need” approach. I thought that by now we have come to peace with the fact that different systems provide solution to different problems. That ERP has found its place and made peace with MES and other shop floor systems. Maybe it is just human nature and we cannot stop ourselves from making the same mistakes over again. I was just watching one of the TED talks about "Monkeynomics" (see embedded video below). It seems that we as humans have something called “Loss Aversion”, i.e. we will take risks in order to avoid loss rather than play it safe.  This is an interesting observation that in retrospect explains a few of the odd behaviors that I have seen from companies in the past.



Another phenomenon that I find intriguing is the flawed notion that general economic methods are universally applicable. In other words the perception from people with business (or more precisely financial) background that it applies in all domains and all situations, specifically when applied to Manufacturing Systems solution. This means that everything that is in the past is money already spent and that we have to consider future state with no regard to what we currently have. Never mind the sweat and tears that where shed in putting a solution in, the extra hours, the training, etc. The current solution may not be perfect (but who or what is?) but it works, people are trained, they are using it, the company knows how to maintain it, in fact it adds value!  Yet, from a business perspective, which I equate to “the accounting or CFOs perspective”, we should disregard all of this; it is all water under the bridge. Just imaging the disruptions that will occur when the solution is gutted and a new one put in place, time, money, sweat, and tears – I just do not get it? We are slaves to this economic theory, investment planning only looks to the future and all that we have done in the past is irrelevant – I guess I will go out and get my memory erased - problem solved.

What is a Manufacturing System - Part I

This is a post that is long overdue. A central discussion topic on this blog is Manufacturing Systems and I have not yet really explained what I mean by a Manufacturing System. I have talked about manufacturing system that are agile and Holonic, so it is about time that I posted a more practical or at least clear description of what I mean.

Most definitions of Manufacturing System are focused on describing a solution, or more precisely the functionality and architecture of a Manufacturing System solution. For example the MESA model presents number of functional categories from a business perspective, where as the ISA-95 (S-95) model provides a solution architecture based on functional decomposition. All these are of course relevant and useful yet it seems that the problem only interesting to academia – try to Google it. It is assumed that we in industry all know what it is – a dangerous proposition to have.

We all agree that the key to a successful deployment of a Manufacturing System is the understanding of the problem that it is designed to solve. This obviously not a novel approach – it is what everybody attempts to do with the system’s requirement or URS. Yet my experience shows that even in the requirement phase many resort to using the existing models, thus reverting to describe the problem with the solution itself. Quite confusing isn’t it?

So here is my take on what a Manufacturing System is, or in other words the Shop Floor Management Problem. I like to describe it as the problem of integrating 3 important flows in a manufacturing organization. The 2 vertical flows provide Product and Logistical information while the horizontal flow is the physical flow of material, equipment and people.

The Shop Floor Management problem is therefore: How to make use of the information provided by the Product and Logistical flow to efficiently and effectively manage the physical flow of Resources and Materials (also known as the production process). Simple isn’t it - that is what a Manufacturing System is designed to do. Try to imagine a seasoned and effective production supervisor or plant manager – the Shop Floor Management problem is very close to his real life job duties.

It is obviously not that simple and there is of course much more detail that is yet to be discussed. I plan to provide some of this in upcoming posts (hence this post is named Part I). Also this is not meant to take away from the importance and complexity of product development, process engineering, operations, and planning. It is a model that is focused on explaining the particulars of managing a shop floor (yes this is my disclaimer).

More detail to come in future posts…

"Lean technology" a Manufacturing Systems perspective

My colleagues and I are in the process of preparing an educational session that will be held at the ISPE annual event in November. So as usual I spend some time looking through my archives for relevant material that I already have – I call it 're-cycling' :-). This time I came across something that I never published or used and so I thought I would share it here. It is an attempt to explore the synergies of the Lean and Manufacturing Systems concepts. Read and tell me what you think…

Manufacturing Technology; A familiar phrase considered part of the everyday vocabulary. What about Lean Technology? Not a common phrase, but the idea of lean manufacturing supported through technology should be as much a part of the vocabulary as Manufacturing Technology. Lean thinking advocates simplification of manufacturing units so they can be more easily shifted to enable the flow of value. So in essence the “lean technology” concept supplements lean thinking by combining state-of-the-art manufacturing with advanced software systems in an integrated environment.

Using information systems in lean manufacturing is not a new concept, nor is it new to the lean movement. Many examples exist that prove that manufacturing (software) system can support a lean organization. Unfortunately most commonly information technology systems for manufacturing tend to become large monolithic systems of great complexity. They are designed to provide generic functionality to fit major industry verticals that can be configured specifically for each implementation. At the same time the uniqueness and the complexities of the specific manufacturing operations make the ability to only configure these solutions more a myth than reality. Most of the system vendors will of course argue against this - however the reality is that in order to meet the requirements of the manufacturing businesses they are forced to implement complex customizations. That is what I wrote on my post about Customize or Compromise.

Although lean thinking advocates the application of a set of specific common concepts, the actual implementation of these concepts in real life tends to be unique to each production line and plant. Information systems that are used to support these lean lines and plants have to be able to provide common functionality to support these concepts. Yet, they also have to be able to support the uniqueness of each implementation. Furthermore they need to be able to support the changes that are inherent in a lean system due to the continuous improvements as they are accomplished.

In summary here is my suggestion for the general functionality of a Manufacturing System that can support a Lean manufacturing environment. (BTW I know that these go against the grain by not using a problem-oriented approach – I will have to redefine this ASAP)

• Value stream: We all know that value is identified by the specific needs of the customer hence the Manufacturing System should be usable and implementable to support only these specific processes that add value. In other words the system once implemented should not require or be constrained to use extra processes or involves extra steps if they are not directly part of the value flow.
• Implement flow: The Manufacturing System should employ a value centric process model that is easily managed and accessible to all the relevant people. This will allow a transparent view of the value flow and thus allow engineers and operators to ensure production flow, be it a one-piece flow, supermarkets, or other relevant Lean solutions.
• Execute Pull: This is kind of the obvious requirement that involves the enablement of pull execution and dispatching of WIP. This may include features and functionality to enable or enforce flow and managing kanbans, supermarkets, balancing, etc.
• Enable Perfection: Enable perfection by providing the production and process visibility needed for the continuous improvement efforts. This is the part of the system that provides Intelligence (a topic that I have written a few relevant posts about). In addition the Manufacturing System should provide adequate configurability, extendibility and customizability that support continuous improvement.

What is Intelligence, and why do we need it?

I believe that it is time to get back on topic in this blog, which is Intelligence in manufacturing and manufacturing systems in general. With that in mind I was looking thru my archives and came across something I once wrote as a positioning statement for an intelligence product – I guess it is not hard to figure out what company that was for? So here goes…

In one of my previous posts I tried to bring up the point that we need to consider metrics in the context of what they are needed for and how they are going to be used. I believe that is the best way to understand how to provide the right intelligence in a given scenario. But what is Intelligence? Well that is a very serious subject, but let’s take in the context of manufacturing and process improvement.

Intelligence implies the ability to comprehend; to understand and profit from experience. As such Intelligence is information valued for its timeliness and relevance rather than its detail or accuracy in contrast with "data" which typically refers to precise or particular information, or "fact".

In the context of manufacturing, Intelligence is a fundamental ingredient influencing the system’s level of performance in reaching its objectives. A manufacturing business system (humans included) is a system that learns during its existence. In other words, it learns, for each situation, which response permits it to reach its objectives. It continually acts and by acting reaches its objectives more often than pure chance would indicate. We can observe the following about Intelligence in manufacturing:

• It is an enabler for performance – Performance Management
• We need to act on it – Actionable Intelligence
• We need to learn from it – Continuous Improvement

Intelligent manufacturing is not a smarter way of producing things; it is a human centric approach where humans interact with the process be it automatic or manual, gathering the right information to take intelligence decisions based on actionable information. It is much more than visibility. Just having the information is of course helpful, but it needs to be taken one step farther. It needs to be provided in a way that people can intuitively capitalize on it using their knowledge and understanding to make effective decisions.

Henri Poincare once noted in a related topic that “Science is facts; just as houses are made of stones, so is science made of facts; but a pile of stones is not a house and a collection of facts is not necessarily science.”

What is an effective decision then? It is a decision that has an outcome that drives increased performance and continuous improvement. Intelligence is therefore not solely about metrics, KPIs or the ability to drill down into the data. In order to increase performance we need to quantify what is important. Hence intelligence is about quantifying what is important, or quantifying the unquantifiable.

What are Holonic Manufacturing Systems?

I thought that I would start some posts in this blog about some previous research that I have been involved in- Holonic Manufacturing Systems. I feel that the theory and the fundamental problem that it addresses are still very relevant in todays world - and maybe even more so?

The Holonic Manufacturing System (HMS) is a new paradigm for next-generation manufacturing systems, which presents a concept that can be used to achieve agile manufacturing systems. It suggests a new paradigm in manufacturing, which changes our old outlook, yet brings many challenging technical problems to solve. The HMS theory focuses specifically on the field of manufacturing control and information technology in manufacturing. HMS is aimed at meeting the challenges of manufacturing environment for mass customization or low-volume and high-variety products. The idea behind HMS is to provide a dynamic and decentralized manufacturing process, in which humans are effectively integrated, so that changes can be made dynamically and continuously.

The central concept of HMS is the term “Holon”, which originates from the work of A. Koestler. A Holon is defined as simultaneously a whole and a part of the whole, thus it can be made up of other holons. This property ensures that holons are stable forms, which can survive disturbances. Furthermore, a Holon is autonomous and co-operative and sometimes intelligent. This property ensures that they are intermediate forms, which provide the proper functionality for the form they are part of. Alternatively, holons have a self-assertive tendency, which is a manifestation of their autonomous nature, and have an integrative tendency, which expresses dependence on the larger whole or their co-operative nature. The Holon's hybrid characteristics allows for entities that co-operate with other entities by offering services to them (servers) and at the same time can act autonomously as free a entity (free agent).

Finally the notion of a “holarchy” is introduced as a dynamic hierarchy of self-regulating holons. The strength of a holonic organization, or holarchy, is that it enables the construction of very complex systems that are nonetheless efficient in the use of resources, highly resilient to disturbances (both internal and external), and adaptable to changes in the environment in which they exist. The HMS paradigm seeks to translate this con­cept, that Koestler developed for social organizations and living organisms, into a set of appro­priate concepts for manufacturing industries. The concept combines the best features of hierarchical and heterarchical (the opposite of a hierarchical) organization, since it pre­serves the stability of a hierarchy while provid­ing the dynamic flexibility of heter­archy.

I know that this is very academic - I will follow up with some posts that exemplify this theory in the future. What do you think?