The return of custom built manufacturing software

Is it really happening? Are the new digital technologies making it attractive and maybe even necessary to develop custom manufacturing systems solutions? For years we have advocated that companies focus on their core business competencies and leave the software development to expert best in class software companies. There are many horror stories of companies that are stuck supporting custom built software that is running their critical operations, why build and spend millions maintaining in house developed systems?

With the emergence of new digital technologies I see companies once again opting to develop custom software to solve their manufacturing systems needs. Is it because it is the 4th industrial "revolution", or is this truly something to consider, does it bring value and if so how? I believe there are a number of forces at play that are causing this to happen.

• Emerging digital technologies specifically cloud based SaaS solutions provide user friendly ways to solve some specific problems like analytics and integration with very quick ramp-up times. I.e. you don't need a lot software development skills.
• There is a real business need to get the promised productivity gains from these digital technologies. In other words organization have allocated money and people to get things moving in their digital transformation. 
• The new generation of workforce comes from the digital age (i.e. digital natives) and are used to in simple words, just download an app for that. They are confronted with what they see as antiquated software systems that are not really user friendly and their reaction is to find another app.
• The new digital technologies in general are human centered - they are developed to solve (and support) what we as people do, where as traditional business software is developed to automate a process.
• The current solution landscape of available digital technologies, in what we know of as the manufacturing system domain, is very fragmented and somewhat immature. Yes there are pieces of it specifically in the Cloud part that are further along but in general no.   

So, is this a case of history repeating itself? Will we see a resurgence of home grown solution that we will in a few years pay dearly to replace with available software form industry suppliers? I am not going to try and be a futurist but I think we can apply some logic to what the future can bring.  So in general, yes I think so - although it will be different (what an ambiguous answer). There will be some level of custom software being built but at the same time there are some forces at play that are different from what we have seen in the past, and these will make a big difference.

The rate of software development and how fast it is maturing is much greater that it was in the past, and the new technological landscape will consist of a network (or mashups) of different systems.
We will not have specific monolithic systems for each department or business function. The future digital factory will be supported by a network of Cloud and Fog (or Edge Computing) software components that will have been put together from the bottom up. The future manufacturing systems will develop and mature over time thru emergence rather than a top-down design and development process. Think about that - if this is true so much of our current approaches will not work (GAMP, ISA-95/88, etc.)!

So much for my prediction of the future, PS no AI used here 😉.

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?

Its still about people!

Is it technology or people that are driving digital transformation? Both I suppose, its people that can make this change and transformation, but they are also the ones blocking it sometimes. I was  reading the article "Why Most Digital Transformations Will Fail" and speculated why we may be surprised that the key to transformation is people. It is in nearly every single article about digital transformation and also a central component of Pharma 4.0.

The article states "...such digital transformations are far from trivial to undertake, in great part because it requires changing both infrastructure and culture within an organization". This is no revelation, its not the first or last transformation in history and this statement is universally applicable.  What is astounding is that, we see it as a challenge unique to the digital transformation. Let's not re-invent anything here and see how we have dealt with it in the past. There are so many examples and to sum them all up, if that is possible, I would say it takes leadership!

In order to drive transformation people need to believe the change is good, they need to understand that it will bring improvements and that they can have a hand in making the change. Therefore the first question to ask is why is it so important to digitally transform? Is it because we need to keep with the times - no its the promise of increased productivity, the promise of being able to do more with less, to do it smarter. I have for many years pondered this topic - hence the name of my blog "Intelligence in Manufacturing". When I was doing research the theme was Intelligent Manufacturing and we would joke that what we did until then was unintelligent manufacturing. Are we becoming more intelligent? Well I hope so in general and we are in fact continuously learning and with that improving. This time around we are doing it smarter, hence Smart Manufacturing.

Back to the topic of people, it obvious that without us non of this would work and yes it is us driving the change, us the people. The article I mentioned goes in length to describe the hesitation that people have to change. It is the same problem that we face any is a revolution (or change, or big change...) like the manufacturing digital transformation aka Industry 4.0. Hesitancy and resistance to change is always there, in every corner of an organization. Every time I present a new technology to manufacturing organizations, it rears its ugly head, Oh no its new technology hide! However I believe that this transformation introduces technologies that are focused on us the people, not automating processes but helping, augmenting, supporting us in how we work. Instead of year long implementations with weeks of training and months of ramp up it will be as simple as using an app - you know like the ones on your mobile phone. That is why its revolutionary.

The change monster :-)

Reflections on performance management

I have sometime to reflect lately about performance and a favorite of mine performance management. As always I fall back on Dr. Deming's 7 (or 14) deadly diseases of management, especially "eliminate management by numbers, numerical goals. Substitute workmanship"! And, the often misquoted "you have to manage what you can’t measure"

What is even worse is that traditional performance management not only focuses on the numbers but is also doing this by looking to the past. Surprisingly, most organization in this day and age still rely on periodic consolidation of business data to give them an idea of what is happening now by looking at the past, last month, last quarter and even what happened last year. This they believe is a measure of how they are performing and even more dangerously an indication of where the business is heading.

The world as we know is in transition to a real-time world where data is ubiquitous - the so called Digital Transformation. We hear everyday how AI, Big Data, IoT, AR/VR, etc is changing peoples life and how we work. These new technologies are also changing the way we do business and the way we run our manufacturing plants. Yet this change is held back by a mindset that is still deeply rooted in traditional main-frame and paper based process thinking. Even executives that feel they are progressive are still operating under these rules. I am just amazed at people who believe that they are cutting edge when they generate an excel report based on manually transformed data that is a month old - and these guys run huge business operations.

We take an employee survey once a year, spend 1 month consolidating the data and up with a PDF report. Then we analyze it and take decisions about our business based on this static report over the period of a year. What about using the wealth of online survey tools to get a real time view into the employee life, using social media tools to gauge employee satisfaction, etc. The surprising thing here is that using these modern tools is cheaper and less effort than managing “the employee survey” process, but will the shareholders accept this data? Hmm… probably not, so let’s go back to paper so we can show them that we are performing - Deming is turning in his grave!

People, Deming was warning about this in the 1960s! The perilous belief that we can run a business to satisfy the numbers and share holders is dead - the digital age will allow them to see performance in real time, and even predict it. The current availability of information and the speed that we can get it will expose the flawed traditional practice of performance management and hopefully make it obsolete. We will have the technology and data to prove that we are "managing what we can't measure".