New era of valve design and engineering

I am not entirely sure of who is the target audience for this blog post. When I started thinking about the topic and was writing this post, I thought of the CTOs, the head of the research teams - “the one who decide the technology road-map of an organization" as my readers. Now that I have finished writing the post, along with CTOs, I feel like maybe the designers who wish to know what is coming next, what kind of technology they should keep working on and what new skillset they would need to acquire, should read this. Maybe the business owners who want to develop leadership in the market and remain competitive should also read this. For me, this sounds like a correct audience for the blog. Although the title says a new era, I really wish you to read this as a "future" in valve design and engineering. This will probably set a correct context while reading the blog. Look at this as more "directional, future and things to work on" than "what is happening today" [although there is strong evidence that it is happening today]. So, let's start.

The 4th industrial revolution is upon us. Few have already created the roadmap and following it rigorously, few have started analyzing the business impact and getting ready for it, and few are still thinking that its far future and may not impact their business. Irrespective of what is the approach of individual business leaders, the whole industry is going at a rapid pace to adapt to this "so-far the biggest industrial revolution in the history of mankind".

This revolution is paving its way for an exciting future in design, engineering, and manufacturing. What we are witnessing today is the convergence of multiple technologies including Artificial Intelligence, Generative Design, Virtual and Augmented Reality, Additive Manufacturing, IoT and Digital Twin. We are witnessing the new era of complete product life cycle starting from customer requirements to product engineering, production, and operations. Many organizations from automotive, aerospace, biomedical and industrial equipment are already using this as an opportunity to seize competitive advantage and establish the leadership in the market.

Compared to the advancements and innovations happening in other industries, the valve industry seems to be stagnant over the last few decades. Few valve industry leaders are investing in this future and exploring additive manufacturing, IoT and AI. It's time to take a serious stand. If not acted upon, this revolution might become disruptive for many businesses.

In this blog, we will look at a few of the emerging technologies. We will try to understand what the technology is and how it is changing the world of product design and engineering. We will also discuss how the valve industry can respond to these technology trends.

These are my opinions based on my analysis and understanding of both the advance technologies and valve industry. If the blog helps/contributes/initiates the thought process of “how can we use these technologies for valve industry" amongst industry leaders, I will consider this as a huge success of the blog and my efforts. These are my personal thoughts and anyone who feels aligned or otherwise, is welcome to discuss this further with me and my team.

So far – Product design and engineering environment

Product design and engineering is a core component of any industry. Design and engineering methodologies have gone through many transitions. For several millennia before the onset of industrialization, design and product engineering were often done by individual craftsmen. These individual innovators used their skills, experiences, and experiments to realize an idea into a product. The industrial revolution in the 18th and 19th centuries brought a radical shift and brought the mass production of identical objects at the forefront. For the first time, the act of design became separated from the act of making. There was a shift from the individual designer's craftsmanship to standard design methodologies and processes. In response to industrialization and mass-production, the “design method" approach is developed in the mid-20th century. This changed the nature of the design.

In the view of design and product engineering, two important revolutions happened during the mid-20th century.

Information Age

The first one is the digital revolution which began between the 1950s and 1970s. It is the development of computer technology from mechanical and analog to digital. During this time, digital computers and digital record keeping became the norm. By the 1960s, many governments, military forces, and other organizations were already using computers. Soon after, the computer was introduced for common use and by the 1970s, many design teams had computers to perform various tasks. The introduction of digital technology also changed the way designers communicate, keep data log and do calculations. This revolution led way to the Information Age. This brief history of the digital revolution infographics gives a good picture about what has happened over last 70 years.

Computer aided design and engineering

The second breakthrough is the evolution of computer-aided-design (CAD) and computer-aided-engineering (CAE). Computer-aided Design (CAD) refers to the use of computer systems in the assistance of the creation, modification, and analysis of a design. Modern engineering design and drafting can be traced back to the development of descriptive geometry in the 16th and 17th centuries. Drafting methods improved with the introduction of drafting machines, but the creation of engineering drawings changed very little until after World War II. The work of two people in particular - Patrick Hanratty and Ivan Sutherland - who are largely credited with setting the stage for what we know today as CAD. By the 1970s, research had moved from 2D to 3D. With the emergence of UNIX workstations in the early '80s, commercial CAD systems like CATIA and others began showing up in aerospace, automotive, and other industries. But it was the introduction of the first IBM PC in 1981 that set the stage for the large-scale adoption of CAD. The following year, a group of programmers formed Autodesk, and in 1983 released AutoCAD, the first significant CAD program for the IBM PC. Over the last four decades, CAD technology has gone through many transitions and today, it has become a front-line method to convert an idea into demonstrable, viewable, and manufacturable products.

Computer-aided engineering (CAE) is the use of computer software to simulate the performance of a product to improve the design or facilitate solving engineering problems for various industries. The application of software may include simulation, validation, and optimization of products, processes, and manufacturing. The history of CAE is surprisingly long, and the range of fields in which it is used is becoming increasingly wider too. The history CAE can be traced back in the 1940s where bell labs developed a ballistic computer for calculation of ballistic trajectory. The real usage of CAE tools/techniques started in the 1960s when the analog computer was replaced by fast, accurate, reliable, and cost-effective digital computers. This gave birth to many companies and products in the area of CAE which is over $10B industry today. Visit this interesting blog on CAD/CAE companies: An interactive timeline to see details about the history and various companies' timeline starting from 1960. Originally, CAE began with the idea of first thinking of the design and then simulating whether that design will work properly or not. Now we have come to a stage where CAE is being used even before the design is drawn.

All these revolutions have caused a drastic change in the way product design and engineering is carried out. The computer speed has gone through many transitions and what was available at a dedicated super-computing facility, is now available at individual designers' desks. The research codes and techniques which were available at the research facility and academic institutes are now available as easy-to-use products. Over the last seven decades, the design environment has changed drastically. The use of a computer, CAD and CAE tools have become an integral part of the process. The tools and techniques have become more sophisticated and started providing more and more insights into the product design and performance.

What remained unchanged?

Even though there is a huge transition in the way product design and engineering is carried out, the fundamental design process remained unchanged. The product design and engineering required sophisticated tools and experienced engineers to materialize ideas into a product. Over the years, all advancements in computational power and design techniques have helped engineers to evaluate design performance quickly. But it is still designer-dependent, and the final form of the product depends on the available expertise. The optimum design of the product remained highly dependent on the experience and expertise of individual designers, teams, and many times the legacy data.

New era – Product design and engineering environment

In my opinion, what we are witnessing today is a new era of how product design and engineering is carried out. There are many reasons why this transition is happening today. If I try to put all the reasons into two categories, I cannot think of anything other than "it's possible today" and "it's inevitable".

The first reason [category: possible today], is the enormous amount of computational power available at our fingertips (cloud computing) and advancements in the tools and techniques available to evaluate what-if scenarios. The second reason [category: inevitable], is that the market has become competitive than ever. There is unparalleled stress on organizations about reducing the product cost at the same time creating the best possible designs. Just to add to this complexity, the industry must quickly respond to customer needs. Manufactures no-longer can invest months and years of R&D work to come up with the design. Regulations are becoming tighter. Customers are no-more interested in off-the-shelf products and demanding more custom products suitable for their own requirements.

This overgrowing demand for the optimized products, quick turn-around time and more make-to-order product are giving rise to the new era of product design and engineering. It is making it inevitable. This is demanding the new ways the idea and customer requirements are converted into a product. Below are the few technologies / approaches in this new ear of product design and engineering. I have tried to divide that in to "possible today" and "inevitable" categories.

Generative design is a design exploration process where designers or engineers input design goals and constraints, and the software explores all the possible permutations of solutions and quickly generates design alternatives. Along the way, it also learns what works and what does not work. And this is a major shift. The designer just focuses on providing accurate performance parameters and constraints. The system/software generates all possible designs for us. The task of generating the design is off-loaded to an algorithm than the human designer. Software are playing a as smart assistant in design process. There have been great success stories of using generative design. In my opinion, this technology is not a new arrival. The shape/topology optimization techniques were available for many years. What has changed today is an enormous amount of available computational power and sophistication of the available products. And that's why it is possible to use this today to find that unique design which was not possible to find using a conventional design method. In the coming few years, we will see more and more use of this technology and more innovative and optimized designs.

The second important transition today is the use of past design data and experience to create new designs. You may see a lot of references like "data at the center", "data is new oil" and "data-driven design". Over the years, a designer develops expertise in specific product design. He goes through the best design practices, talks to design experts, learns from them and conducts many experiments. That's the way the expertise is developed. All the designers go through the same process. What if this expertise is captured in a system? What if there is some system, which understands all the design iterations done, what worked and what failed? What if there is a system which can predict what will work and what will fail, the way an expert designer can understand and evaluate the design. This is exactly achieved by Machine Learning. This is exactly what Artificial Intelligence is doing for the design community. In one of the forms of ML, you provide the input and output for various scenarios. You really don't know, what is the process/equation/technique to get the required output. The ML algorithm will find what is that secret recipe to convert the input into an output. Once ML algorithms are trained, it will quickly and accurately tell you what the impact on output will be if inputs are changed. ML helps to capture huge experimental data, design expert's knowledge into a system. Once this is done, the design process does not depend on the availability of experts. The human expertise, legacy data, experimental data is utilized to add artificial intelligence during the design process. One example is ML-based valve design application developed by simulationHub. This application is based on 960 valve design variations and flow performance data. It's an interesting test case of how ML can be used in the valve design process. Read more about how we have developed this application and get a live experience of using the application.

simulationHub's valve design using Machine Learning - ML application

There is nothing new about the core of machine learning. Multidisciplinary design optimization (MDO), genetic algorithm, neural network, data analytics, and many such ML techniques have a long history. It is possible today, as these techniques are available as a ready to use, simple library/API. It is possible today as we have huge computational power and a system that can quickly go through the data and understand the correlation. There is a lot of work happening on making these techniques more accurate, training them on more and more data and making these more accessible. Many organizations are investing in collecting the legacy data, product performance data, design methods to build the custom ML model to suit their business needs.

Another transition happening today is a true evaluation of "what-if" scenarios. In the optimization community, we call this as design-of-experiments (DoE). In simple words, it's the process of changing the various design parameters and understanding its impact on the design output. This is carried out to find the perfect combination of design parameters to generate optimum product design. There is nothing new about this method too. Many designers use this method in their day-to-day design activities today. The only difference is the number of design iterations conducted before the final design is selected. In the past, the design iterations were limited due to two major factors. First, the cost required to evaluate each design and second, the time required to get performance of each design. In the conventional experimental methods, evaluating one valve design takes weeks or months and requires huge budget. The alternative approach of evaluating product performance is by using software (CAD, CAE etc.). This approach has reduced the time and sometimes cost also. But most of tools are complex to use and needs an expert. In past, the extent at which DoE was done, was limited by available experts, and how much an organization can invest in the software and hardware infrastructure and many other factors.

This scene is changing now. Cloud service providers like Amazon (AWS), Microsoft (Azure), Google (Google Cloud), has provided access to limitless computational power. We no longer need to invest heavily in buying the compute power, we can simply use it as per our need and pay for what we use. The second factor causing the change is a transition in the way the software is available. The SaaS (Software as a Service) model is becoming more popular where you pay for what you use. For example, simulationHub's Autonomous Valve CFD (AVC) application. This cloud-based app allows running multiple scenarios simultaneously. In one of the experiments, while building the valve design ML app, we conducted 960 design evaluations in just 3 hours. Using the simulationHub Web Services (SWS) platform, we did the process automation and completely removed human intervention. And that's the power of the combination of both cloud computing and advance products. The availability of cloud computing and advanced products, making it possible to evaluated multiple "what-if" scenarios to achieve optimum product design. This is becoming more affordable, accessible and usable for all design communities. The way computing power and products are progressing, we will see designers evaluating almost all design combinations to get a true optimum product design.

The valve industry is witnessing the changing landscape of customer demand and supply. The industry is witnessing the paradigm shift in customer behavior. With process control becoming more sophisticated, the customer has access to the huge data about various process parameters. There is an overgrowing demand for process optimization. Every day, the process industry is challenged by bringing the optimized product with a minimum possible cost. The valve is critical and many times the final component in the process control, and that the reason why there is a huge demand for optimized valve performance. The "off-the-shelf" valve demand is reducing day-by-day and customers are expecting the trailer-made, customized valve which will meet their specific requirement. Because of this paradigm shift in customer demand, many industry leaders in the past are struggling to acquire minimal market share today. Various stringent norms like fugitive emission are being imposed, which demands to relook at the legacy valve designs methods and define the product road map to tackle these stringent industry norms and overgrowing customer demand.

To summarize, over the years, we have seen many transitions in design and product engineering. What we are witnessing today is not the betterment of existing methods, but we are looking at a radical change in the way product design and engineering is done. In my opinion, generative design, ML and data-driven designs will become an integral part of every product design and engineering process.

Response of valve industry for these technology trends

The valve industry needs to respond to these latest technology trends to make sure that the industry is not leftover or behind what's happening around. Or to put it more empowering context, the valve industry needs to use these technologies to tackle the current and future demands of customers and the market. The companies need to use these technologies and trends to create a unique position in the market and be a market leader.

I have been working with the valve industry over the last 10 years. During our CFD consulting days, we worked with various valve companies and provided the design and analysis services. Over the last two years, I am interacting with the industry leaders and designers for our Autonomous Valve CFD (AVC) product. Through my interaction with industry, what I have understood is, many of the valve companies have incorporated CAD and CAE methodologies in the design and engineering workflow. Few companies are doing this in-house and many are getting it done through consultants. Over the years, companies have transitioned themselves from 2D drawing to 3D CAD and analytical methods to CAE methods. Many companies have developed their own design methods based on their legacy data and design practices. Few have the central "expert teams" which comes in the play when something new is to be done. So far, the companies have adapted to the changing environment of valve design and engineering.

simulationHub's Autonomous Valve CFD (AVC) application

Overall what I have noticed is that the advancements in the valve industry happen at a slower and more evolutionary pace than what happens in technology-intensive industries like automobiles and aerospace. That might be one of the reasons why I see few examples of the actions on these new technology trends, this new era of product design and engineering. I see a lot of things happening on smart valves, research work in fugitive emission, wireless actuators and IoT. I also see some of the examples of using additive manufacturing like Ramén Valves, GE Oil & Gas, Mesto, Bray. But not much happening in generative design, ML and artificial intelligence.

Considering the growing demand in the customized products, tight limits on the product cost and churching timelines on R&D and product development, it's time to look at these advance technologies seriously. I believe it's time to look for an alternative approach to satisfy the need of the future.

So, the question is, how do the valve industry can respond and leverage this new technology? Although there is no standard roadmap or answer to this question, here are some of the things that the industry leaders can do:

Be informed and spend time learning

Know what is coming, be informed. If you really don't know what is coming, it will never be on your radar until it disrupts your business. By knowing what will or might happen, you can better prepare yourself. You can define your actions and reactions very well. By knowing what is coming, you won't be caught off guard if there is sudden change in the way things are done. Ask your team to spend some time learning about the new technology. Encourage and reward skill development. It takes time to learn what's on the cutting edge, but the innovation driven by your teams through emerging tools make it worth.

Understand change in customer and competitor behavior

Keep an eye on how the customer needs are changing. Your product might be satisfying the current need of the customer. But what will be their future needs, and do you have a technology to satisfy future needs. One of the best places to look at is your competitor. This may not always work, and it will not really help to establish market leadership, but this might be a good place to look for technology trends.

Ask what if we don't adapt?

It's just as important to understand your business as it is to understand the technology you're considering implementing. Ask some honest question:

Have a growth mindset

You need to take a long-term view of technology. The transition will not happen overnight. And, once the new technology is introduced into the organization, it will stay for a long time. So have a growth mindset in-terms of adopting the technology. Plan the roadmap for at least 5 to 10 years.

Planning and priority

You need to strategically plan the transition. Adapting the new technology should not be a tactical decision, rather it should be a strategical decision. Make the discussion around the adoption of new technologies a large part of your yearly and quarterly planning. Get everyone involved in finding out how new technology could solve one of your core business problems.

Balance between present and future

You cannot disrupt your existing way of doing things. You need to take care of the present, the present work orders, the present customer needs. You need to introduce new technologies slowly in the process. That would need a meticulous plan. There might be resistance to adapt to new technologies. You need to help your team to visualize the future and help them to live the designed future not the default future. You also need to create a correct blend of existing and new technologies and expose that to all the team members.

Experiment and prototype

You can plan for the experiment, but you will not come to know the results before the experiment is completed. You need to try the new technology, experience the benefits and limitations. The best way to do this is by creating prototypes. Identify the business problem. Create a small project around this problem and use new technology to solve the problem. Even if technology cannot solve the problem, you will come to know more about it, you will surely be able to identify the problems which can be solved with this technology. So, experiment and prototype around the new technology.

These are general guidelines about getting ready for future technologies. This is applicable across all industries. The leaders in the valve industry need to think and can use these guidelines to crate the technology transition roadmap.

simulationHub and its role in technology transition

CCTech (a mother company of simulationHub brand), is working on various product ideas over the last 13 years. We developed many products in CAD, 3D printing and CAE domain. The breakthrough really happened in the year 2015. We started conceptualizing a product with the vision of "Democratization of Technology". We wanted to develop a platform that will make the complex technology accessible to every designer, manufactures and anyone who can leverage the technology to create better, and optimized products. We spent six months to iterate on what that product would be. We talked to in-house and external design and consulting teams. We listened to their needs and constraints posed by their existing methods and tools. To democratize the technology, we realized that there should three basics attributed to the product "Accessible, Affordable and easy-of-use". This gave birth to cloud-based, appified SaaS product simulationHub. We realized that a general-purpose product may not able to serve the purpose of the democratization of technology. A general-purpose product will become too complex to use and defy the sole purpose. So, we decided to go to the "appification" way. The way to "take one problem at a time and build an autonomous solution for that problem". To achieve this, we realized that we first need to build a platform that will give access to all required small steps during the design and analysis process. To achieve this, we developed the simulationHub Web Services (SWS) platform. This is a cloud platform where all the micros steps are exposed as web services (APIs).

Once the platform got developed, we started the search for industrial problems to be solved. We talked to various industries and designers to identify the problem statement. We realized that the valve industry is the best candidate which can get heavily benefited by the democratization of CFD. So, we conceptualized our Autonomous Valve CFD application. This application solves the problem of calculating valve flow coefficients Cv, Kv and Cdt. This cloud-based application is a virtual test rig and conducts the valve flow capacity test according to ANSI/ISA–75.02.01–2008 standard. The application asks for very minimum inputs to the designer and conducts the test in a few hours. The app is benchmarked with several experimental test labs including UWRL (Utah, USA), FCRI (India). The results are validated with more than 30 distinct valve designs. This upfront design evaluation application is helping valve designers to predict the valve performance quickly, accurately and without much of the underlying knowledge of complex technology (CFD). It's not only the CFD, but the application also has various machine learning algorithm which fine-tunes the parameters based on valve type, complexity, angle of opening and many such input variables by the user. The way this app is conceptualized, it allows evaluating multiple "what-if" scenarios simultaneously. As mentioned before, 960 valve design scenarios in 3 hours. The app has opened a new window for DoE and true valve design optimization.

simulationHub research team is also working on "how can we use the advanced technology to solve valve industry problem?". The team is working on exploring machine learning and its application in valve design. In one of the POC (proof of concept) project, the research team has created a machine-learned valve design application. This application is a "data-driven" design solution where the flow coefficient values of 960 valve design variations are used. Read more about how we have developed this application and get a live experience of using the application. Another example is the use of Augmented Reality (AR) technology in the valve industry. The first application is 3D valve catalogue. In this application manufacturer's complete valve portfolio is displayed in Augmented Reality. This is a new way of visualizing the valve with all the specifications and its flow performance data. This creates a better experience, provides reach data about a valve and brings a huge advantage for the sales and marketing team. Another example is CFD simulation in AR. This application helps to bring the valve flow performance results in AR. The designer can use this to get more insights into the valve flow performance. This can also be used to demonstrate the valve performance to end customers and build more confidence about the product.

simulationHub's valve Augmented Reality (AR) application

Our research work is proof of concepts. The proofs that these technologies can be used successfully in the valve industry. This proves that it will add tremendous value and can create a unique position in the market. The only question is how to identify real problems and see how we can leverage these advanced technologies to create business value.

How can we work together?

Over the years of interaction with the valve industry, we have identified a few of the problems. We are working on those problems. We are creating a solution for them. But there are many. We cannot visualize all those problems. You, the one working in the valve industry, you the designer, you the valve manufacturer, knows them better. You know what business problems you are facing.

We understand this advance technology. We have invested years to know how the technology works. We know the best ways to utilize this advanced technology. We know how we can apply this advanced technology to solve engineering and business problems. We have experience and expertise to create a success story using this advance technology.

We both can work together. We can act as a consulting partner, a solution provider, a software developer. We understand technology and you understand your product. You know what problems are most critical. We know how can use advanced technology to solve that problem. You have all the required data and we know how to utilize the data and extract meaningful information out of it. We have already started the dialogs with a few of the leading valve manufacturers to layout the roadmap for advanced technologies. We are already helping a few valves manufactures in digital transformation. We both can work together to leverage the power of these advance technologies.

We want the valve industry to do a smooth and quick transition to this advanced technology. I believe that it will happen only through collaboration. It will happen only with the visionary leadership and carefully crafted roadmap. Me and my team will be glad to discuss this with you. Feel free to connect with me or my team.

PS: I would also love to write about other emerging trends like Augmented and Virtual (AR/VR) technology, IoT and additive manufacturing (3D printing) and how we can leverage that in the valve industry. Not here, not today. But would love to discuss this over a call or over a cup of coffee (if you invite me).

References

New ear of valve design

Valve additive manufacturing

Generative design

History of product design and engineering

Getting ready for new technology

Autonomous Valve CFD

Autonomous Valve CFD

Autonomous HVAC CFD

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