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Project of the Future – Roundtable

Transforming Construction: The Impact of Intelligent Production on Trade Contractors and the Future of Projects

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The panel discussion is about the Project of the Future session and Intelligent Production. Intelligent Production is a system that is able to self-organize and self-optimize. It builds on the capabilities of IoT sensors and wireless networks to collect data and quickly optimize the production system, controlling it without the need for manual decision-making. The panelists discuss the blend between mechanical engineering, robotics, artificial intelligence, and construction and how it’s going to change the traditional trade contractors’ job. The project of the future looks like having a better understanding and transparency of the process of construction from start to end, making decisions based on data and facts, and not on feel.


[00:00:00] Gary Fischer, PE: Now we’re going to have a quick discussion about all of this. We’ve asked some folks to come back and join us in a panel discussion about the project of the future. Iris and James and Bob. James, are you there? There he is. Okay. Great. Well, that was pretty insightful.

[00:00:27] Gary Fischer, PE: So, James, much of that touched on what Roberto mentioned briefly around intelligent production. Give us a snapshot from your perspective of what intelligent production is, how it relates to what Martin just talked about.

[00:00:41] H.J. James Choo, PhD: Yeah. So what is intelligent production? To simply put: it’s a production system that is able to self-organize and self optimize.

[00:00:50] H.J. James Choo, PhD: And what’s really interesting. It actually builds on some of the capability that Hunter actually also talked about. Fortunately, most of us here, again, Hunter exception, are not the ones that are actually investing to build awareness networks, actually build the data infrastructure and the Internet to actually make this happen.

[00:01:13] H.J. James Choo, PhD: We’re actually the bene– most of our construction industry is the beneficiary of it. At the same time, the supply chain folks are in the implementation phases of IoT to get visibility into what’s actually happening, right? And then all the mobile devices that are actually out there. So once you actually have the sensors deployed throughout the value stream and the data can be actually collected through the IoT sensors and the wireless networks.

[00:01:45] H.J. James Choo, PhD: What we actually have is the ability to know quickly. Production system models and use operations have optimized them and then feed that information back into the supply network so we can actually figure out how to actually best optimize the production system and control it without actually having the manual decision-making that actually happens on a day-to-day basis at this point in time.

[00:02:09] H.J. James Choo, PhD: So that’s our intelligent production. Very good. Yeah. Did you have something else? Yeah. And I thought it was actually very, very interesting what Martin actually talked about regarding what humans do versus what machines do. Yeah. And you know, in terms of, and in terms of the intelligent production, it’s interesting because as machines take certain portions of what humans actually have to do in response to actually be part of that or manage what actually changes.

[00:02:43] H.J. James Choo, PhD: So you start to really think about the different disciplines that we actually have in different organizations in this industry that we actually have currently. We might actually have a whole new set of industries or organizations that are formed that are not the traditional trade contractors, as it actually becomes more automated and the people that are actually.

[00:03:05] H.J. James Choo, PhD: Construction engineers may actually not be doing the same job that we’re actually doing now if some of the things are actually being automated. Right. So I think it actually brings a very, very interesting perspective to what is actually construction because it starts to plan with manufacturing and in the software industry as it matured, it actually is doing – people are building software that build the software automatically.

[00:03:27] H.J. James Choo, PhD: Yep. So, you know, where’s the blend between mechanical engineering, robotics, artificial intelligence and construction? I think that’s something that is very interesting. So, Bob,

[00:03:40] Gary Fischer, PE: let’s switch to you. I know you have some thoughts. You’re the guy doing the real work. What does that project of the future look like to you?

[00:03:50] Gary Fischer, PE: Oh,

[00:03:51] Bob Snyder: your audio is.

[00:03:56] Bob Snyder: I think the big part is really mapping and understanding it – the process of construction from start to end. Mm-hmm. and making all those parts and pieces transparent to everyone else. I think we’re so siloed. I don’t know that any one individual I know as a trade contractor, I really don’t understand.

[00:04:15] Bob Snyder: The designer’s process or the owner’s process in selecting an investment to make or necessarily the commissioning piece. So I think when we all start getting together and communicating, you’re going to start to see everyone having a much better understanding due to the transparency and sharing that data.

[00:04:32] Bob Snyder: And I think the decision trees are going to be much more rich in data and I think the decisions that are going to be made. Are going to be different because they’re going to be based on data and facts instead of based on feel, or they’re going to be based on the entire production system instead of just your silo.

[00:04:50] Bob Snyder: I think it’s, you know, we talked a little bit earlier about this: this idea of construction being very stage gated, right? It’s you, you come up with a concept. And once that concept is there, now you sit there in WIP and, you know, you make it and it sits in WIP and you build it and it sits in WIP and then you commission it.

[00:05:09] Bob Snyder: It’s all, and they’re not connected and it creates a tremendous amount of cash to do that. And if we can do real concurrent production engineering and really advise each of the silos, I think you’re going to make different decisions and I think there’s a huge opportunity to save time and cash and really increase the net present value of these investments.

[00:05:32] Gary Fischer, PE: Yeah, very good point. So, Iris, what are your thoughts on the project as the future? Yes,

[00:05:38] Iris D. Tommelein, PhD: well lots of thoughts and lots of thoughts that resonate very well with what has already been said with Martin’s, you know, terrific introduction to all the production tasks that are being automated today.

[00:05:51] Iris D. Tommelein, PhD: So, I was trying to think further out into the future than the things that we already have today. You know, we mentioned the need in our industry for experience and then making decisions based on facts. I think the term “experience” is very much overrated and it probably behooves us to better understand what kind of experience

[00:06:19] Iris D. Tommelein, PhD: our future construction personnel are going to need. So I think a lot of the experience that experienced professionals have, including myself, is actually experience based on kind of knowing what to do and knowing how to do it. But I would argue maybe sources of the kind of YouTube would tell us more how to do things.

[00:06:42] Iris D. Tommelein, PhD: Sources of the kind of Google that allow us to scrape the Internet will tell us more about what needs to be done, which regulations apply in which complex and so forth. So that kind of experience maybe will become less relevant and more automated in contrast. So, the kind of experience that is going to be needed more is judgment, right?

[00:07:02] Iris D. Tommelein, PhD: As human – human decision-making, as Martin mentioned so many times – human decision-making in terms of, for example, design methodology. My presentation this morning about tolerances was very much related to that. There’s no robot that can help us manage the tolerance management process at this point in time.

[00:07:21] Iris D. Tommelein, PhD: So there’s more work to be done in automating design tools and then being clear where the human decision-making, the human judgment, needs to come in. I think there’s also a lot of work to be done looking into data fusion. Beyond having robots that perform individual tasks. We need to look, of course, at robots, working with people, the cobots.

[00:07:44] Iris D. Tommelein, PhD: And then we also need to look at, you know, why not have fleets of robots supporting fewer people. Right? And how are robots going to collaborate with robots? And there may be – I have a somewhat more, what’s the word, pessimistic view than the view that Bob just communicated about.

[00:08:06] Iris D. Tommelein, PhD: You know, how nice would it be if we can only – if we can integrate all the data and share all the data? I agree. I think it would be wonderful if we can integrate and share the data, but there are a lot of people who want to own the data and we should not take it for granted that they will be willing to share the data.

[00:08:25] Iris D. Tommelein, PhD: Mm. And I think as academics, but I hope also industry will be behind this idea, that it’s going to be really important to collaborate on the data sharing. I mean, it’s an old idea. We talked about supply chain management earlier in this symposium. Many of the problems with supply chain management come from the BBI effect and the BBI effect.

[00:08:51] Iris D. Tommelein, PhD: And part is the result of lack of information as to how the supply chain is behaving. Likewise, I think we have a challenge ahead in sharing the data that comes from instrumentation that comes on, for example. You know, the bucket that you put in front of an excavator as opposed to the data that comes from the excavator itself as opposed to the data that comes from the operator who himself or herself may be somehow equipped with sensors as well.

[00:09:20] Iris D. Tommelein, PhD: And how, how do we put all that together and, and who’s going to own the data? This is not a new question. Certainly not. I’m not the only one who’s skeptical about it. But the good news is there are some industry efforts underway. I spent some time in Germany earlier. This, and one of the initiatives they have there, maybe Martin knows about it as well, is called Mick 4.0 machines in construction 4.0, where they’re trying to bring industry equipment manufacturers together to agree on the sharing of certain kind of data, not necessarily all the data that they’re collecting with their sensors, but sharing certain kinds of data, not just between the bucket and the –

[00:10:02] Iris D. Tommelein, PhD: but also with, for example, the construction managers who need to make decisions, maybe other people on site who need to make logistics decisions. So I think that’s where a lot of our work is headed. It’s trying to bring the industry partners together and really envision where we need to collaborate, as in sharing data and what we need to compete.

[00:10:27] Iris D. Tommelein, PhD: Of course competition is a healthy, healthy venture.

[00:10:33] Gary Fischer, PE: Insightful. So, Bob, reaction to that.

[00:10:40] Bob Snyder: Okay. I mean, there’s a lot of challenges with the sharing of data. They are grabbing this data, you know, the entire construction technology world is focused not necessarily on improving productivity. They’re, they’re focused on taking this data and capitalizing on it. That’s been really the big push.

[00:11:01] Bob Snyder: And a lot of the construction technology is coming to us in the form of administration. Things like Procore, right? That’s really been the focus. It hasn’t really been on production. And the reason it’s been on administration is because the amount of data that they can glom and take and take advantage of is huge.

[00:11:23] Bob Snyder: And that’s really been the push, you know, the one who owns the data, owns the world and the universe mm-hmm. And we see that across all industries. I think that we are so far away from the data sharing being that important to us. I think it’s just, let’s make the construction process transparent.

[00:11:42] Bob Snyder: You know, it doesn’t really matter how fast you do something or, you know, but let’s just start talking about it and at least let’s open our eyes to the fact that this is a complete production system. It really does matter. And just look at the simple things like the five levers and the WIP.

[00:11:58] Bob Snyder: And it’s all the stuff that makes so much sense. You don’t have to get a ton of data out of the process to make some massive changes to the process. And just start to inform it, you right the right way. So

[00:12:13] Gary Fischer, PE: you’re headed on your own journey to the project of the future. But what I hear you saying is kind of the baby steps.

[00:12:20] Gary Fischer, PE: First off, realize you’ve got a production system. Realize you need to bring transparency to it. Be more deliberate around it. Use the levers that control it and start the journey there. Is that

[00:12:30] Bob Snyder: what you’re saying? Yeah, I think it’s all about being curious because I think the journey becomes addictive.

[00:12:37] Bob Snyder: Because you know when you live in the trade contractor world like I have, you see all the problems, you just don’t know how to solve them or you just know why they’re there. And then when you start looking through this operations science lens, all of a sudden you realize, oh my gosh, what the heck was going on all these years?

[00:12:51] Bob Snyder: Now I know why I shouldn’t have, you know, a thousand feet of pipe sitting on the ground for a week. Why did I make a thousand? Why should I have made 500 or why did I make one? And really started analyzing, you know the whole process. And then looking at the batch sizes and then you start throwing some formulas against it and you’re like, holy moly, we’re really, there’s, it’s frightening that we’ve been wasting so much, but it’s also so damn exciting because there’s so much opportunity for improvement.

[00:13:18] Gary Fischer, PE: I see a lot of heads nodding here, Martin. You probably have companies come to you and say, “I want to get started here.” What do you advise them?

[00:13:27] Martin Fischer, PhD: Yeah, I think we, I see us being very, very, with respect to product or building or infrastructure, you know industrial facility design 20, 30 years ago.

[00:13:45] Martin Fischer, PhD: Because, we saw, and we have now all, every one of us is now well aware of the power of a representation of what we built that can be seen where multiple people can see the same thing, but that also has data and connects with computational capabilities, whether that’s structural energy or yeah.

[00:14:12] Martin Fischer, PhD: You know? Mm-hmm. And so we’ve all experienced it. And so that’s for me a blueprint of what we have to now do with production processes. And now we can, because at least the companies I work with, they don’t have actually, you know, they’re used to using something like a BIM. Yeah.

[00:14:34] Martin Fischer, PhD: Together we make the design of the building or whatever we are making better through the expertise we can bring to the process, because we can look at it. Because of the data we can draw from that model. And so now we need to do the same fit our production processes because very few production processes are done by one person.

[00:14:56] Martin Fischer, PhD: I mean, they’re almost nothing. So it’s, again, it has to be a collaborative approach. And so for that, we need a visualization and a computational tool. And I think that’s what we have available now. That’s what I would do. Start there. You know, you need to start relatively small in a few, maybe departments, etcetera.

[00:15:15] Martin Fischer, PhD: Like we saw from the examples from the students, that was fantastic. But then, you know, start to think about how you’re going to connect these production processes and how, so you can get to the bigger questions, you know, about just product, and even questions beyond that. But that’s why I would say you have this mindset.

[00:15:33] Martin Fischer, PhD: You need to build a digital twin of our production processes, digital and physical. That needs to be a support collaboration of people with different backgrounds and it needs to support simulation computation. And I know you have guys that have been working on this for a long time but I think the industry needs to now really jump.

[00:15:57] H.J. James Choo, PhD: I mean, as Churchill said, right, “Never let a good crisis go to waste.” I think we’re actually in a crisis mode right now, and I think, you know, people are actually looking for data. They’re trying to get their hands on data, but if we’re going to actually deal with data is, you know, track, monitor and progress management, then I think we should try to actually eliminate the need for that to begin.

[00:16:19] H.J. James Choo, PhD: Right. So the question is how do we actually do more with less people by innovating and automating what’s remaining and then eliminating what’s not necessary, right? I think that’s what we need to actually focus on because again, as we said, there’s more work than we have people there at this point in time, and it’s forecasted to remain even – get a bigger gap.

[00:16:44] Gary Fischer, PE: So wait, let me switch gears on you a little bit here. So TriPro is one of the first EPC companies we’ve seen really embrace a new way of doing things and thinking about things. Why don’t you think we have greater impact uptake in the whole EPC community than we currently have on this project in the future?

[00:17:06] Gary Fischer, PE: On this journey? Anybody want to take a hazard to guess?

[00:17:13] Gary Fischer, PE: Well, I mean, why don’t we start with you.

[00:17:16] Iris D. Tommelein, PhD: I think, I mean, Iris, transparency isn’t for everyone, right? Not everybody wants transparency, and this gets back to similar issues in supply chain management. It’s sometimes very difficult to know what happens. You know, with the second year and the third year subcontractors on your project, you know, maybe if you’re lucky, you know what your first year subcontractor is doing, but it’s, you know, what comes below is oftentimes very opaque.

[00:17:45] Iris D. Tommelein, PhD: And there obviously is a lot of value in getting that transparency so that you can improve your decision-making. In that sense, more data is usually better if you know how to use it smartly. But not everybody is interested in it.

[00:18:02] Iris D. Tommelein, PhD: Very a good point,

[00:18:05] Gary Fischer, PE: Bob.

[00:18:07] Bob Snyder: You work with a lot of these folks, I think, you know, it’s – production systems are about production and the largest piece of the puzzle is the labor. That’s your, you know, and the creation of actual physical transformation of pipe and fittings and things like that. You know, the data is a lot, but really it’s the physical transformation of the labor required to do that.

[00:18:28] Bob Snyder: And a lot of it really comes down to the labor of the field. So unless you’re actually direct hiring people you don’t necessarily see or feel the advantage of a production system mentality. True EPC companies who are actually doing tons of direct hire, I think it would, they would be foolish not to want to adopt or dive into this full fledged, but those were really, you know, EP, CMS, maybe they do some engineering procurement, but they’re really construction managers.

[00:19:01] Bob Snyder: I’m not sure that they see, they see the advantage of this. Because I think a lot of it proves some of the points that we should be limiting administration, which unfortunately the – a lot of the construction management is built off the backs of this idea of more administration yields better results and less time and more certainty.

[00:19:19] Bob Snyder: So I think, you know, I think you’re going to find that the bulk of your BCMs are RE, or EPCs are really EP, CMS, and they’re hiring trade contracts and subcontractors all the time. And they haven’t been forced into a position where the end result when it comes to the time being saved or the amount of production that they get hits their own personal bottom line.

[00:19:45] Bob Snyder: So I think that’s probably why you see more of a lean over to like the LCI stuff and that – and really this idea of not focusing on the work as much because they’re not really doing the work. They’re not

[00:19:57] Gary Fischer, PE: feeling the pain as much or the potential benefit as you would, for example.

[00:20:02] Bob Snyder: That’s really good, insightful.

[00:20:04] Bob Snyder: Yeah, I mean, I think, you know, we’re looking at running our company, like our entire company, a series of 10 or 20 major projects at one time and looking at it as one common production system because they intertwined, and I’m looking at, you know, our goal of life was always, “Hey, less labor’s better, right?”

[00:20:20] Bob Snyder: Less sub work, you know, subcontract work. That’s how you mitigate all your risk. But when you start looking through this lens, you’re like, “Hey, wait a minute, I should just hire labor myself” or “Hiring guys T&M, and taking on that responsibility because that’s where the uptake is for me.” I can, you know, I can hire guys at a T&M rate, and as long as they operate within my production system, I can afford that 10% markup to the subcontractor.

[00:20:44] Bob Snyder: But the gains are so much greater because of this idea of the production system. So it’s, I think a lot of that is really where this lies. That’s really insightful. I agree. Martin, were you gonna say something there? I was

[00:20:55] Martin Fischer, PhD: reminded, I mean, it’s curious what everybody else thinks. But a data point I got from our visitor we had a few years ago – I was talking about how Porsche improves his production system.

[00:21:08] Martin Fischer, PhD: And basically he said that, I think it was something like that. For every 150 people producing work, they have one person that is thinking about how to IM, how to improve that production. Mm-hmm. So in the factory of 1200 people, they have eight people focused on “how do we make the production system better?”

[00:21:30] Martin Fischer, PhD: How is it actually working? How do, and I don’t see these roles in our industry, don’t invest in that. That, I mean, I think that would help. I mean, I’m not sure that’s the entire solution, but could be part of a solution of advancing more rapidly. Yeah.

[00:21:46] Bob Snyder: That’s a really good point.

[00:21:47] Gary Fischer, PE: Hey, we got a really good question.

[00:21:48] Gary Fischer, PE: It’s kind of related to this. It’s, “How will PPM relate to cost management and contract management in the project of the future?”

[00:21:59] Gary Fischer, PE: Anybody want to take that one?

[00:22:08] Martin Fischer, PhD: So your cost management will,

[00:22:14] Martin Fischer, PhD: I was just thinking, am I simplifying too much? But I think it’ll be pretty much automated. Because what we’ve seen in research we’ve done, when you go to a great level of detail, which you will, if you build a production model, then any kind of summary can reduce very easily and rapidly. And you can close the loop at the detailed level at a summary level at, you know, you can then, then you can slice and dice the data as you need.

[00:22:45] Martin Fischer, PhD: If you have weekly progress portrayed and you want to remunerate that, you can do that. If you, I mean, yeah, whatever way you do that, then you can do that. Your cost management gets complicated when you don’t have detailed data and then you, but you need it in some cases and then it becomes a mess of reconciling accounting’s view with payroll’s view with the job site deliveries with etcetera, etcetera, etcetera.

[00:23:14] Martin Fischer, PhD: How about,

[00:23:15] Bob Snyder: how does

[00:23:15] Gary Fischer, PE: contracting need to change, Bob?

[00:23:19] Bob Snyder: What’s your, I think, I mean this idea of, you know, cost, like what is cost management to me? You don’t manage costs, you manage the things that create the costs. So we come up with all these terms, but at the end of the day, if you want to manage your costs, you manage the production.

[00:23:39] Bob Snyder: And you manage the capacity and you manage those things and you really don’t manage those things. You just make sure that the stuff is there when it needs to be and that you are, you know, trying to work on the variability across the production system. So it’s, you know, and then it’s the idea of con, like what’s a contract – it’s something you put in play to hold people accountable, but it, I’m not sure that.

[00:24:02] Bob Snyder: That’s, that’s risk avoidance. I’m not, you know, ppm you’re looking at production management. You’re looking at “how do we improve productivity across our production system?” Through the mapping and studying of the science behind that, and really contract management and cost management. They just become a byproduct of, let’s say, what you’re actually doing at that point.

[00:24:21] Bob Snyder: Yeah. We

[00:24:22] Gary Fischer, PE: I had a great conversation with Ford about this, and I, it was so different than when we were approaching it in Chevron, so we were using bidding. To get better pricing. Okay. I know that’s suboptimal. And Ford’s ideal price is a secondary issue to us. We look for people that we can work with that, have the technology we want, that can work within our production system the way we want.

[00:24:45] Gary Fischer, PE: We know what things should cost. So cost is a secondary issue. We have a two-page agreement. And the costs are a non-issue because we know what it should cost. We work that out. That’s just a non-issue. The important issue is how they work together in our production system and management blew my mind because that’s not how we approached it at all.

[00:25:02] Gary Fischer, PE: So I, from my point of view, that’s kind of what needs to happen differently in contracting, which I think is just what you’re saying, Paul, let’s get to focus on the right

[00:25:09] Bob Snyder: things. I mean, bidding and pricing is, I mean, if you bid projects, lump sum jobs like I do every day, and I’ve done for 30 years, it, you know, the actual cost of the thing is, I mean, that matters, but you’re looking really at the market.

[00:25:25] Bob Snyder: You’re looking at how much margin can I actually put on it? How much competition do I actually have? None of those things have anything to do with real cost. They have to do with “how do I make more money and survive in the business world?” So, it’s, you know, I can do the same job tomorrow that I did a year ago and I can be, you know, at a significantly different price.

[00:25:45] Bob Snyder: And, but basically the cost might just still be the same. It’s just that snapshot in time. You know, I only got – you only one bidder. Guess what? You’re going to pay more for me if there’s only one bidder every single time. So you just sound related. Related. Yep.

[00:26:00] Gary Fischer, PE: I hopefully addressed the question. Any other thoughts on that topic before we wrap it up?

[00:26:09] Gary Fischer, PE: All right. Well, I thank you all very much for your time and effort and thoughts and there’s a lot of meat in this conversation that we just had. So I think we’re ready to move on and talk about our next subject, which is around academic partnerships.

[00:26:25] Bob Snyder: Thank you very much. Thanks.

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Read Biography

Gary Fischer, PE

Project Production Institute

Gary Fischer, PE

Project Production Institute

Gary Fischer is the Executive Director of the Project Production Institute (PPI) and Chair of the PPI Energy Working Group.  He has over 40 years of experience in all aspects of capital project development and execution across downstream, chemicals and upstream in Chevron.  As GM of Chevron’s Project Resources Company, he was responsible for Chevron’s project management system, a supporting team of subject matter experts, an early concept development group, and Chevron’s decision analysis function.  Before retiring he took a special assignment to deploy Project Production Management and digital transformation across Chevron’s global portfolio of capital projects.  Gary’s prior experience includes project leadership roles in engineering, construction, and project management spanning across all segments and many locations. He also served as the upstream director of capital projects for Eurasia, Europe, and a gas to liquids venture with Sasol.

Gary holds a Bachelor of Science Degree from Colorado State University and is a licensed Professional Engineer.

Read Biography

H.J. James Choo, PhD

Project Production Institute

H.J. James Choo, PhD

Project Production Institute

H.J. James Choo, Ph.D is Chief Technical Officer of Strategic Project Solutions, Inc. and a member of the Technical Committee for Project Production Institute (PPI).

He has been leading research and development of project production management and its underlying framework of Operations Science knowledge, processes, and systems to support implementation of large capital projects globally since 2001.

James has worked with high profile organizations in oil & gas, life sciences, heavy industrial, civil infrastructure, aerospace & defense and other industries.  He has also worked with many manufacturing companies to improve their service levels by reducing lead times and optimizing inventory through the use of Operations Science.

James is a frequent contributor to research and curriculum for Texas A&M University, University of California at Berkeley, and California Polytechnic State University.

Prior to joining SPS, his experience included roles as a construction site engineer, research associate at research institutes, teaching assistant at universities, and software developer. He has been developing computer systems for implementation of Lean Construction since 1997 during his Ph.D. studies at UC Berkeley.

James has a Bachelor of Science in Civil Engineering and a Master’s Degree in Civil Engineering from Yonsei University, Korea.  He holds a Ph.D. in Construction Engineering & Management from the Civil and Environmental Engineering Department of University of California at Berkeley.  He is also certified as a Master Factory Physicist from Factory Physics, Inc.

Read Biography

Martin Fischer, PhD

Stanford University

Martin Fischer, PhD

Stanford University

Martin Fischer is a Professor of Civil and Environmental Engineering and (by Courtesy) Computer Science at Stanford University. He is also the Director of the Center for Integrated Facility Engineering, a Senior Fellow of the Precourt Institute for Energy, and the Coordinator of the Building Energy Efficiency Research at the Precourt Energy Efficiency Center.

His research focuses on modeling, predicting, measuring, and improving the life-cycle performance of the built environment. He is known globally for his work and leadership in developing virtual 4D modeling methods to improve project planning, enhance facility performance, increase the productivity of project teams, and further the sustainability of the built environment. His award winning research results have been used by many small and large industrial and government organizations around the world. He has published over 100 refereed journal articles and book chapters and given over 50 keynote lectures on his research.

He has lived, worked, consulted, and taught in Europe, South America, North America, the Middle East, Asia, and Africa. His consulting work includes building owners, architecture and engineering firms, construction firms, government and research organizations, and software companies.

He holds a Diplôme d’Ingénieur in Civil Engineering from the Swiss Federal Institute of Technology in Lausanne, a MS in Industrial Engineering – Engineering Management and a Ph.D. in Civil Engineering – Construction Engineering from Stanford. He received the CAREER award from the National Science Foundation in 1996, was named a top 25 Newsmaker by Engineering News Record in 1996, won the best paper award from the ASCE Journal on Computing in Civil Engineering in 2002, and was elected as a Foreign Member of the Royal Swedish Academy of Engineering Sciences in 2012.

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Iris D. Tommelein, PhD

UC Berkeley

Iris D. Tommelein, PhD

UC Berkeley

Iris D. Tommelein is a Professor of Engineering and Project Management in the Civil and Environmental Engineering Department and directs the Project Production Systems Laboratory (P2SL) at the University of California, Berkeley.

She has been studying, developing, and applying principles and methods of project-based production management for the architecture-engineering-construction (AEC) industry, what is termed Lean Construction. Her pioneering research in Lean Construction includes teaming up with design specialists, general- and specialty contractors, owners, suppliers, and other stakeholders in order to increase process and product development performance. She is an expert on site layout and logistics, operations and methods design, materials management, and supply-chain management. She is involved in developing digital twins and related decision-support systems, enabled through the use of information technology systems that leverage sensor data, heuristic- and mathematical optimization as well as artificial intelligence (AI), and graphical and interactive user interfaces. Her current research focuses on takt planning.

Iris has led many industry workshops, hosted conferences on Lean Construction, and is actively engaged in consulting work. She has published over 250 refereed articles and book chapters and given numerous keynote lectures on her research.

Iris graduated as Civil Engineer-Architect from the Vrije Universiteit Brussel (VUB) in Belgium. She also holds a MS in Construction Engineering and Management, an MS in Computer Science (Artificial Intelligence), and a PhD in Civil and Environmental Engineering from Stanford. She was recognized with the Lean Pioneer Award 2015 from the Lean Construction Institute (LCI) and is a member of the National Academy of Construction (NAC).

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Bob Snyder

Binsky & Snyder

Bob Snyder

Binsky & Snyder

As a fourth-generation owner, Bob Snyder has worked and been involved in the mechanical contracting industry since his youth. Bob’s experience spans all aspects of the business including Sales and Estimating, Project Controls and Management, Engineering and Drafting, Purchasing, Information Technology, and Financial Management.

In addition to office and management experience, Bob worked in tool and fabrication shops, spent time on the road in a service van working in the field with service technicians and developed hands-on skills on projects working with the plumber and pipefitter craftsmen. As a graduate engineer, Bob has strong technical and design aptitude and has a vast understanding of both conceptual and technical aspects of mechanical systems. He also has a great level of experience in information technology and has been involved in designing the project control systems used at Binsky. Bob has devoted significant time to the Mechanical Contracting Association of New Jersey and Industry Council, currently sits on the Board of Directors, and holds the position of Secretary/Treasurer. In addition, Bob has served as a Trustee on Plumbers Local 24 and currently on Pipefitters Local 475.