Predicting the Future of Engineering Technologies Isn’t Exactly a Science
Jeffrey Rowe posted on January 22, 2019 |

Partial federal government shutdown aside, 2019 has kicked off and a number of my peers and fellow pundits are hedging bets on how things will play out in engineering technology this year. I caught up with Dave Opsahl, vice president of Corporate Development at Tech Soft 3D for his take on the coming year with some engineering technology trend predictions.

Do you believe in fortune tellers? I personally don’t, but regardless of whether you do or not, predictions are still fun to make and pontificate on. What follows are Dave’s 2019 predictions for the overall technical software solutions industry based on a conversation we had recently.

Below, Dave Opsahl’s remarks are indicated with “DO,” and mine are “JR.”

Prediction #1: The pace of acquisitions and industry consolidation will continue.

DO: This might be an easy one, but with the threat of an economic slowdown, acquisitions aren’t as attractive as you might think. However, the pace of acquisitions in 2018 dwarf that of recent years and show no signs of slowing. The private equity market has tremendous amounts of cash looking to be put to work. For example, companies like Aras have received substantial capital infusions, and corporate buyers have record cash reserves as well as historically low capital costs. It feels a bit like a land grab out there. Acquisitions (as measured by volume and value) should equal or exceed 2018.

JR: No secret here. As far back as I can remember, the CAD/CAM/CAE industries have been perpetually consolidating, and there are no signs of this abating. More recently, it hasn’t just been companies acquiring similar companies, such as PTC acquiring CoCreate—CAD and CAD. With greater frequency, companies are acquiring complementary companies, such as ANSYS acquiring SpaceClaim—CAE and CAD. I see this acquisition trend continuing as some companies look to make their offerings more comprehensive—and it makes business sense to do so, either by absorbing technologies into their own, or continuing to develop them as separate products or brands (think Dassault Systèmes SOLIDWORKS, ENOVIA, etc.).

Prediction #2: License revenue growth from sales to the AEC/BIM/process industries will exceed that of the discrete manufacturing industry.

DO: As measured by overall revenue, the discrete manufacturing market has, going back decades, been the most attractive market for solution developers. Over the last several years, though, we have seen advances in the AEC/BIM/process industries that are driving massive changes in their workflows. There has been much press given to the benefits of BIM as what amounts to the “digital twin” of a building or plant for the owner/operator, and substantial amounts of new regulations demanding BIM compliance—mostly in Western Europe. The move from design-bid-build to design-build is having a huge impact. The percentage of growth in the overall AEC/BIM/process market will be higher than discrete manufacturing in 2019.

JR: Again, this is no secret as witnessed (again) at Autodesk University 2018, as a majority of the noise and announcements made were regarding AEC/BIM. Building and construction worldwide are booming and there seems to be no end in sight as population grows and the universal influx to cities continues. All this AEC activity requires software for every aspect of the process, so AEC/BIM software sales should continue at stratospheric levels for the foreseeable future.

Prediction #3: “Digital transformation” becomes the dominant marketing message.

DO: Let’s face it, in a red ocean market like ours, marketing professionals are finding it increasingly difficult to gain mindshare with potential customers. When additive manufacturing exploded a few years ago, we were bombarded with—“this is how our solution can leverage your additive manufacturing strategy.” Anything to connect yourself to a hot trend. More recently, it has been how mixed reality is going to change your world. Going into 2019, expect to see the majority of solution providers cast their value in terms of how it enables digital transformation, as evidenced by the messaging on their websites.

JR: This goes hand in hand with other coined terms of late, including Industry 4.0, digital twin, smart products/Internet of Everything, and smart manufacturing. Before that, it was things like “totally integrated solutions” and “paradigm shift.” “Digital transformation” is just a natural evolution and outgrowth of what has been happening in product design, manufacturing and consumption for years, and just the latest spin on gaining mind and market share that could literally mean anything (or nothing). I suspect that this particular moniker will be short lived as everybody tries to jump on the bandwagon and define what it is to their best and specific advantage.

Prediction #4: Simulation process and data management (SPDM) will be the next “new thing.”

DO: Every so often our industry hits an inflection point, where the technology now available makes it possible to rethink the way we do things. Solid modeling is a case in point; additive manufacturing has done the same thing in this decade, and more recently IoT and generative design have taken on that mantle. Right behind is SPDM, which is turning the way we think of the role of CAE and simulation on its head. The goal is to democratize the use of analysis and simulation data, which will enable process improvements across multiple disciplines. Expect to see a host of new offerings coming in the SPDM space in 2019.

JR: The significance and impact of simulation have been moving further forward in the product development process for years and with good results. Instead of being an afterthought, simulation is increasingly being regarded as a vital aspect of the design process. Even bigger, though, is that physical processes along with products are being simulated and the data generated from both are being integrated into a comprehensive data management system with links to PLM and ERP systems. A positive result of an SPDM is that it lets manufacturers control the use and storage of calculation data, possibly achieving significant time reductions spent in managing data. This concept is just beginning to gain traction, but is highly regarded in industries such as aerospace and automotive.

Prediction #5: Software components are still relevant for engineering software.

DO: When you look at PTC’s acquisition of Frustum, this is an example of a component that really hasn’t had a space (generative design) yet, but will be integrated into existing products at a rate we can’t yet appreciate. nTopology is another example of a component developer (topology optimization) that should get snapped up by another company in the not too distant future. But who? That’s anybody’s guess, but I suspect it won’t take too long before this component developer is acquired. Beyond outright acquisitions overall, there seems to be more of an appetite for licensing software components as more vendors try and move their solutions to so-called digital transformation (mentioned above). Anything you can get that pushes technology to a commoditization level will result in more software component use, and that’s a good thing. This trend could be illustrated by Convergent Modeling at Siemens and how it’s brought into the modeling scenario for choosing B-rep, meshing capabilities, or an integration of both, whichever best suits a design situation.

JR: For quite a while now there has been a lot of banter throughout the MCAD community about the significance of software components. While it’s true that few users really care about the origin of software components, they are good for the following reasons:

  • They are developed, supported and maintained by an expert source that focuses on improving specific aspects of the component.
  • They allow relatively small organizations to develop applications relatively economically and let them focus on what they do best.
  • They are updated and released on a regular schedule so customers can time their application releases accordingly.

As they have been in the past, software components will remain significant and relevant into the future for the MCAD industry.

Side note: There is a movement afoot as to whether B-rep is necessary at all, and this is something that we’ll follow up and report on in the near future.

Prediction #6: Cloud-based (SaaS) engineering apps will continue to proliferate, but . . . .

DO: There are too many people equating multi-tenant (an architecture in which a single instance of a software application serves multiple customers and each customer is called a tenant; tenants may be given the ability to customize some parts of an application, but they cannot customize the application's code) with cloud, so it’s important to make the distinction. There will be a lot more cloud adoption, but not in multi-tenant mode because of security concerns and data leakage. Beyond security concerns, another major issue that nobody wants to talk about with services in the cloud is how will these proliferating services talk with each other and interoperate. Connecting to the cloud and utilizing available services with existing in-house systems with guaranteed performance or else why not just run it privately is also a huge issue.

JR: For as long as I can remember, cloud computing has offered two things—endless (unrealistic) promises and perpetual (unrealistic) growth. For some time that was true, but several things have occurred in the past couple of years that temper those claims and portend what might happen in the future for technology providers that become increasingly reliant on the cloud—reliability, accessibility and security. Cloud computing is still as much a work in progress as it is a market offering.

It wasn’t all that long ago that an executive of a major engineering software firm said that his company was not at all interested in the cloud as a platform (product, service or otherwise) because he likened it to nothing more than vapor. Well, times have changed, and that same company has devoted a lot of resources to cloud offerings—something it claimed a few years ago it would never do. How times (and attitudes) change.OK, the cloud is more than vapor. That’s a given, but is it perfect? Of course not, but it is evolving and improving at a very high rate.

Prediction #6: Engineering security issues will continue to be at the forefront for adoption issues.

DO: There are concerns and challenges of security when transitioning to the cloud, but a lot of the security issues could be addressed with blockchain, because it has a lot of potential to solve problems with non-repudiation (the assurance that someone cannot deny the validity of something; non-repudiation is a legal concept that is widely used in information security and refers to a service, which provides proof of the origin of data and the integrity of the data). The idea is that if information is being transmitted but not incorporated in a design, you ask why or why not, and are asked to prove it. Blockchain can solve this problem instantly because it provides a traceable trail for all information. This is especially important as supply chains get more and more distributed and need to be held accountable for everything.

JR: While cloud-based engineering services are certainly nothing new, there still remains a gnawing reluctance that prevents some prospective users from embracing the cloud—security. One of the most compelling reasons to switch from traditional on-premise systems to cloud-based alternatives is that services support virtually any office or engineering application and are data neutral, especially important for CAD files. As important, however, is the fact that cloud-based alternatives are inherently secure when compared to traditional data methods and could be made even more secure with blockchain.

Keep in mind, though, while it is possible to store data on a blockchain, the protocol was not designed with data storage in mind. Blockchain data security is especially effective because only a hash of the data and parts (subsets) of the data are stored on the blockchain, and storing these data subsets is decentralized instead of storing them in a centralized database on, say, a server in the corner or some consumer-grade cloud storage services.

Prediction #7: AI is just starting to come into its own.

DO: It plays quite a large role in generative design and factory operations. There are some large semiconductor fabs that cover acres but are run by very small numbers of people. This would be impossible if not for the advances in AI and machine learning to make adjustments, perform predictive maintenance, and so on. AI should help generative design really take off in a different direction from early adopters, but which direction is anybody’s guess.

JR: AI and machine learning are not new concepts; they have been around since the 1960s. However, all the elements required for machine learning have come together only recently. Access to more bandwidth to transfer data over the Internet, affordable data storage, and increasingly powerful computational resources is now widely available. Most importantly, universal accessibility to robust algorithms democratizes the use of machine learning. In other words, machine learning is the learning in which a machine can learn on its own without being explicitly programmed. It is an application of AI that provides a system the ability to automatically learn and improve from experience.

So, there you have it. Will all of these predictions actually come true? Probably not all of them, as there are no guarantees, but I would venture to bet that most will, at least to some degree. In any case, 2019 promises to be another exciting year for engineering design and simulation software.

If there is anything you think will be prominent or earth-shattering in the engineering technology arena in 2019 or beyond, let me know.


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