Bringing Digital Manufacturing to Market
Last week in Washington, D.C., the National Center for Manufacturing Sciences (NCMS) and Intersect 360 Research presented the results of a survey based on over 300 manufacturing firms in the United States about the current state of digital manufacturing technologies. More specifically, the questions were aimed at ultimately identifying the key barriers and drivers for their adoption of complex technologies to drive innovation.
While we will touch on some of the findings of the research and its potential implications in a while, it should come as no surprise that the “missing middle” designation became a key, guiding phrase. Many in the HPC community have already heard this term repeated elsewhere, it is not always a common, understood concept for those who hold the purse strings—namely representatives in the U.S. government, some of whom might not have even been familiar with the broad domain of high-performance computing and the many layers of meaning and technology that comprise it.
The goal of the research and presentation was to convince government leaders of the inherent value of making high-performance computing software and resources accessible to the manufacturing sector from the bottom up. Without having access to core technologies, particularly in the realm of modeling and simulation, many smaller design and manufacturing shops have a hard time remaining competitive—and we all know what this “trickle up” impact is on the national economy.
Again, chances are you’re well aware of the concept of the missing middle, but let’s take it one step further and enter the realm of manufacturing, HPC and this presumably vast, lost subset of the HPC-denied American economy.
The Digital Manufacturing Angle
The concept of digital manufacturing itself can appear, at first, as a bit too broad or nebulous, in part because from first glance, it implies that the final product is digital in nature or otherwise not tangible enough to apply to something as solid as manufactured products. Digital manufacturing, however, refers to the entire lifecycle of a design or product that was based on the use of advanced computational resources and technologies to deploy simulation and modeling for multiple aspects of the design and development process. As Intersect 360 Research notes, “by creating a digital model of a product, a manufacturer can perform a wide range of tests, such as manufacturability analysis or performance testing, before physically building a new design.” It is in this total solution based on technology that digital manufacturing as a term is best applied.
What this overarching concept of digital manufacturing ultimately means is that companies who feed the manufacturing supply chain are able to improve their final product through refined design and testing efforts and furthermore, many are able to speed the time to market for their products since testing engineered parts or complete products can be time-consuming and expensive.
One of the better ways to think about digital manufacturing is to consider it in the case of a manufacturing firm at the top of the food chain, heavy-equipment maker Caterpillar.
Feeding a Caterpillar
Although not a missing middle company by any stretch of the imagination, providing an overview of how HPC does work for refining the product lifecycle (and the challenges that are present when the HPC absent from it) can almost be better realized via a case study of a company that is thriving versus one of the many missing middles who plod along with legacy systems and 2D rendering software. After all, we know what their challenges are. But for a massive manufacturer who has both high-end systems yet still occasionally resorts to older, more expensive testing and design methods, we have a more thorough perspective.
Fortune 50 heavy equipment manufacturer Caterpillar’s research program manager for virtual products, Keven Hoftstetter, highlighted the key benefits and challenges of modeling and simulation for the company’s product cycle and bottom line last week during the manufacturing and HPC-related HPC 360 event in Champaign-Urbana, Illinois. The equipment manufacturer is a top-tier user of HPC, thus they certainly do not fall into the “missing middle” that has been clearly defined for the manufacturing sector and includes the smaller firms that support the supply chain that migrates to a summit that would include a company like Caterpillar.
Caterpillar is a company on the bleeding edge of modeling and simulation for manufacturing, both on a software and hardware/GPU level. Caterpillar places significant emphasis on research and development projects to helps refine product development and bring their line of equipment to customer as well as environmental standards. In addition to the core elements of their manufacturing business, they also house other broad divisions handling equipment financing, logistics, and remanufacturing/rebuilding.
As one might imagine, Caterpillar’s needs go far beyond modeling or simulating the machine functions since there are many parts that are required in advance, all of which much operate a peak performance, both individually and inside the specific machine. Accordingly, research and development at Caterpillar is the backbone of profitability on the micro level (testing pistons, for instance) to the macro level (making sure an earth moving vehicle performs on target).
While Caterpillar’s basic product cycle model is the same as many other manufacturing companies (concept; design, then on to the build and test phase, and finally the production phase) the products that they are developing and testing are on the massive scale. It is not feasible to build giant centers to house and test the actual prototypes in a repeated, 24×7 manner as they have been doing before taking advantage of simulation to handle their design and test process. Hoftstetter noted that they built a 10-acre facility to test their earth moving equipment but if they had to continue to build out centers like this they would be unable to compete.
Caterpillar also devotes a significant amount of time and resources into the many parts and components that are critical to their earth moving equipment. For instance, Hofstetter noted that since they are a leader in diesel and natural gas engines and industrial gas turbines a great deal of their research and development efforts are related to computational fluid dynamics and combustion system interaction.
Since it would not be viable for a company like Caterpillar, who sits at the top of the supply chain and has far more resources to continue to competitively develop and test its products without sophisticated modeling and simulation software and the resources required to power it, why would it make sense to think that smaller companies who help drive Caterpillar by providing components of its larger parts and final products can scavenge enough resources?
Since it all feeds into the top, if there could be a way to empower those at the lower end of the supply chain, let’s say a small engine parts maker for Caterpillar, why wouldn’t it make sense to encourage this? Let’s say for example this small, hypothetical parts design and manufacturing company could deliver high-quality products at a lower cost to Caterpillar, all due to a dramatic reduction in development and time-to-market periods because of the boost of added HPC capacity or even first-time HPC software and resource capability?
This is what lies at the heart of all of these “missing middle” debates, yet still there are no answers on how to best reach out to these smaller providers of manufactured designs and products when all they really need are the resources. And as you know, these are some very expensive resources we’re talking about here.
While HPC on demand providers are putting themselves forward as the next best thing to an in-house cluster, there are still hefty software license issues to contend with that will still drive up the cost. On the other but related side, there are cloud services providers boasting superior services with a performance hit that won’t (they will promise) be dramatic.
While nothing seems to appeal to most quite like the good old workstation for modeling and simulation tasks and since the GPU revolution is still just in its infancy in terms of HPC resource providers with affordable solutions, one has to wonder how much longer this missing middle in manufacturing will remain lost.
Research in Context
So let’s get back to the Intersect 360 and NCMS research that started this whole conversation in the first place. Actually, let’s back way up…
What is rather unique about the study was that the 321 respondents were not told that the survey had anything to do with HPC. As Addison Snell noted during a presentation similar to the one he gave in conjunction with NCMS in Washington, D.C. the day before, in order to take care of the sticky issue of sample bias, the focus was on technology as a general concept versus the far narrower HPC distinction.
This does mark the study as different from several others that have emerged that are distinctly related to high-performance computing. However, if potential respondents were asked to take the survey, even if there was the possibility of marking an answer “we do not currently use HPC,” they might be far less likely to objectively consider the questions.
As it stands, 80% of the respondents came from the industrial or commercial manufacturing space (with the remaining 20% in supporting roles in academia, trade organizations and the public sector) and those on the commercial end of the spectrum were asked additional questions related to product design and development and to what extent they were deploying available high-end technologies to aid in their efforts, among other related questions.
While the above numbers will do you far more good if you take time to unravel some of the study’s finer points (and the important elements have only been hinted at–there are a number of sub-issues) about the distribution of opinions about securing access to advanced technologies (don’t call them HPC resources if that makes it more palatable, of course) the main point is that there is a combination of general resistance and lack of insight about how these technologies can be leveraged (and to what benefit) for those in that missing middle of manufacturing.
What the research found was that “there is potential, untapped benefit to digital manufacturing technology usage among U.S. manufacturers, particularly small to mid-sized manufacturers. For these companies to get over the hurdles inherent to adoption of advanced technologies, they will seek partners and programs that mitigate risk and help defray costs so they can make investments required to improve their competitiveness technologically.”
Still, what gives some pause is to consider the inferior technology that is driving many manufacturers feeding the supply chain. If we see Caterpillar as a representative example of the power of having access to modeling and simulation, except of the vast scale, it’s pertinent to apply the example of them building a 10-acre facility to test pre-built testable equipment to run constantly for days on end when software might have taken over the task.”
Although companies further down the supply chain don’t have the same sized products or design challenges, this example reverberates—when scaled down, what many of these smaller companies are doing is the cost, time, and resource equivalent of the 10-acre test lot.