Who Benefits Most from Robot Autonomy?

Autonomous robots are among the most likely candidates for the next generation of General Purpose Technologies. These kinds of technologies, practices or standards can affect economic output at the global level because of their ability to be applied to multiple sectors. 

We know that robot autonomy has applications across both goods manufacturing and everyday services. While the broad productivity benefits of newly independent forms of automation can be spectacular, we can expect that no one company or inventor will truly dominate them – instead, each domain will have purpose-built or vertical-specific applications of general autonomy technology and principles which will make the biggest possible impact in those sectors. 

So who really benefits from this, and who benefits most? If you’d like to understand more of what the world will look like as autonomous robots become a fact of life, read on. 

Shareholders & Investors

When new technologies come to pass, it’s ultimately those who take on the risk in investing in them first that benefit most.

However, this isn’t always the case. For instance, it’s estimated that three quarters of venture investments don’t return the initial commitment and 25-30% of venture-backed businesses fail completely. While many businesses may at least return enough to justify their initial investment, both outsized risk and reward are what’s necessary to actually achieve the entirely new level of growth that most venture capitalists are expected to achieve.

At the same time, robotics has long been a challenging sector for venture capitalists because of the common limitations in adapting to different circumstances. Autonomous robots can change this, but they are still restricted to defined scenarios, locations or use cases. As we’ve seen with autonomous cars (despite the many billions invested in them), getting robots to operate with complete independence in totally unconstrained environments (like a city street) is usually a longer way off than even the most patient investors are able to manage. 

Robotics investment has taken off, primarily by the demographic transitions that make productivity growth essential for a high standard of living. Source: Wealth Daily.


Imagine, for a moment, that autonomous robots have become commonplace. What difference would they make? A few can be considered:

  • With autonomy for specific tasks, managers can be certain that tasks are executed with the methods and quality they expect
  • Using data-driven systems, managers can have visibility on both good performance and failures or areas for improvement – without concern for tip-toeing around a robot’s feelings
  • With specialization among autonomous robots (anything from working with delivery personnel to executing tasks in a factory), managers can focus on the support and guidance of their employees, ensuring that they improve their productivity and develop critical skills over time

This sounds like a scenario in which every one of a manager’s most typical headaches is miraculously cured. While, in effect, the most effective companies are thinking of use cases for autonomous robots that optimize a manager’s happiness, what autonomous robots also do is expand the range of who acts and serves as a manager – Robot Wranglers, as CEO Mike Playter of Boston Dynamics would call it. Managers take on risk today in adopting any new technology, but as point-specific applications mature, more risk will come in simply failing to adopt what’s new. 


Autonomous Robots pose a unique set of challenges and opportunities to engineers above all. How can we expect systems to work where autonomous robots are involved, and what failsafes need to be introduced in order to ensure that failures of autonomous systems don’t halt their progress. There are three categories to think about here that are most pertinent to engineers: mobility, manufacturing and public spaces.

Mobility: When we’re sitting in traffic or stuck down a long road after a wrong turn, we often don’t consider the amount of effort required in engineering traffic flow to work as seamlessly and intuitively for humans as possible. When it comes to autonomous cars, designing roads for densification, efficiency and limitations around visual signalling, roadwork diversions and other inconsistent scenarios where autonomous vehicles may not be so quick to adapt are essential. At the same time, roads can be redesigned to accommodate only autonomous vehicles that communicate with one another – meaning that traffic signals, intersections, onramps and offramps may all actually be able to go without many of the design features needed to accommodate humans. At the same time, parking and managing exits and entrances may become a lot more simple as well, since these autonomous vehicles could essentially function more as taxis than personal or family transportation. 

Manufacturing: In the manufacturing space, robots have long been used to optimize the production of dirty, dangerous and repetitive jobs. The challenge here is that robots are usually cost-effective in the most repeatable and high-margin products because those are the sectors where the precision fixturing required to make robot programs effective can be facilitated. With autonomous manufacturing robots, these constraints – as well as the need for continuous production lines and intensive automation integrations – can be reduced because of their ability to respond to demands as they emerge. Working within configurable process constraints, these robots don’t need to follow the mass production practices which still guide so many of the world’s biggest manufacturers, giving them more flexibility and higher productivity than ever before. 

Public spaces: of course, within public spaces, the services we require are the most important. Whether it’s healthcare, education, old age care or other designed environments, engineers can realize cost savings for their clients by improving the flexibility and multi-purpose capacity of these facilities according to the services that can be performed by robots. In one example, autonomous mobile robots can help hospitals centralize and better manage the distribution of medicine and equipment, saving space and increasing the efficiency of use for all their essential goods. This kind of autonomy can also reduce the total human footprint in situations where stuff like – oh let’s “imagine” a contagious virus hopping about – improving the overall outcomes of hospital care while improving the flexibility and creativity of facility design.

Overall, autonomous robots don’t specifically benefit engineers more than anybody else. They might actually increase the need for engineers to rethink our spaces to best optimize around new autonomous capabilities. More engineers is always a good thing for existing engineers, isn’t it?

Engineering robotic solutions has come with known challenges for a long time. Ultimately, sharing and developing new solution sets is the main area of future growth.


Job theft is always an accusation leveled against robots, but that simply isn’t true. Since manufacturing robots were introduced – for example – the number of manufacturing robots and total manufacturing productivity worldwide has increased dozens of times over. What’s more, as consumers the proportion of dollars we spend on goods has halved, while we devote more of our consumption to services that ultimately create even more employment.

Two questions are important to ask about the state of the workforce, however: 1) do people have the skills they need to make a good living and 2) do people have the tools they need to be productive in making their living? In both of these cases, the answer seems to be no, and yet autonomous robots may help change that.

For one, autonomous robots with sufficient flexibility can take over highly specialized tasks that may simply not be as cost-effective for workers to learn from a skills vs pay perspective. At the same time, focusing entirely on a specialized set of skills often keeps people from achieving more generalist work goals that are still valuable and contribute substantially to overall productivity. 

Overall, it’s the lack of automation and autonomy that could actually be keeping workers from making higher wages and experiencing a higher standard of living. While businesses may sometimes be hesitant to invest, subsidies and encouragement to automate could create an uncapitalized profit opportunity that would make workers more scarce in the pursuit of profits – precisely because all the tools except for the workers are in place to enable firms to grow. 

Workers and robots aren’t a zero-sum game, working together enables humans to be more productive and avoid the less pleasant aspects of their job. Source: American Machinist.

Who Benefits Most is Hard to Say

We all fill different roles, we are both members of classes and consumers in our society. What we need to understand is that technology may cause disruption, but it’s a fundamental enabler of improvement and growth in our day to day lives. Would we love to go back before laundry machines and manually wash our clothes, or have someone do it for us? Do we bemoan the loss of elevator or traffic light operators? 

These roles were once a substantial portion of the workforce – the people who filled them were able to move on to better lives. People forget, for instance, that the refrigerator gained market share during the great depression, actually contributing to some of the deflation (in food savings) which caused farmers so much pain. Do we think there was a better time to incorporate refrigerators, or otherwise go back to the old ways? As a society, we must manage the transitions that come, but as a society, we can’t pretend like staying in the same place doesn’t simply mean falling behind. 

With AutonomyOS™ and AutonomyStudio™, it’s never been easier to deploy an autonomous robotic system. Using 3D Perception with AI-based Task Planning and Motion Planning, manufacturing engineers and integrators can configure autonomous robotic systems for value-added processes that allow manufacturers to achieve more consistency and flexibility in production than ever before.

Improving the Quality of Your Industrial Paint Process

Industrial paint quality is a tricky thing. Not so much because reaching precise and accurate application is difficult – nobody’s asking for the Mona Lisa from an autobody shop (ok not “nobody”) – but it’s when you get to the point of painting 100 parts or 1000 that the challenges of maintaining consistency at high quality becomes difficult.

What does this consistency problem come from? There are a few key factors: the application method, the tool used and maintenance, cleaning or changeover required, and the nature of the parts you’re working on in terms of whether achieving a consistent finish is more difficult.

What scenarios could this apply to? Parts with crevasses, unusual curvatures or a unique surface features all can make a consistent finish difficult to achieve with the most basic systems available. By taking advantage of the right technology and approach – whether it’s skilled labor, automated or fully roboticized – achieving a consistent industrial paint quality can be realized through variety of subtle optimizations. 

Painting can be difficult for any metal fabricators because of the variety of parts addressed and varying customer quality requirements. Source: PEP Engineering UK.

Looking at What Your Parts Require

What are some of the most common parts that need painting? They run the gamut but are commonly recognizable in everyday life:

  • Car, bus and truck bodies
  • Structural steel assemblies – bridges, infrastructure and buildings
  • Heavy equipment (earthmoving, construction, agricultural)
  • Medical imaging and software technology
  • Energy equipment (if not simply all those parts at the gas station)
  • Planes, trains (we already mentioned automobiles)
  • Funeral caskets, shipping containers and every metal or wooden box in between

Paint is applied in most of these cases to generate both an attractive finish and to offer long-term protection against environmental challenges or simple weather wearing. In all of these circumstances, it’s not simply large flat paneling or single large assemblies that are painted, but also many small parts which are assembled together after the fact depending on the type of equipment being assembled. 

Furthermore, consistent finish is required because parts must fit together, whether or not your parts hold together well, while customers often first notice the quality of finish before anything else. They are are demanding not only because they expect parts to be visually attractive, but also because the visual quality of that finish will reflect on the final product or service they may offer to someone else. If you want to understand what type of parts fit best with each workflow, check out the next section. 

Painting heavy machinery can be a challenge because parts are usually painted before assembly (due to weight and contours), meaning the variety of paint programs needed is greatly increased compared to unibody painting.

Making Systems Fit Functions

There are three basic orientations towards painting industrial parts that manufacturers of all kinds know today – skilled labor, automated booths and paint robots.

  1. Skilled labor

Skilled labor is the most commonly recognized means for industrial painting. This isn’t true to all sectors, but when it comes to sectors like structural steel and heavy equipment (nominally “high-mix, low-volume” industries) skilled labor is often the best choice because of the changeover and varied shapes or nature of parts, as well as the need to flexibly respond to orders and requests as time goes on. In more mass manufacturing industries (like cars and light duty trucks) robotic painting is the most common way to get things done. We’ll get to that shortly

  1. Automated booths

Automated paint booths are uncommon but still used where large parts need a general and not necessarily consistent level of painting. This can include large flat and structural panels and other parts where a light screen or different shape-perceiving mechanisms can loosely target the paint gun being used to the size or area of the object being coated, but not necessarily to curves or hard edges. Furthermore, it won’t prevent drip – critical to high-consistency and quality finish operations. 

A cartesian-style automated paint booth. Obviously accuracy may be inconsistent, but depending on customer requirements, the quality needed may not be exceedingly high.

  1. Paint robots

Paint robots have been for decades the standard in the automotive industry because of the volume, value and repeatability of those industries. The value of paint robots lies in their ability to consistently execute highly repeatable operations. Where they falter is in their need for programming and precision fixturing. Generating a robot program means that once it is put into production, it is difficult to change, causing the need for precise fixturing during a production process in order to ensure that inconsistencies (or outright process failures) do not emerge as a large volume of parts are processed.

BONUS: Autonomous Paint Robots

Yes, actually, as it happens, the end might be nigh when it comes to the programming and fixturing limitations of traditional paint robots. Autonomous robotics technology is built primarily on the use of 3D perception and AI to see parts as they are in their environment. This means that with the appropriate process model for painting, an autonomous robot can not only generate its own program in real process time – it can also do so in a way that is agnostic of the actual position or orientation of the parts that it’s processing. Because they are able to see parts and generate their own programs, autonomous robots are far more versatile in automating high-mix paint processes than what has been previously achieved.

Autonomous manufacturing robots can apply paint to varied parts – no matter their shape – with maximal consistency, providing the most possible quality improvement for high-mix manufacturers.

Application Techniques, End Effectors, Flow Optimization and Control

With the type of system you want taken into consideration, it’s then important to take into account what type of techniques, end effectors and more you want to apply. Every material has its own strengths and limitations, and paint is no different – it simply depends on what the actual behavior of your material is and if it appropriately achieves your goals. 

If you’re thinking of a manual system, then handheld paint guns are likely to suffice. These are lightweight, easy to manage and require regular but not burdensome levels of cleaning. In this context, reciprocating arms and robots can have end effectors that use purging or self-cleaning functions based on air pressure that reduce the need for overall maintenance. They may also have porous components that provide quick replacement maintenance, but create a cost in replacement. Ultimately, however, for the right type of operation, this cost is far less than actually having to manually clean end effectors on a consistent basis. 

With the appropriate mixing and pressure systems, industrial spray effectors can provide sufficient coverage, accuracy and efficiency for most industrial paint applications. In sectors like powder coating, it is more of a concern to optimize around grounding, part shape, speed and frequency. With industrial paint, most of the trade offs come around pressure, volume and accuracy of operations, which in most industrial cases is generally an easier fit. 

Maximizing Output Quality With Autonomous Manufacturing

For most industrial paint applications, skilled labor is generally required. This is problematic in that – even in parts of the world that we may consider less developed – the willingness of young workers to embark on manufacturing careers has only continued to decline. 

While finding the right engineering and programming staff might be less of a challenge, those people can’t do it all on their own – or can they? With autonomous robots, it becomes much easier to scale the know-how of your most effective team members, eliminating the traditional robotic integration bottlenecks while also realizing greater productivity and improved savings on waste, energy, consumables, rework and general downtime. 

All of this effectively avoids the challenges of achieving a quality finish, while giving you the flexibility you need to address more customers as you grow. 

With AutonomyOS™ and AutonomyStudio™, it’s never been easier to deploy an autonomous robotic system. Using 3D Perception with AI-based Task Planning and Motion Planning, manufacturing engineers and integrators can configure autonomous robotic systems for value-added processes that allow manufacturers to achieve more consistency and flexibility in production than ever before. Contact us for more info!

How to Reduce Manufacturing Labor Costs Without Cutting Headcount

We usually think of automation as “replacing” workers. The truth is, most forms of automation simply augment the labor that we have today. ATM didn’t eliminate bank tellers, and nor will robots really eliminate the need for a skilled manufacturing workforce.

What ATMs instead did was rid bank tellers of simple tedious transactions – transactions which weren’t necessarily more productive when done by a person and ultimately reduced their relative value to their employer. Instead, ATMs handle the tedious or predictable stuff, tellers handle the special cases (which – big surprise – there are still a lot of), and banking has never looked back. 

So, when you’re thinking of how to reduce manufacturing labor costs (with or without cutting headcount), the most important approach to take is to consider how you can augment the productivity of your workforce by eliminating unnecessary excesses in your production process. 

The added labor costs you may be thinking of are:

  • Frequent overtime due to falling behind against production demand
  • Constant rework causing either overtime or excess hours
  • Eliminating duplication of hours due to quality issues
  • Improved safety and wellness protocols that reduce total insurance costs
  • Reducing turnover by creating an environment that keeps employees happy

Ultimately, some or all of these steps don’t just reduce the relative costs of labor to your overall production, but they will increase your productivity, profitability and can also increase the proportion of your labor costs that actually go to employees.

Eliminating Frequent Overtime

Struggling to keep up with demand is actually a pretty good problem to have, but if it goes unaddressed it can still compromise your business. Part of the challenge here is that when demand increases faster than your ability to train and employ new skilled employees, you fall behind even further, compromise on quality or have to raise your prices – putting you in the sights of a competitor who may not have those problems. 

So, how can you add flexibility to your manufacturing process that improves your “surge capacity” while reducing your fixed costs? As it turns out, autonomous manufacturing systems can enable high-mix manufacturers to finally realize some of the same benefits from robotics that mass manufacturers have long known. 

These include repeatability, durability and consistency in operations, while being able to function for one shift per day or 24/7/365 with limited incremental labor throughput. At the same time, these machines enable your existing skilled workforce to avoid tiring, repetitive or dangerous tasks and further avoid overtime because their regular productivity is that much higher. 

If you want to understand the hidden costs of going without automation, click here. 

Reduce Rework to Limit Labor Overruns

One of the biggest challenges for manufacturers for the last few years has been to find capable workers to add second and third shifts to their production line. In many cases, the absence of skills, competency or ever the willingness to show up has meant that it simply hasn’t been profitable to meet demand by adding new shifts, because the work of those shifts actually requires so much rework that it makes serving that demand unprofitable.

In many of these circumstances, skilled, experienced employees and managers have gone the extra mile to meet what they could, and we know that during the pandemic durable goods demand in particular has surged. As time goes on, the money here may be good, but ultimately this is likely to add to the labor costs of your most skilled and experienced workers, and quite possibly work them into an early retirement.

With new machines and autonomous systems, these workers no longer have to do the work themselves. They can instead work from oversight positions while they ensure that production needs are met and the most basic aspects of your process are respected. At the same time, this form of “lights out automation” can reduce rework – even in high-mix environments – because it doesn’t require the same instruction, care and attention that skilled workers do. With autonomous robots, every movement is infinitely repeatable, meaning the unexpected whims of inexperienced workers will limit the possibility of rework in the first place. 

Eliminating Duplication of Hours Due to Quality Issues

This adjustment is a bit like the one above, but with a little caveat. Do you have extensive processes or quality assurances that exist in order to avoid added costs on orders? Do you have multiple employees doing the same thing on the same production line because you simply cannot afford to get anything wrong? Autonomous machines effectively eliminate these excessive process and actually improve the quality of your orders. 

As it happens, the relative labor costs in manufacturing have gone up significantly, meaning these kinds of processes may not be that uncommon. Since 2010, in fact, unit labor costs are 20% higher on an indexed basis – even while total wage share trends towards a 60-year low. While commodities have been cheap in that time, manufacturers have simply seen their cost structure shift towards labor without the increase in productivity that actually benefits both labor and employers. Duplicate processes or repetitive quality checks are a huge component of this – they make jobs more repetitive, less attractive, less productive and keeps them from finding ways to improve their performance and earn more from their output. 

Improved Safety and Wellness Protocols That Reduce Total Insurance Costs

When a person gets hired, they collect their wage and benefits. When a firm hires somebody, they pay those wages and benefits, additional state mandated benefits, employment insurances, payroll taxes and more. Not only do many of these policies perversely discourage employers from hiring people when they need them – it actually makes firing employees more attractive and relatively easier compared to the total costs associated with dismissing someone. In fact, these policy sets ultimately cut the prospective wage increase by half and the annual wage increases of incumbent employees by up to 10%.

Health and safety costs also impose even more of a burden on employers and employees – particularly when it comes to labor costs that employees only benefit from in that it keeps them safe. A study by the Institute of Work & Health showed the average Ontario manufacturer spends more than $1500 per employee on health and safety initiatives. In the United States, injuries cost manufacturers nearly $8 billion in 2019, with nearly half of that being Muscolo-Skeletal in nature. 

Acute injuries are not the only risk to the workforce: one study in Britain showed that fully a third of manufacturing workers suffered from conditions like heart disease, hypertension, diabetes and asthma, while these conditions on average increased the occurrence of acute injuries between 12 and 25%. In many cases, the stress or environmental hazards of these jobs can be contributors to the occurence of these chronic conditions as well.

With autonomous manufacturing systems, you can look to remove workers from exposure to a variety of health and safety risks and ultimately work to eliminate those added costs to skilled labor, while further improving the productivity of your most experienced employees and empowering them to do more.

Reducing Turnover by Creating an Environment That Keeps Employees Happy

While employers can do everything they can to keep things interesting in the workplace, the true costs of tough jobs ultimately fall most heavily on the employees who do them. 

At the same time, as committed as some may be to simply working hard, employees of all stripes are willing to take less if they find their work more meaningful. Most manufacturers produce essential goods that make a key impact on daily life – something employees can feel good about. But what about following orders? What about those days that never seem to end?

All of these aspects of a difficult or overly “authoritarian” organization can cloud the more meaningful aspects of working in manufacturing, while also reducing the engagement employees feel in the workplace. Getting away from this approach is essential to getting more done and – often – equipping employees with the right technology can make them happier to deal with whatever comes. 

With AutonomyOS™ and AutonomyStudio™, it’s never been easier to deploy an autonomous robotic system. Using 3D Perception with AI-based Task Planning and Motion Planning, manufacturing engineers and integrators can configure autonomous robotic systems for value-added processes that allow manufacturers to achieve more consistency and flexibility in production than ever before. Contact us for more info.

How Robotics Integrators Can Use Autonomous Robots To Grow Their Business

Industrial robot integrators are like the special forces of industrial automation: highly skilled operators who parachute in when a big-name company needs to reinvent their process for maximum efficiency.

This has meant steady streams of income and stable business for a long time, but that’s only without considering what integrators may be missing out on: the high-mix market. More than 70% of North American manufacturers are high-mix – that is, working on more than 100 batches with parts numbering less than 1000 per year. For these manufacturers and the integrators who don’t serve them, adding robotics simply isn’t cost-effective for the amount of programming required to adequately address this potentially huge market.

Autonomous robots can change this because they respond to manufacturer’s needs in real process time, eliminating the changeover constraints that plague traditional robot programming. With this new ability to address the high-mix market, robotics integrators can finally grow their business and improve efficiency in a variety of new ways.

Robot Integrators Can’t Practically Address the High-Mix Market Today

Today’s high-mix manufacturers can’t benefit from most traditional robot integrations. Some are incorporating robot HMIs or machine tending use cases, but in reality the market for this is limited and doesn’t offer enough value-add to attract the highest level, well-known robotic integrators that are familiar with high throughput industries like automotive and consumer electronics.

As such, getting over this programming cost requires an understanding of the cash flow and capital expenditure effect of autonomous robots. Put most simply, the use of autonomous robots is among the most cash-flow-positive choices a high-mix manufacturer can make, and this permits integrators to rapidly distribute their knowledge and services at higher margins while eliminating one of their biggest time, money and human resources cost: robot programming. 

Why is this the case? Because autonomous robots require no manual or code-based programming in order to become fully operational. In these circumstances, integrators can rely on their savvy to more rapidly deploy intelligent machines and focus on collecting profits from cost-savings on installations, while their customers will be grateful to embark on a long term relationship with expert robot integrators than can guide and maintain their systems in the long term. 

Finding ways to address the high-mix market has been the white whale for many robotics integrators. Autonomous technology means no more “nibbling around the edges”.

Integrations Are Slow, One at a Time, and Often Don’t Match With Control Systems

Compared to the current landscape of robotic integration, why would this model be beneficial? There are a few reasons:

  1. It’s not incompatible with the old model, it’s actually entirely complementary. Most of the work in preparing mass manufacturer integrations is in programming and preparation. With autonomous motion generation, most of the work is in installation and validation – while it’s less work overall, allowing you to create more specialization among your team.
  2. High mix manufacturers have higher tolerances on a customer by customer basis than many high-precision, highly demanding mass manufacturing scenarios, making it a more forgiving sector to work with where payback is sufficient.
  3. Autonomous motion generation isn’t exclusive to high-mix, it’s just where it’s most beneficial. As mass manufacturers trend towards mass customization of discrete goods, the avenues for autonomous robotics will only grow in order to adapt to the convergence of styles between high and low mix.

In the simplest possible terms, autonomous robots offer a new integration model that is simpler and more effective than previous robotics or automatic machine control workflows. At the same time, it permits diversification for integrator firms that don’t just allow them to grow more deeply into customer organizations, but also across more varied industries.

In recent years, the core customers of robotics integrators (automotive and electronics) have begun to lag. Autonomous Robots offer a new opportunity to grow in a diverse array of industries. Source: International Federation of Robotics.

Changing Workflows Are Becoming More Commonplace in Manufacturing

Mass manufacturers only update their workflows every 5-7 years, while materials handling flow is subject to more frequent and flexible change and in a high mix workspace – if there is any defined flow at all! This requires new interpretations of the role of robots because adapting to customer needs ultimately means that any and all productions will trend towards a batch size of one.

While the actual realization of this is far in the future, preparing for the transition then will only prove too late. At the same time, autonomous manufacturing principles can be applied more broadly to all types of machines and verticals. Integrators who avoid getting caught on their back foot will have the opportunity to develop new and differentiating experiences that will only increase their demand – and profitability – in the long run.  

Building a Reliable Customer Base Starts With Growing It

It’s never too early to start growing, but if you’ve got a strong bifurcation between your most and least experienced engineers, adding technologies that allow both to ultimately increase their productivity and work volume without creating more headaches creates fundamental efficiency in your business.

By attempting to grow your customer base now, you prepare the ground to work in the long term. While the only constant these days seems to be change, robotics integrators can get ahead of the curve by thinking of new ways to use their expertise in deploying autonomous robots – whether it’s for manufacturing, services or beyond!

With AutonomyOS™ and AutonomyStudio™, it’s never been easier to deploy an autonomous robotic system. Using 3D Perception with AI-based Task Planning and Motion Planning, manufacturing engineers and integrators can configure autonomous robotic systems for value-added processes that allow manufacturers to achieve more consistency and flexibility in production than ever before. Contact us for more info.