Going Green With Manufacturing: The Path Towards Sustainable Automation

There’s no question we’re in the midst of a climate crisis. As officials from all over the world struggle to create a plan to mitigate the effects of climate change, the causes are still points of contention. The beginning of the COVID-19 pandemic paved the way for a brief but impactful decline in carbon emissions. Once the world reopened, however, it brought climate challenges back to square one. The pandemic also highlighted a stark drop in available goods due to a labor and supply shortage in which the effects are still being felt. Factory automation is a solution for the lack of labor, but how sustainable is it? At a glance, it might be easy to write off automation as energy-consuming, but this doesn’t tell the whole story.

Like most technologies, automation requires careful attention and planning to maximize its efficiency. If left unchecked, it could lead to different forms of waste. For example, in paint spraying procedures, human labor will account for a certain amount of waste. When fully autonomous robots execute that same task, the waste should be greatly reduced. If this autonomous robot is using iffy software or is poorly programmed then it could waste even more paint all while consuming large amounts of energy to complete a job in mediocre fashion

How Bad Can It Get?

The International Institute for Sustainable Development (IISD) developed a board that listed the best- and worst-case scenarios for the environmental impacts of automation technologies. The IISD breaks down different categories of automation categories and lists the impact each sector has on the environment based on greenhouse gas emissions, resource usage, and ecosystem usage.

The worst-case scenarios here are predictable. If left unchecked, the environment could have significant adverse consequences in fields such as autonomous transport and the Internet of Things. Essentially, if resources aren’t properly managed, then it’s only normal that waste could become an issue.

Resource management is essential to the preservation of the environment. The chart predicts that in a best-case scenario, artificial intelligence – along with autonomous transportation and the Internet of Things – would have a “significant positive impact” on the environment. Again, these are purely predictions from a single source, but they aren’t unattainable. If advanced technologies, like nuclear fusion, can advance to a point of universal adoption, then these predictions will be closer to reality.

Figure 1. Showing a best- and worst-case scenario of greenhouse gas emissions, resource use, and ecosystem use for various sectors where autonomous systems can be implemented (via Dusik et al.)

Manufacturing and Its Impact On the Environment

In an article published by Al Jazeera in 2021, they state that “manufacturing – especially of the cheap construction staples steel and cement – accounts for about a third of global greenhouse gas emissions.” In the United States, manufacturing processes consist of 25% of the country’s energy use. Manual methods of manufacturing are quickly becoming archaic and will require an overhaul towards automation to reduce greenhouse gas emissions.

Inefficient technology is one factor behind the world’s overconsumption of technology. In 2013, a report published by the International Energy Agency (IEA) estimated that the world’s 14 billion online electronic devices had wasted around $80 billion every year. Though the IEA lacks an update nearly a decade later, it’s fair to assume that this number hasn’t gotten any better.

New technologies are hoping to make energy consumption all the more sustainable with different parties advocating for different methods such as solar-powered electronics and the aforementioned nuclear fusion. Neither of these forms of energy is ready for widespread use – in fact, nuclear fusion is still very much in its infancy – but that doesn’t mean advances in other sectors won’t help mitigate the effects of climate change.

Figure 2. Coal- and oil-based electricity generation cause the most greenhouse gas emissions while hydro, wind, and nuclear all have minimal impact (via Let’s Talk Science 2020).

What the Research Says

A research paper titled “A global horizon scan of the future impacts of robotics and autonomous systems on urban ecosystems,” written by a number of authors including Mark A. Goddard and Zoe G. Davis, detailed how exactly a robotic autonomous system (RAS) could affect the environment down the line. While they touch upon the ecological benefits of factory automation – more on that later – they also specified how automation could benefit entire cities and ecosystems.

In short, automation could lead to better use of land, especially in dense cities, like Dubai, which could lead to less space being used for transport infrastructure. They predict that if automation becomes widespread, then fewer people will need cars, paving the way for reduced roads, car parks, and driveways. They add that automation in buildings could regulate energy consumption and reduce heat loss.

With these services becoming more eco-friendly, “RAS will reduce human-nature interactions by, for example, reducing the need to leave the house as services are automated and decreasing awareness of the surrounding environment while travelling.”

While the research goes far more in depth about topics such as managing invasive species and biodiversity, it’s clear that, if properly implemented, RAS could be a game-changing service provided to the world.

These long-reaching effects are not just for cities and communities, they will also immensely benefit manufacturers who will be able to both augment productivity and reduce their carbon footprint.

Considering a sustainable factory will not only benefit the environment, but will benefit your savings in the long run

How Sustainable is Automation Really?

The world of automation is vast. There are many different ways an autonomous system can help the environment. Robots can be programmed in empty fields to plant trees. Self-driving electric cars will one day be commonplace, not only eliminating the need for gas refuels but also greatly reducing noise pollution as cars will be mostly silent and obnoxious honking from irritated drivers. While these are more day-to-day and simpler options, enabling autonomous robotic systems in manufacturing plants can also go a long way toward reducing their carbon footprint. Here are some examples of how automation can contribute to the fight against climate change:

Reduced Energy Consumption: Fewer humans in the factory means you can downsize and use less space in the factory. With less space means heating and air conditioning costs will decrease. As well, autonomous robots will take less time to complete a task, therefore using less energy.

Reduced Waste: With human labor, it’s normal to expect waste when performing certain tasks like paint spraying or powder coating. A fully autonomous robot will know exactly how much of each resource to use, minimizing waste. It will also reduce reworks, touch-ups, and complete revisions.

A reduction in both energy consumption and waste will not only benefit the manufacturers’ costs but will also contribute to a substantial reduction in greenhouse gas emissions, eventually minimizing a factory’s carbon footprint. As well, if new forms of energy, like nuclear fusion, become usable, then it will improve a factory’s level of sustainability as well.

Figure 3. Greenhouse gas emissions (GHG) from industry make up for nearly a quarter of the U.S.’s total GHGs in 2020, signifying an urgency to move towards sustainable forms of energy. (Via EPA)

Getting There: The Road to Sustainable Manufacturing

The world is slowly but surely taking steps to ensure our collective carbon footprint declines. With autonomous robotics systems, manufacturers can directly contribute to that. While it might not be the sole reason manufacturers will switch to a fully autonomous robotics system, they can find some solace in knowing that adopting these systems won’t only be beneficial to their company, but to future generations who depend on the Earth’s wellbeing.

 

With AutonomyOS™ and AutonomyStudio™, you can move towards a fully autonomous robotics system that is as practical as it is ecological. 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 to learn more

ROS: How Well Does it Address Manufacturers’ Needs?

The first time you see a robot perform a specific action, it can be quite awe-inspiring. Seeing robots like the Personal Robot 2 (PR2) clean tables and fetch drinks is certainly a sign that the future is now. Though the concept of having a robot understand what it needs to do is fascinating, how does it actually know what to do and how to do it?

There isn’t a universal answer to this. Robots have, for the longest time, been able to simplify some elements of programming thanks to robotics middleware such as Urbi, OpenRDK, and ROS. Though these platforms all offer different advantages and limitations, ROS stands out from the crowd thanks to one thing: its open-source nature. ROS’s repository is free to access, meaning that anyone who’s interested in programming robots can start with this middleware for free.

How ROS Came To Life

The Robot Operating System, more commonly known as ROS, started as a project at Stanford University by Keenan Wyrobek and Eric Berger. During the time in grad school, the duo had noticed their peers were wasting way too much time trying to program robots – Wyrobek even heard people say they had spent four years trying to make a robot work with no success – and decided to create a universal, open-source platform that would allow developers to share their knowledge.

“People who are good at one part of the robotics stack are usually crippled by another[…]” said Berger in an interview for IEEE Spectrum. “Your task planning is good, but you don’t know anything about vision; your hardware is decent, but you don’t know anything about software. So we set out to make something that didn’t suck, in all of those different dimensions. Something that was a decent place to build on top of.”

 
Since 2018, robot installation numbers have fluctuated namely due to the pandemic causing significant changes to the labor market. Graph via IFR.

In a separate guest editorial by Wyrobek for IEEE Spectrum, he specified that he had seen developers spend 90% of their time re-writing other people’s codes, with the other 10% allocated to innovating. Afterward, Wyrobek found donors to help fund the building of 10 robots and shipped them off to 10 different universities in order to have teams of software engineers build developer tools that would allow other developers to innovate and build on the software. Essentially, Wyrobek was tired of seeing developers attempt to reinvent the wheel each time, so he and Berger wanted to simplify everyone’s lives.

How You Can and Can’t Use ROS

On its own, ROS can’t really do much. There are vast libraries of packages included in the ROS repositories, but ROS itself only provides the canvas on which developers can program and execute their desired tasks.

Using ROS, developers can build the three main components of a robot: the actuators, sensors, and control systems. These components are then unified with ROS tools, namely topics and messages. The messages are used to plan the robot’s movement and, using a digital twin, developers can ensure that their code works without having to actually test it on a real robot.

These messages can travel throughout ROS using nodes, which is essentially an executable file within a ROS package. Each node is registered to the ROS Master, which sets up node-to-node communication. All this technical information to say that programming is an essential part of ROS. Developers and programmers have to code each action they want the robot to perform. Without ROS, this would be a daunting task, since developers always tend to reinvent the wheel. With ROS, however, this is a much simpler task thanks to its open-source nature.

ROS allows developers to simplify the job by using nodes to register requests to the robot and how exactly it will respond to them.

ROS succeeds in providing a canvas for its developers due to its large community size. While other robotics middleware, like URBI, aim to solve the same problems, there was one key difference in their success. URBI was an expensive software to license, and while developers still used it, it failed to build a community similar to ROS’. With a large community comes more tools for developers to share. Consequently, more projects could be pushed to completion in record time. 

In fact, the robotics middleware has become so widespread that, as per Bloomberg’s reporting in 2019, 55% of robots shipped by 2024, over 915,000 units will “will have at least one ROS package installed, creating a large installed base of ROS-enabled robots.”

Additionally, Lian Jye Sue, Principal Analyst of ABI Research claimed that “the success of ROS is due to its wide range of interoperability and compatibility with other open-source projects.” The more ROS expands through community-based packages, the more adoption rates for ROS will climb in the future.

ROS’ free entry point allowed developers from anywhere in the world to start tinkering with different projects and upload them to ROS’ repositories whenever they feel comfortable with its status or if another developer wants to take a chance and try to improve upon it.

A look at ROS' user interface running on a UBUNTU system (Image via ROSIndustrial)

The Limitations of ROS

When things are free, they tend to have some serious trade-offs. For a project with the breadth and depth of ROS, it’s understandable that it has its limitations. Developers aren’t paid when they upload their packages on ROS’ repositories, nor are they compensated for keeping them updated. Updates to the ROS platform are done regularly, but they rarely, if ever, increase the range of tasks it can accomplish. As stated earlier, open-source middleware like ROS is built to help, not reinvent the wheel.

While ROS can do a lot, its limitations can severely affect a company trying to think outside the box or simply trying to narrow down the effectiveness of its product. One of the main downsides of ROS is the potential lack of updates for certain packages. If a certain company has been working on a package but the project for which the package was made is nearing its conclusion, then updates afterward will become scarce or non-existent. The packages are left to die and can become obsolete quickly. If other developers are using these packages, then their product might suffer if bugs arise with no one to patch them.

Another area in which ROS suffers is its lack of compatibility with computer operating systems – it only works on Ubuntu. (Its successor, however, works on Windows and Mac as well but ROS 2 is far from a finished product and doesn’t offer the same consistency as ROS.) Ubuntu is not a hard real-time operating system, which means ROS could become obsolete quickly depending on industrial robotics needs. As the middleware uses more power and space, there’s no guarantee of real-time control.

Finally, ROS lacks support for micro-controllers and embedded chips – it has to run on a computer. The only real alternative for this is to run ROS on Raspberry Pi (and similar type) boards.

Though the number of flaws and limitations of ROS isn’t necessarily high, they are impactful. Still, if a company has a more narrow and focused idea of what needs to be done, then they should be mindful of these caveats. A platform like ROS was never meant to please everybody, but for a company with simple goals or for a student trying to acclimate themselves to the world of robotics, ROS can provide a solution.

Who Uses ROS?

According to ROS’ website, hundreds of companies, from startups to Fortune 500 enterprises, have downloaded over 500,000 different ROS packages for use on their projects. One Canadian company, in particular, succeeded in using ROS to develop their robots. Clearpath Robotics, founded in 2009, develops several robots based on ROS and are programmable using ROS right out of the box.

One of their most popular ROS-powered robots is the Jackal, an unmanned ground vehicle that can autonomously drive itself around a multitude of different terrains. It’s an entry-level robot, but one of the most widely used ROS-powered vehicles at the moment. With over a decade of success and usability with ROS, Clearpath Robotics is even making the switch to ROS’s successor, ROS 2, which aims to fix all of ROS’ limitations. 

 
Clearpath Robotics uses ROS and ROS2 to ensure that their deployed robots continue to develop and execute complex processes.

But it’s not just Clearpath Robotics using ROS, companies like Fetch Robotics and TurtleBot use the middleware to fill their different needs. Where the former focuses on developing robots designed for warehousing, the latter develops inexpensive, personal robot kits made more for enthusiasts and researchers, rather than whole solutions for a given industry. 

The versatility of ROS can benefit a myriad of different companies in different industries, but it’s not quite the world-changing plug-and-play solution it aims to be.

No matter how a robotic system is configured, most often an HMI will be required to make it easy for operators to manage - ROS doesn't necessarily make that process easy, however.

Enter the World of AutonomyOS

In contrast to the open-source middleware that is ROS, there exist a plethora of proprietary platforms designed for more specific uses. Omnirobotic’s AutonomyOS™ is a middleware meant to simplify and widen how robots are being used. While they both aim to achieve similar results, AutonomyOS™ flips the script by removing the need to code – something that still drives ROS.

By removing the lengthy coding process, AutonomyOS™ allows better resource allocation. Gone are the days of spending countless hours trying to find the perfect code to make the robots execute the desired tasks. The logical question to ask after reading this is “How does it work if no one is required to program it?”

Before the robot executes its actions, it needs to know what object it will be working on first. In order to analyze the object, it must first pass through a set of 3D perception cameras that will digitally reconstruct it and make it visible with AutonomyStudio™, the integrated development environment that allows for the configuration of a system in a virtual space. Though 3D perception can be costly, Omnirobotic enables integrators to deploy 3D cameras using HDR-enhanced sensor fusion, effectively eliminating the need to adjust camera parameters.

With AutonomyOS™, setting up the behaviors of the robot is essential to executing a task. That means no more wasted time on programming movements.

Once the reconstruction is complete, that’s when AutonomyOS™ shines the most. AutonomyOS™ includes a built-in task planner that can interpret any process model and can plan the desired motion to execute the tasks at hand. Using HTN planning, scenario exploration, and behavioral patterns that the end-user can design themselves, AutonomyOS™ can convert the specifics of the object’s part positions and overall geometry into usable toolpaths.

When the toolpaths are ready, AutonomyOS™ can then generate a proper motion for the robot to execute the necessary actions. Several elements are considered when planning out the proper motion, such as managing collidable spaces, avoiding singularities and joint pressure, and streaming motion through a robot controller for real-time production workflows.

Where ROS Can't Compete

AutonomyOS™ can be primarily used by High-Mix manufacturers for a variety of different applications like paint spray processes, welding, and sanding. What is “High-Mix” Manufacturing? It is generally defined as any manufacturer or production that processes more than 100 different SKUs in batches fewer than 1000 each year – basically, a lot more variation than mass manufacturing.

For AutonomyOS™ to analyze and understand the task it needs to execute, it just goes through the steps listed in the previous section and, well, does what it needs to. ROS, on the other hand, would have to be programmed to understand the shapes and technicalities of each piece it needs to work on.

With a good set of behaviors, AutonomyOS™ can execute a large number of functions

Let’s say a factory needs to paint over a batch of items – say stools, desks, and drawers. Let’s also presume that there are at least 5 different models of each item. If you use ROS to get a robot to paint over them, then you’d be required to program the robot to understand the shapes and sizes of each item, as well as to go after odd forms and intricate spaces to maximize the surface area onto which the robot is painting.

AutonomyOS™, though, will execute these tasks after having analyzed the items with its 3D perception cameras. Then, using AutonomyStudio™, the end-user can set up the appropriate behaviors to ensure that programs will be properly executed – and this before the robot has even begun moving.

All Good Things Have A Cost

ROS has its fair share of uses. Without repeating what was listed above, it’s clear that, up until a certain point ROS can help develop automated systems. Who it helps is more important than how it helps however. Its limitations are succinctly explained above, but it can be especially useful for a company with limited resources and funding to get their feet wet with automation. Given its free entry point, ROS is more of a learning software than a software that can solve a plethora of manufacturing problems.

AutonomyOS™ doesn’t share the low-cost entry point but its uses far exceed that of ROS. As well, unlike ROS packages, AutonomyOS™ won’t become obsolete because a developer has stopped working on their project. AutonomyOS™ has a monthly subscription fee but with that comes a platform that continues to grow, enabling support for more machines and robotic systems far into the future.

ROS vs. AutonomyOS™: A Uneven Battle

AutonomyOS™ expands the scope of what a robotics software can do for manufacturers. That doesn’t mean ROS is bad, it just means that, as free middleware, it limits itself given that there are no developers paid to create new packages. It’s a community-driven project that, even with constant updates, can’t revolutionize the robotics industry. AutonomyOS™ is more advanced in nature, but is also for those who are ready for full robot automation in their factories.

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 to learn more!

Are You Really Ready For Factory Automation?

As automation begins to saturate the manufacturing industry, it’s become increasingly clear that it holds several benefits over traditional human labor. These benefits are no secret either – countless publications and businesses have posted articles over the years explicitly detailing the advantages of factory automation. Though it’s clear that the pros outweigh the cons, automation isn’t necessarily a plug-and-play solution. 

There are several factors that will impact whether or not you should lean into factory automation. These factors include whether existing technology can actually help you automate your targeted process, what kind of flexible automation solutions are already available, or where you can find inspiration from unique forms of automation that may in fact help improve your own application or targeted project. 

Like any major business decision, it’s important to weigh these factors to make sure that automation will better serve your business and if taking the first steps is feasible in the near future.

What Can and Needs to be Automated

Firstly, it’s important to ask yourself what process you want to automate. Naturally, not all automation processes are simple turnkey solutions. Decades ago when automation began to be broadly incorporated in the automotive industry, the nature of automation was different. The robots had a planned programmed set of paths and moves to make in order to repeat the same task over and over again.

Cars don’t change components suddenly, therefore the automation is – relative to other industries – simple. Though the automotive industry largely benefits from automation, they only represent a sliver of all manufacturing and not every sector can benefit from automation in the same way.

Automation for High-Mix manufacturing environments doesn’t necessarily work the same way as it would in the automotive industry. Certain processes can’t be executed by doing the exact same task over and over again. Some processes, such as powder coating, paint spraying or welding, require some planning to automate with each and every cycle.

What is “High-Mix” Manufacturing? It is generally defined as any manufacturer or production that processes more than 100 different SKUs in batches fewer than 1000 each year – basically, a lot more variation than mass manufacturing.

For example, let’s say you manufacture tables, but your existing paint process is slow and produces a lot of waste and rework. In traditional automation, if your tables are all the same, you could use a robot. If your tables vary in size, shape or other factors, then you would need the right software and peripherals to manage that variation and still improve upon your existing process. Put simply: if you have no variation, you’re probably already using robots and other forms of automation. If you have a lot of variation, it’s possible to automate, but new solutions must be considered.

Robots and automated machines aren’t the only factory automation solutions available today – resourceful manufacturers can find plenty of software and equipment to support more flexible systems.

Can I Even Automate My High-Mix Production?

When considering factory automation, which is a necessity today, many High-Mix manufacturers are losing hope. Maybe you’ve tried to install a new machine or a robot but the part variation you see has always led vendors to tell you “automation isn’t for you”.

For the longest time, that has been true. Most manufacturers have a level of part variation that qualifies as “High-Mix”. If you make something in metal, wood, plastic or other discrete end-use materials, it’s most likely that traditional automation is too rigid and specific for the amount of change and variation in structure that your plant sees.

If you’ve always been told “no” by automation vendors, robot manufacturers, or the typical automation provider who simply doesn’t believe that it’s possible to automate your production processes, then fret not – there may be another way! Today, manufacturers can actually deploy flexible automation or even autonomous systems that can adapt to the actual variation in your production – or at least be easily trained to change when change emerges. After all, as a High-Mix manufacturer, change truly is the only constant.

In High-Mix environments, not everything will be the same, so you may be curious as to how the technology works. With technologies like AutonomyOS, it becomes easier to envision a shift to automation – even in High-Mix.

A Brief Historical Analysis of Flexible Automation

Before jumping into the technical aspects of automation, it’s worth noting how manufacturers grew to adopt automation.

In 2003, engineers Francesco Jovane, Yehuda Koren, and C.R. Boër, conducted a study outlining the progressing needs in manufacturing for flexible automation. Granted this study is nearly 20 years old, but the findings in this academic essay still ring true despite substantial technological advancement since.

Going back to the 1960s, shoe manufacturers shifted from fully manual labor to machine-aided labor. In the 1990s, society’s desire for custom shoes increased leading European manufacturers to push for an increased presence of automation. Customization became so popular that these consumer wants “became the centre of research activities in the footwear sector.” In fact, a flexible automated pilot plant for mass customized shoes was installed in Italy as part of the Italian National Program for Innovative Production Systems. While this was obviously an early attempt at flexible automation in manufacturing, its success meant that more innovation would have to come from larger projects adopting this style of manufacturing.

Later in the study, Koren and Boër explain a survey that accounted for several manufacturers across the United States and Europe, though they are not named. The manufacturers in question had already implemented a form of flexible automation and were asked about its type, their experience with the system, and the most relevant future directions of development.

They noted in their findings a split between those who had benefited from flexible automation and those who didn’t. However, raw statistics don’t tell the whole story. Those who didn’t benefit from automation were found to have not understood the implementation and use of the systems properly. The two writers specify that “the users who were more careful in the analysis of drivers-enablers were the most satisfied with the Flexible Manufacturing Systems.”

In short, as flexible manufacturing became more commonplace in the early 2000s, manufacturers were found to benefit from it with the caveat that they understand how their systems work and how to take full advantage of it. With that being said, it’s important to understand what needs to be automated in your manufacturing plant.

Productivity Isn't What It Used Be

When deciding for or against factory automation, it’s important to ask yourself how your business is tackling the shifts in productivity that have beset the manufacturing industry. One of the most common pain points within the industry is the recent exodus of employees towards different industries. With a startling lack of youth entering the manufacturing industry, the majority of current employees consists of those either nearing retirement or those in too deep to change directions. 

Without new employees to take the mantle as older employees retire, there will be a lack of knowledge transfer to the few younger workers entering the workforce. There won’t be any older mentors willing to teach the younger generation the tips and tricks of the trade.

Moreover, the older generation’s productivity will begin to lag as they age. Normally, this would be balanced out by the younger generation’s eagerness to work, but due to the lack of mentorship from the veterans to the rookies, their productivity is stagnating as well. The result of that is an increase in bottlenecks in the production lines.

Even if your business has suffered minimally from this phenomenon, it doesn’t mean it’s necessarily out of the picture in 10 or 20 years. Take a look at the age ranges of your employees. Even if the majority of them are in their 40s, but younger ones remain scarce, the productivity decline is inevitable.

If you’ve noticed – or even just begun to notice – these trends in your business, it may be worthwhile to take a step back and evaluate the future of productivity within your manufacturing business. Planning for automation doesn’t take a couple of days. It can be a lengthy process and as time continues, productivity led by humans may take a dip, which will further necessitate automation.

When automating your factory, there will be a learning curve and an adjustment period that may seem daunting. Even when recruited at a lesser rate, new employees won’t have as arduous jobs. Though you would still require them to operate the robots and their accompanying software, the burden of repetitive tasks will be lifted off of their shoulders. Moreover, morale could see a lift as employees won’t necessarily be burnt out by the end of the day.

If you’re starting to see the writings on the wall, it certainly would not hurt to take a look at automation options.

How Some Rise to the Challenge

Of course, several companies have already taken the plunge toward flexible automation and have already seen success with its implementation. Fizyr, a computer vision company located in Delft, noticed the supply chain disruption during the pandemic and developed a platform that would allow robots to autonomously take on tasks such as item picking, palletizing, truck unloading, and more.

Fizyr as a company doesn’t build or program the robots. However, it does assist in their automation tasks with their software that they describe as plug-and-play. Essentially, the vision software, using 3D cameras, allows robots to perceive the different sizes of the packages needing to be moved. With the variation in sizes in mind, the software would then relay the information to the robot which would then know what method of grasping it should use to make sure the items are being handled with care.

Given that not all boxes are made equally, Fizyr’s platform facilitates some of the longest and most mundane processes by allowing the robots to handle the heavy work. And this isn’t just a case of having a robot perform the same actions on a fixed schedule every day – with different sizes for each box it’s scanning, it’s processing the best method possible.

Based on Fizyr’s success, it’s not impossible to envision a future where your warehouse has automated a portion of your daily tasks. Whether it’s fixed, flexible, or fully autonomous, there’s a solution for your automation needs.

Being Ready For the Cost of Factory Automation

If you’re looking for efficient factory automation, it’s probably because you intend on saving more money over a long period of time. Replacing skilled manual labor with autonomous robots will guarantee that, however installing them and pairing them with the right software will still come at a cost.

Naturally, buying or renting a robot isn’t always cheap. Typically, automated robots vary in price depending on their model, release date, and capabilities. Prices can start at around $25,000 for used models but that’s only for the robot itself. The accompanying software and integration are an added cost that can also fluctuate depending on the provider of the software. Though these prices aren’t set in stone, they aren’t particularly inexpensive either. 

These costs may seem daunting at first, but it becomes easier to rationalize them when you consider that the robots won’t need salary increases, health benefits, or any other recurring monetary investment that human labor would require.

Think of it this way: you’re investing in your future. That doesn’t always come cheap, but the saying “You have to spend money to make money” has never been more true.

Understanding Limitations of Factory Automation

Factory automation is still very much in its early stages and not every robot and software is ready to take on the world (yet). In order to fully embrace the automation you want, you will need to understand what you can and can’t do within the product’s limitations. Being ambitious is always a positive, but setting the right expectations can set the stage for more future success.

Just because automation has certain limitations today doesn’t mean these same limitations will be there tomorrow. As the technology advances exponentially yearly, most of these restraints will eventually be lifted.

Let’s go back to our table manufacturing example. Say these tables are wooden and need to be sanded down but the technology isn’t quite perfect yet, you can still use the paint spray processes to start and eventually finish with sanding down the line once the technology is ready. Don’t let automation’s initial limitations blindside you about its potential.

With autonomous robots, you'll be able to take a step back and watch the robots do the hard work, giving you more time to focus on other priorities.

Consider Alternatives If You Don't Automate

Factory automation requires you to take a leap of faith into a new world, which can understandably be unsettling – that’s how change usually is. However, it’s worth noting the long-term effects of not going down the automation path. 

As the labor force in manufacturing continues to decline, it’s becoming increasingly difficult to find replacements for those exiting the workforce due to retirement, among other reasons. You will either have to outsource the labor, where quality will surely take a hit, or pay incoming employees a substantially higher wage than those who preceded them. 

If you opt to continue operations as is without any change, your output could also suffer as a result. With fewer employees – or less skilled employees – output will naturally take a hit. 

What’s important to understand is automating your business doesn’t happen overnight. From the initial decision to automating all the way to getting this project online, it could take two or three years. If done properly, the benefits of automation can be realized over 20 years or more. As the technology advances, so will your business. Every passing day means problems are solved and benefits are gained.

These automation solutions naturally go much deeper than simply planning and executing a task. Sure, the robots will need some maintenance and upgrades over time, but none of these costs will fluctuate the same way costs for human labor will. Over the years, automation will save you on labor costs, sick days from employees, overtime pay and much more. As well, if their productivity can easily eclipse that of a person, then automation will easily pay itself off within a timespan much shorter than the full life of a system.

Automation isn’t a one-stop shop to solve all your manufacturing problems right away. You will need patience, proper foresight, and specific planning. If you have all three of these components and the willingness to try new things, then you will see the benefits of automation sooner rather than later.

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 to learn more!