How to Reduce the Cost of Rework in Manufacturing

The cost of rework in manufacturing is growing. Retiring baby boomers and skilled laborers – along with a lack of younger workers to replace them – is effectively making the old models of factory and jobshop life obsolete. Stepping in to replace a lot of that skilled labor is automation, however automation usually requires significant investment and doesn’t adapt well to facilities with a lot of batch variation or high-mix product set. As such, the cost of both work and rework is going up.

When it comes to industrial processes like painting and powder coating in particular, more people are unwilling to work in such difficult environments while the ability of coaters to achieve the high-quality output they’re looking for is diminishing. This is so significant that as demand increases, many coaters simply end up refusing orders or refusing to employ additional shifts because they can’t be assured that the quality of work produced will avoid rework enough – ultimately turning a lot of profitable deals into a loss.

While mass manufacturers have eliminated a lot of rework and defect issues, all manufacturers can reduce the cost of rework through a few key initiatives that bring them into a new era of efficiency. These include flexible automation systems that better respond to short term demands, autonomous robots that help improve value-added processes by adapting to parts as they are, and maximizing consistency in such a way that can eliminate rework in the long term and give manufacturers the freedom they need to grow. 

Labor costs have steadily risen no matter what manufacturers do. While this is primarily a demographic problem, new automation tools can help. Source: FRED.

Flexible Automation Systems

Flexible manufacturing systems and flexible automation are a new generation of work tools that enable manufacturers of all types – from sheet metal, aerospace and heavy equipment to consumer electronics, automotive and other discrete products – to better adapt and modify their workflows throughout the day in place of relying on rigid or fixed systems to get work done.

What are some good examples of flexible manufacturing systems? These can include autonomous mobile robots, integrated machining, container-based control systems, buffer storage and autonomous value-added robots – all of which essentially add slack and flexible automation to your production processes in order to give your workforce the bandwidth to focus on getting things right the first time.

Ultimately, this is the first channel to reducing rework because it eliminates some of the causes of defects and the need for rework in the first place. Often, these kinds of issues can come from moving too fast and simply not giving workers the time or materiel needed to ensure that they avoid mistakes. While total productivity could lag where all things are held equal, these flexible systems can help speed up a lot of the downtime in your existing production in ways that allow workers to do more without feeling pressed to do so – another situation where rework often arises.

Autonomous Robots

While autonomous mobile robots have grown more common for a variety of materials handling scenarios, they don’t necessarily add value to parts in a way that would reduce rework. This is where autonomous robots for value-added processes can improve things instead – whether it’s for painting, spraying, coating, welding, machining or other processes, a variety of technologies are now available today that bring these closer to reality.

What is autonomy? It’s effectively any system that, once parameterized, can operate with limited oversight or surveillance, meaning you can expect a reliable and consistent output based on simple instruction sets instead of complex robot programming, jigging, fixturing or other challenges. 

With autonomous robots, it becomes much easier to specify the behaviors you want to articulate without needing to consider part shape or orientation limitations. For example, Omnirobotic’s AutonomyOS ™ uses 3D Perception with AI-based Task Planning and Motion Planning so manufacturing engineers and integrators can configure autonomous robotic systems for value-added processes that reduce labor shortages, increase productivity, save energy, waste and rework. As well, it will allow manufacturers to achieve more consistency and flexibility in production than ever before.

 

Autonomous robots like those running AutonomyOS ™ can execute value-added processes with limited oversight, maximizing the productivity of high-mix manufacturers.

Maximizing Consistency

The underlying benefit of this type of technology is the capacity to use existing industrial robots without needing to program them or fixture the parts they operate on. As it happens, manufacturers have already seen massive benefits from this. The study below indicates this: the output of an autonomous robot was compared to that of a skilled worker for a variety of parts and paint colors, and in all cases the robot was fundamentally more consistent without needing to be programmed. 

At the same time, that target consistency of 1 mil was previously quite restrictive – variations of .5 mil could lead to significant rejection or rework rates. By using robots, this aerospace manufacturer was able to overcome the limitations it had seen within its skilled workforce and took it’s previous rework rate (between 40 and 50%) to near-zero in only a few weeks. 

Autonomous robotics technology can create a fundamental leap forward in the quality of output realized – no matter the variety of parts processed!

Eliminate Rework With Autonomous Manufacturing

Of course, robots are incredibly good at following orders – to the letter, in fact. While it would be nice for humans to have this capacity, we know that people are far more creative, innovative and as a consequence inconsistent, which means that we will always get some level of rework whenever a human-led process needs to be relied upon.

While there are sometimes no other options, the truth is that accurate, flexible automation built on the new general purpose technologies of today can eliminate the uncertainty and inconsistency that leads to the high cost of rework in manufacturing today. At the same time, autonomous manufacturing robots and systems can free up workers and managers to focus on oversight, design, management and guiding processes to their best outcome, rather than having to do all the dirty work themselves!!

With AutonomyOS™ and AutonomyStudio™, it’s never been easier to deploy an autonomous robotic system.

Manufacturing Labor Supply Is Dead – What Did it In?

There are two questions when it comes to the manufacturing sector in North America – why have jobs been going overseas and what did them in?

While plenty has been made of the political ramifications for each question, the real challenge to consider is what appropriate economic choices could be made and why certain classes of people were expected to pay a price for that.

The history of the relative decline in North American (or simply American) manufacturing is a complex one, and the main to consider here is not whether the sector was “sold out” – although it clearly seems like that may have been the case – but how the American economy was forced to adapt as its comparative advantages rapidly changed, and what implications that has for the next generation to enter the workforce and find that manufacturing isn’t really something they’d like to go back to. 

The Degree to Which Manufacturing Labor Is Dwindling

The number of Americans working in a factory has declined by a full third since 2000. 3 million baby boomers retired during 2020 – double the number in 2019. There are massive shortfalls in machinists, welders, frontline engineering and plenty of the hard-scrabble jobs that built America’s reputation as a manufacturing powerhouse. 

Industries like machining, metalworking and related equipment manufacturing, median workforce ages of 48 and above substantially outpace the total labor force’s media age of 42.5. There are approximately 6.3 million manufacturers between the ages of 45 and 64, and only 4.1 million between the ages of 20 and 34. 

By 2030 there will be 2.1 million unfilled manufacturing jobs in the United States, and that will effectively cost the US $1 trillion in annual productivity. The top two consequences cited by manufacturers of not being able to fill jobs were the inability to increase revenue growth (82%) and maintain production levels to satisfy demand (81%)

Warehouse and distribution jobs are increasingly competing for manufacturing workforce share, despite entry-level jobs in manufacturing averaging $15.55/hour, or double the minimum federal wage, and manufacturing wages for skilled workers are even higher.

Starting to get a sinking feeling? Wondering how this could even be possible? Don’t worry – we’ll get to the answer soon. 

Manufacturers have clearly invested in re-shoring, and yet the supply of labor simply can’t meet demand. How did we get to this sputtering restart?

Why The Usual Suspects Aren’t Necessarily the Ones to Blame

The decline in the manufacturing labor supply can be chalked up to a variety of changes over the last 50 years:

  1. The decline in comparative advantage of US Manufacturing following post WWII recovery
  2. The relative increase of labor cost and quality of jobs available in North America and the decline of interest in manufacturing work vs other sectors of employment
  3. The opportunity for global economic integration in place of a new Cold War
  4. Long-run demographic decline that is now culminating in a rapid skills decline

These are all incredibly broad-based, macro-level concepts for which many individuals and corporations ultimately pay in their bottom line. While we can vary rarely “change the wind” in such circumstances, we can always “adjust our sails”.

Thus, what are the most salient aspects of each of these points?

Decline following WWII recovery

The United States rose from the Civil War and into the 1920s to become the largest industrial power on the face of the earth, with resources and labor power that could outstrip entire continents. This advantage became so massive that the US was considered to control half of the world’s wealth and most of its gold reserves by the end of World War II. While the US helped rebuild the rest of the world from a state of near-total devastation, those countries ultimately caught up and earned back some of the relative wealth they had lost. At the same time, countries like Germany, Japan and today China have developed the machinery and productive capacity to compete with the United States in a variety of industrial sectors, ultimately reducing the United States’ comparative advantage in those sectors. The irony here is that these countries in many ways followed US development models from the 19th century, while the US approach to more refined financial capitalism has produced its dominance in global capital markets and technology megaliths that we see today.

Relative increase in quality of jobs

There is something to be said in the satisfaction of working with your hands and making things people actually need, and for that reason the manufacturing workforce will never truly be “dead” (sorry for the clickbait title). However, given the opportunity to work all day in an air-conditioned office or at a whiteboard drinking trendy coffees and talking to your colleagues about the latest Netflix mini-series, most people will forego the discomforts of a more honestly productive line of work. At the same time, many of these more comfortable jobs are available in the United States than elsewhere in the world because of 1) the country’s large consumer sector and 2) the global presence of US corporations which are most often still managed from the United States. 

Avoiding a New Cold War?

Yes, it’s the China question. Yes, there’s a lot to say here. On many levels, much of the argument about manufacturing in China centered on integrating the global economy to avoid a new age of “living on the knife’s edge”. While some people have benefitted more than others, nobody is benefitting from the state of the labor market in North America today. Again, It’s important to keep population in mind – America is a big country, yes, but still leads the world in many ways despite its size, not because of it.

Demographic Transitions

US preeminence across the globe in part came from the rate at which the United States grew, but between 1950 and 2010, the rest of the world rapidly outpaced anything the US could put up in terms of sheer workforce size. In these circumstances, it’s no wonder that more cheaper labor was available globally – if that need to work wasn’t in some way satisfied, who knows what kind of instability would follow? As it happens, the population growth rates between the United States and the rest of the world are expected to converge over the next 40-odd years, something that will ultimately crush the availability of labor in the United States – exactly when the US will need a workforce (and a manufacturing workforce above all) to continue to compete. 

The sheer supply of labor overseas is something North American manufacturers simply could not have ignored. Now that global population growth is coming back into balance, considering new forms of productivity will become the priority.

The Limits of Computerization

To adapt a quote from bertrand russell, we must ask: has the history of digital technology simply been a footnotes to thomas watson? Ultimately, the introduction of computing power is the most compelling aspect of it, but then it imposes new costs – it requires us to structure data, environments, peoples behavior in new ways to get more out of it. This is incredibly labor intensive and not always productive, the biggest step forward is autonomous machines – the ability to step into the real world

The fact is, since the 1970s at least, growth has been slow, resources more costly, people have been having fewer kids and the general rate of change in society is much slower – even if it feels faster because of media, social networks and digitization expose us to the changes that do happen at a more rapid, iterative pace.

In response to this, we need new capabilities, new general purposes technologies that actually make an impact in the physical world

As it happens, this is actually the best possible thing that could happen to workers, and will happen for possibly the first time in 100 years or more – the widespread distribution of technology that fundamentally changes how, why and what people work for. 

Why All That Is About to Change

We’re in a multi-generational transition – the way humans and machines interrelate will create more and better jobs. If you look at the history of automation, the rise of machines didn’t just displace many people but did so from jobs that were miserable drudgery, and actually increased the share of growth that went to wages as a result. People no longer had to struggle en masse for a living – the advent of new energy, sanitation, transportation and combustion made life far easier and work far more manageable

Automation grew at a far faster rate between 1870 and 1940, actually increasing accrual of income to labor – all while some of the world’s most well-known corporations and modern institutions got their start. Among these technologies: the internal combustion engine, sanitation, telecommunications, chemicals, pharmaceuticals and electrical machines that made life fundamentally better, but also drastically easier, while creating ease and flexibility in the workday like never before.

Higher prices are the best way to create supply, but not at the cost of the final product. Research has shown that rapid introduction of new technology increases productivity to such an extent that it actually helps the labor market grow. Source: Robert J. Gordon, “The Rise and Fall of American Growth”.

Stepping Into the Autonomous Manufacturing Future

The fact is, the new jobs created will create increased pressure to distribute new goods and better satisfy the workforce. Giving more freedom to individuals is a part of the job of our economic machine. At different times, it achieves this with different degrees of effectiveness – it’s most recent run being somewhat lackluster.

With Artificial Intelligence that can finally be used on the factory floor, however, things will be different – a lot different. Autonomous manufacturing robots are one such technology: they can accomplish tasks like painting or coating parts without the need for programming or extensive human oversight, automating the most difficult parts of jobs that are already hard to fill, and just one example of how the manufacturing labor supply that’s still here doesn’t have to keep trudging through its days, and can instead accomplish far more than previously thought possible with new autonomous manufacturing robots at their disposal.

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.

What Is General Purpose Technology?

General purpose technology is a technology or technology set that has broad implications for a wide variety of factors in human life at any given time. In many ways, general purpose technologies pile on and magnify each other’s power, but new technologies also make us realize the inconveniences of old ones, such as advances in different types of toolmaking, lighting or transportation.

Classical examples of this type of technology are the wheel, fire or stone tools. While we generally think of technology today according to what is patentable, the fact is that once a general purpose technology is discovered, it’s range of applications and variety of effects means that the whole concept in itself rarely gets patented, but the specific instances where the technology principles are applied become both lucrative as businesses and broadly beneficial to society.

Ultimately, one of the best examples is the transition that took place from animal domestication to railroads and internal combustion, and finally the potential that exists for autonomous vehicles and systems as a whole. As we go along, we realize that general purpose technologies are difficult to predict, often because they so fundamentally change the way we live. At the same time, rethinking everything from the ground up is essential to real innovation and to true productivity improvements that make like better. 

The Horse-Drawn Carriage

Today, general purpose technology is considered to be a critical factor in future economic growth. The principles behind this technology usually involve a fundamental reduction in inputs or a fundamental magnification of outputs. For instance, horses were a common part of city streets through the late 19th century. So common in fact that substantial portions of grain grown to feed people also had to go to horses to “fuel” their activity. Horse manure was a large contributor to ill health in cities, and horse trampling was a not-uncommon cause of death for urban citizens who may have simply been in the wrong place at the wrong time. 

The use of cars ultimately meant the demise of horses as a means of transportation, but for leisure of course they are still as lively as ever. Source: Green Project Management.

At the same time, long distance horse-drawn travel had many pitfalls – namely the need for large wagon trains to retain the appropriate resources to again “fuel” the long distance adventure. At the same time, a horse can travel approximately 25 to 35 miles per day at a sustainable speed. We know that even some of the earliest cars could travel 25 to 35 miles per hour. Hence the internal combustion engine was considered a “general purpose technology” that fundamentally transformed the human conception of time and space. 

No longer were the conventional limits of 30 miles per day to be radically imposed. First, with railways and then with cars, infrastructure was also laid down to ensure that fast travel could be realized on a broad basis – first in Europe and North America, but eventually through most parts of the world. While the first transcontinental expedition by Lewis & Clarke traveled 8000 miles over 2 years, the transcontinental railroad itself took 10 days to ride – and took a much straighter path at that.

Autonomous Vehicles as a Next Step

Today, cars and highways can allow a person to cross the United States in a matter of days while still stopping for sleep and the bare necessities of life along the way. Planes allow for it in a matter of hours, with a variety of added safety concerns, inconveniences and predefined destinations along the way. 

As it happens, air travel is also considered a General Purpose Technology, but Autonomous vehicles are a further improvement on the cars and trucks that have already provided so much freedom and productivity to the everyday individual.

Even where cars are used for leisure, autonomous vehicles are fundamentally a labor-saving device. Source: YoungWonks.

With Autonomous Vehicles that effectively “drive themselves” travelers can not only conceivably eat, sleep and take care of business without ever getting out of the car, but drive continuously at high speed, but could conceivably do all that in less than 24 hours (if an autonomous vehicle could safely drive at beyond 150 miles per hour).

Obviously, there can arrive a point of “overkill” in the effectiveness of new technology. But it’s also important to think about how much labor and attention is saved with an autonomous vehicle – how much less boring and tiresome it will be to drive across the country, and with a laptop and a network connection, how much more work could conceivably get done while the drive is taking place. 

But What If Autonomous Vehicles Are Just the Beginning?

As it happens, Autonomous Vehicles aren’t the only use of AI and machine vision that are going to transform the way we live and work. Autonomous manufacturing technologies – chief among them being robots with autonomous capabilities – are fundamentally transforming the way goods are produced to serve consumers, businesses and society as a whole. 

Through the use of autonomous manufacturing robots, manufacturers can already deploy a variety of spray processes without the need for programming or fixturing, drastically reducing the time required to achieve a high quality, highly repeatable, highly reliable process output – even in high-mix or highly varied productions.

Omnirobotic’s AutonomyOS™ is the only way to do this today, and by providing a reliable, cleaner and safer working environment, is helping make manufacturers more productive and ultimately helping workers achieve a better quality of life in some of the most challenging industrial jobs around. 

Omnirobotic’s AutonomyOS™ enables manufacturers to automate their spray and finishing processes – even in high-mix scenarios. A versatile technology for a versatile age.

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.