Disabled Workforce Finds New Hope in Robotics Jobs

January 31, 2012

Robotics not only promotes job growth through sustaining industry; it creates jobs for disadvantaged populations. The Lighthouse for the Blind, an AS9100- and ISO 2001:9000-certified manufacturer, provides jobs for over 200 visually impaired workers, in every part of the company, from the shop floor to management.

Automation Empowers Disabled Workforce

By Wayne Riley, Assembly Magazine

A nonprofit organization, the Lighthouse has been providing machine shop services for more than 60 years. It employs more than 230 blind or deaf-blind workers—80 percent of its workforce—including 70 machinists who are blind or deaf-blind. Each month, these employees create more than 5,500 unique parts at a total volume of 50,000 pieces for Boeing and other aerospace companies with an acceptance rate of more than 99.96 percent.

The workforce at Lighthouse turns out a wide variety of parts and equipment, including aerospace components, specialty tools, office products, hydration packs, bulletin boards, mops and canteens.

Workers do their jobs with help of sophisticated assistive technologies, including large-print keyboards, computer screen-reading software known as JAWS (Job Access With Speech), and digital calipers paired with a voice output device that speaks the measurement on the readout.

With these aids, blind and deaf-blind personnel can operate the most up-to-date equipment for producing aircraft parts and other products with the same skill as sighted individuals.

We’re proud that several RIA members are partners with Lighthouse, including robot supplier FANUC Robotics America Corp., integrator PRE-TEC, and Boeing. What other ways do you see robotics making the workplace more accessible?

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Automation Outlook Positive for 2012

January 27, 2012

Last week at the record-breaking Robotics Industry Forum, Alan Beaulieu, President of the Institute for Trend Research (ITR) presented on the future of automation growth. Beaulieu gave a keynote address to the attending 350 industry professionals about the potential success and pitfalls in the next few decades.

If Your 2011 was Good, 2012 will be Better

By Mark T. Hoske, Control Engineering

Outlook for automation growth in the U.S. is strong for 2012, and if you’re in a technology business that did well in 2011, you’re likely to do well in 2012 also, suggested Alan Beaulieu, president, Institute for Trend Research (ITR), in a Jan. 19 keynote presentation at the Robotics Industry Forum, AIA Business Conference, and MCA Business Conference, in Orlando, Fla. Beaulieu (and others at the meeting) emphasized that automation helps companies become more efficient. “It will be a good decade for automation,” which helps companies be more productive and efficient even during tough economic times, Beaulieu explained.

Among U.S. concerns, Beaulieu said, debt payments continue to grow within federal budgets, as overspending continues. Now debt is 120% of GDP, the highest since WWII, with no remedy (and none of the large post-war growth potential) in sight, he said. Businesses need to invest now, adding talent and efficiencies to prepare for a possible mild recession in 2014, a larger one in 2019, and a possible depression by 2030.

Read the original article in its entirety at Control Engineering. What are your thoughts about the future of automation? From the business level, are you seeing the same patterns for growth that Alan Beaulieu sees? What are your suggestions for continuing stability in uncertain economic times?

You can explore more research from the Institute for Trend Research at the ITR webpage. The Robotics Industry Forum is an annual members-only conference co-located with the AIA Business Conference and MCA Business Conference. If you don’t want to miss another exciting year, you can learn more about membership on the RIA website. We hope you’ll join us next year for another record-breaking event!


Automation in the Cloud

January 26, 2012

By Rush LaSelle, VP & General Manager, Adept Technology, Inc.

Originally posted 01/07/2012 on Robotics Online.

Manufacturers and processors of anything from snack foods to automobiles are being driven to offer higher levels of variety in what they offer their customers. Invariably, supply chain power is shifting to buyers and consumers. This shift has been driven by numerous factors including the proliferation of information available to shoppers on all forms of digital devises effectively creating larger consideration sets. As the choices have increased, sellers and ultimately suppliers are forced to increasingly adhere to fads and rapidly changing consumer sentiment to retain market share. If we were to define the optimal supply chain to meet this trend it would be one where any item, no matter its level of complexity, would be produced on demand. Further, even the most commoditized and low costs items such as confectionary would be produced in a batch size of one to permit mass customization. This would enable a buyer to select a picture of the family dog from their iPad, upload it to a manufacturer’s website and a few days later a delivery van would arrive at your door with a box of chocolates each in the shape of Scruffy.

Markets are best served by catering to the individual tastes and preferences of the consumer. Therefore, we are beholden to understand how manufacturing must adapt to move past today’s batch processes to achieve a batch size of one. The innovation required to enable manufacturers to offer this, the ultimate level of production flexibility, will be drawn from fast-paced/cutting edge/advanced industries such as gaming and information technology.

Enter cloud manufacturing as technologies exist in all facets of packaging, labeling and decorating product to permit rapid change of color patterns and form. The pacing item is process control and ultimately the information from the consumer. And with the unprecidented speed of digital connections between people and the commercial world through social networks and alike, this valuable information can now be made more quickly/easily available to manufacturers through the cloud. Cloud manufacturing represents the convergence of information, learned processes, and intelligent motion or activity.

Definition
Cloud Manufacturing is a model for enabling convenient, on-demand network access to a shared pool of configurable manufacturing resources (e.g., robotics, control systems, networks, applications, and services) permitting the comparison of digital process control with physical operation. The networking of sensory input, databases, and computing resources facilitates the management of sufficient data to recognize complex patterns and execute algorithms to evolve behaviors. Reconciliation of environmental conditions and information available in the cloud permits mechatronics to serve as the conduit between the digital and physical world.

Dynamic Process Control
To illustrate the concept, consider a robot tasked with dispensing icing on a cake. Today a robot is programmed to process certain patterns and graphics taught by its user. The robot would be outfitted with the ability to dispense various colors with different nozzles and the system would produce cakes with various images. In a highly controlled environment, a cell with set programmed paths will produce the images without incident. However, what happens if the environment and/or process changes. Consider the impact of the following:

  • Viscosity of the icing
  • Temperature within the facility
  • Humidity

Viscosity of the icing is critical and most closely controlled. To keep the viscosity the same, the cake decorator is most likely locked into a single supplier to ensure consistency. In the event that the decorator produces his or her own icing, the level of process control to maintain the consistency is costly.

Temperatures in facilities affect a large number of parameters in the process. If the cake is cooled in ambient conditions it is subject to the changes in the plant’s temperature, which may impact the dimensions of the cake when it comes to the automated decorating station. If the icing sits in the delivery system for a period of time and the facility’s temperature varies day to day, the viscosity and properties of the icing are altered in kind.

Like temperature, humidity can impact numerous steps in the process. A higher level of moisture in the batter during one shift changes how the cake rises or its dimensions as it cools from the cakes produced the previous shift.

In some cases simple localized sensory input can adjust for environmental changes. If the cake height changes due to temperature, humidity, or upstream process changes, a variety of sensors could provide an input to the robot to offset the dispense height to accommodate the change. This signifies a defined rule-based solution and is far from complex.

Viscosity can be measured though numerous sensing devises located in the delivery equipment or lines. With the appropriate delivery mechanisms, the manner in which the icing is pumped through the lines and ultimately though each nozzle can be profiled and managed to adjust for the changes in viscosity.

Therefore, it would appear through a rule-based system and the implementation of sensors that the cake-decorating system can accommodate environmental changes, correct? Not so fast. As humidity changes and temperature goes up or down the icing exhibits different properties of adhesion and set-up. So, while the robot is dispensing at the right height and the right volume, the desired flower image changes from a carnation to a dandelion. The interaction of the various environmental factors and effects now represent complex patterns.

When the inputs or variables become sufficiently large, this model exceeds what manageable rule-based solutions are capable of solving. In our cake-decorating example we are now going to add 3D vision which will record the decorated cake. The image will be analyzed with set parameters to determine if the critical features are within spec. The image will be correlated to environmental data to catalog plant temperature, humidity, icing, viscosity, cake height, and any other inputs we care to monitor. As the process compares predicted outcomes to actual outcomes, the system has the ability to dynamically adjust the process. Over time as patterns develop with the information, the process will evolve to where for all combinations of environmental conditions the system will learn how to modify the path of the robot to reliable draw a carnation.

Cloud manufacturing enables machine learning given the networking of expected results or those stored in a database, input from what is observed in the environment, and comparison of the predicted outcome with the actual. In this model, the robotic system is the networking device that provides sensory input and ultimately uses the information processed in the cloud to intelligently process the part. Hence the robots act as the connection between the digital and physical.

Batch Size of One
Let’s continue with our example of decorating cakes and return to the desire to personalize products for each individual consumer. The concept of cloud manufacturing allows access to a network where the consumer resides. In a basic model our baker has a website where a customer can upload a photo of their child playing lacrosse with the expectation that this photo will be reproduced on a birthday cake. This is a simple printing process for our baker, and there are web services that provide this service. But our baker wants to reproduce this image with depth to it as opposed to having it solely in one dimension like a photo.

When the system was set-up to make a carnation the decorator had programmed the robot to dispense the icing at a specified rate, in the right place, at a precise angle, and for the appropriate amount of time so that it created a layer of the image. It would continue to make layers of the icing on the cake’s surface until it produced the desired pattern and image. It is unlikely that this was a one pass programming effort, most likely it took time and refinement, (and many cakes) to get an image that would finally meet the decorator’s artistic standards.
The challenge with the baker’s business model is that the decorator won’t have the luxury of processing the lacrosse picture numerous times due to the material loss and decorating machine availability required to tune the system for set-up.

Once again, we find a scenario where the patterns and data set are so large that it moves beyond where rule-based programming is feasible. Over time and through iterations, a database will eventually be built and the behavior of the decorating machine will evolve to where the interaction with the icing already deposited and that coming from the nozzle will be understood and the robot can process accordingly.

Reduction in Programming
To realize greater flexibility, manufacturing has come to depend on robotic automation to deliver incrementally better levels of customization for production and packaging. One of the greatest barriers to deployment and the largest complaint from users of industrial robots is the programming. Many have asked why they must become proficient in dedicated languages to accomplish moderately straight forward tasks using robots or mechatronics as a whole. The cloud offers solutions to these challenges today and offers even greater promise for the future.

Manufacturers have used networks in the manner defined by cloud computing where programs are stored remotely and shared across networks. If a cell installed in California is to be replicated in Beijing, a back-up located on a server is transferred to the machine, a calibration routine is implemented, and the program is shared. This effectively enables an operator in China to leverage the development or work done by a programmer in California. As languages become increasingly open, algorithms and canned routines will be available in the cloud so that programmers can pull blocks as opposed to always having to program from scratch.

Machines are just beginning to gain the ability to search for these blocks and with certain conditions implement them to affect their activities dynamically. In another example, a recycling plant uses robots to pick glass from a paper line. Today the robot is programmed to identify and remove hundreds of unique types of glass and sort them for optimal recycling. The robot determines all the known products using an onboard processor, which would have been programmed by identifying each product with a local camera. Not only is training the system to recognize hundreds of unique glass types cumbersome and prone to error, it leaves the system unable to adapt to unknown parameters and foreign materials.

If, however, the recycling system were to harness computational capabilities and information from the cloud, it might search terabytes of information to identify an object previously unseen at this system’s location. This would function very similar to how web crawlers search the web today for any other type of information when keyed into a computer or smart device. In this scenario once the item is matched to an image in the cloud, a resulting action would be performed as the image is crowded or grouped into a product class or family which would instruct the robot how to manipulate and place the item.

This now reduces the programming requirements for a system while simultaneously expanding  its flexibility almost infinitely. The result is a system which costs significantly less to deploy and provides much greater economic value to the manufacturers or recycler in this example.

Ecosystem Drivers
The concept of cloud manufacturing is not solely driven by the demand for ever-increasing levels of flexibility and efficiency in deploying automated systems. As noted earlier, there is a supply side effect where technology and networks are now enabling higher levels of speed and low-cost processing previously unavailable. Factory automation and robotics must begin to view themselves not as industrial islands, but as devices within an information ecosystem. Historically, manufacturing equipment’s only connection to its environment included a power source, input of raw materials and output of processed goods. As such it was not adaptable to any form of change. During the industrial revolution while goods were finally being made cost-effective to where consumers could afford items previously considered a luxury, buyers were offered any color car they wanted from Ford as long as it was black. The industry focused on employing technology to enable mechanical processes to produce faster and more consistent products but flexibility was not an essential requirement.

As manufacturing begins participating in the information revolution, machinery and automation will generate and consume greater amounts of data to where they can offer higher levels of quality through dynamic process control, provide the flexibility to satisfy and insatiable consumer appetite for mass customization, and ultimately decrease costs of implementation through learned heuristics. Unlike the productivity gains of the Henry Ford era, today’s gains will be driven though better utilizing processing information technologies.

It can be expected that over the coming years that manufacturing will more fully capitalize on the information ecosystem surrounding it. This ecosystem spans the networking and data storage industries to the human machine interfaces currently being deployed by consumer electronics manufacturers and gaming technologies. As the automation industry begins its reach into the cloud, manufacturing communities will not only improve productivity, they will begin to reclaim the prominence the industry once claimed in the economy.


Environmentalist Robot Helps Monitor Pollutants in Ocean

January 25, 2012

In wake of the disastrous cruise ship crash off the Italian coast, a group of researchers is utilizing their water-bound robot to test the waters for pollutants.

Laser scanners, GPS sensors, and sonar compasses help navigate the robot in diverse water scenarios and prevent collisions above and below the water. Information about the water’s properties is sent instantaneously to supervisors via a wireless computer network. HydroNet’s creators, from the Sant’Anna School of Advanced Studies, say it could provide real time analysis of oil slicks and contamination for environmental authorities.

With an area as vast as the ocean, aquatic robots like the HydroNet could help with pollutant detection and clean up. In what other areas do you see robots helping us take care of the environment?

Watch the video interview and read the transcript at Reuters website.


Record Attendance for the Robotics Industry Forum

January 24, 2012

Last week we had an outstanding turnout for our annual Robotics Industry Forum down in Orlando, Florida. Over 350 professionals from the robotics, vision, and motion control industries gathered for three days of exceptional speakers, business-building networking, and market insights. Samuel Bouchard, CEO of Robotiq, summarized his findings at the conference nicely:

Robotics Industry Forum 2012: 10 interesting things that I’ve learned

3. Robots DO create jobs

Who said that: Mike Wilson, British Automation and Robotic Association
This did not surprise the robotic folks listening to the talk, but everybody was glad to finally see serious numbers that prove this important statement. In fact, a recent study from the International Federation of Robotics indicates that every industrial robot that is installed will create 1 or 2 jobs.

To read the other nine valuable points gleaned from the conference, visit our LinkedIn RIA group page. Did you attend the Forum? What did you find of interest?

The Robotics Industry Forum is an annual members-only conference co-located with the AIA Business Conference and MCA Business Conference. If you don’t want to miss another exciting year, you can learn more about membership on the RIA website. We hope you’ll join us next year for another record-breaking event!


A Robotic Talent Show

January 19, 2012

You may not think that the ability to balance, hop, or cling to a vertical surface would be useful traits for a robot in an automation or manufacturing sector, but the more complex designers make robots the more creative applications are available for a variety of different industries. Discovery News recently listed their Top 10 Robot Talents in an article by Alyssa Danigelis. My favorite? The ability to build while flying —

Construction robots and ones that fly aren’t all that unusual, but it took a group of roboticists and architects to put those two skills together. The result is a team of “robotic quadrocopters” that cooperated to construct a 20-foot tower from lightweight foam packaging blocks.

The robots were built by Swiss Federal Institute of Technology Zurich roboticists and Swiss architects Gramazio & Kohler. They used a platform they called the “Flying Machine Arena” which allowed them to test fast-paced motions on the ground and in the air.

Working in tandem from a blueprint along trajectories that avoided collisions with each other and the building structure, the quadrocopters gripped the foam bricks and quickly flew each one into place.

“It’s a first,” Howard said. “It makes sense.” The Flying Machine project is one of those things, she added, that makes us go, “Why didn’t we think about this before?”

Which of those ten traits do you find most impressive? What new applications can you see for these robotic skills?


Choosing the Right Robotic Gun for GMAW Applications

January 17, 2012

by Robert Ryan, P.Eng., MBA , Director, Automation and Aluminum Group
Tregaskiss
Posted 01/06/2012

From high-volume, low-variety manufacturing facilities to low-volume, high-variety fabrication shops, robotic GMAW (Gas Metal Arc Welding) arc welding has become increasingly popular due to the potential weld quality and productivity improvements it can provide. Not only do those benefits make it an attractive investment for growth and profitability, but they can also provide companies with a competitive edge.

Selecting the right equipment for a robotic GMAW arc-welding operation, however, is not a task to be taken lightly. From determining the correct style of robot to suit an application’s particular requirements to deciding which welding peripherals to purchase, companies must always choose wisely. Selecting the appropriate robotic GMAW gun that suits the requirements of the application is also essential for optimizing the return on investment. For example, using a robotic GMAW gun that has a higher amperage capacity than required can unnecessarily increase the total cost of ownership. Conversely, selecting an inadequate GMAW gun can lead to performance issues, costly downtime and premature failures.

Instead, companies are encouraged to select a robotic GMAW gun that is suitable for the amperage, duty cycle and cooling capacity needed for the application. Doing so helps ensure good weld quality, and reduces equipment and maintenance costs. The right robotic GMAW gun also helps companies improve productivity.
The following information helps to outline key considerations towards making the right selection.

Selecting the right robotic GMAW gun, including an air-cooled model (as shown here), can help ensure good weld quality, and reduce equipment and maintenance cost—factors that lead to a good return on investment and greater productivity.Staying Cool with Air-Cooled Technology
Typically, air-cooled robotic GMAW guns (rated at 500 amps) operate comfortably in the range of 200 to 300 amps at approximately 60 percent duty cycle with mixed gases (i.e. welding continuously for 6 of 10 available minutes). Further, these guns are ideal for welding thinner materials—typically upwards of 4 mm thick —and work best for shorter welds on high volume applications, including (but not limited to) those in the automotive or recreation equipment industry.

Air-cooled robotic GMAW guns, like their semi-automatic counterparts, rely on the ambient air to cool them during the welding process. These guns feature a unicable through which the welding wire, gas and power are all delivered. Air-cooled unicables use the appropriate amount of copper to create a conductor that is capable of managing welding current without any additional cooling. When compared to water-cooled unicables of similar rating, air-cooled unicables generally have up to four times the circular-mils (i.e. cross section) of copper.

There are several advantages to using air-cooled robotic GMAW guns, the most significant of which is their durability. An air-cooled gooseneck (or neck) has a much stronger and durable construction when compared to the gooseneck on a water-cooled robotic GMAW gun, making it more resistant to bending in the event of a collision or through general wear. Replacement parts for air-cooled robotic GMAW guns also cost less and are easier to maintain. These guns tend to have a more streamlined design and smaller working envelope, allowing greater access into smaller joint configurations than a water-cooled robotic GMAW gun. Too, air-cooled robotic GMAW guns maintain their accuracy very well, which makes them an excellent option for applications requiring consistent, repeatable welds.

One limitation to air-cooled robotic GMAW guns is the lower duty cycle when compared to water-cooled guns; they are not capable of welding continuously for as long as a water-cooled robotic GMAW gun.

Just Add Water
Water-cooled robotic GMAW guns offer excellent advantages for applications that require welding at higher amperages for prolonged periods of time. These guns provide high amperage capacity—generally 300 to 600-plus amps—and are capable of managing a duty cycle within the 60 to 100 percent range. They are Water-cooled robotic GMAW guns (as shown here) offer high-amperage capacity for applications requiring prolonged periods of welding.designed for welding on thicker materials (typically 1/4 inch and greater), making them a good choice for applications in heavy equipment manufacturing or similar such industries. As a rule, the larger the overall size of the weldment, the greater the chances the application will require a water-cooled GMAW gun.

To prevent overheating, water-cooled robotic GMAW guns rely on a supply of water or coolant from an external source. These sources include circulators or chillers, which tend to add to the overall cost and maintenance requirements of the system. The coolant travels through a water hose in the gun’s cable bundle (also containing the power cable, wire, and gas and water return hoses) and circulates up through the gooseneck to the consumables. For very high-amperage applications, there are also water-cooled nozzles that are capable of circulating the coolant around the nozzle, but these are more expensive than standard ones.

As mentioned previously, water-cooled power cables (found in the cable bundle) have approximately ¼ of the copper found in an air-cooled unicable; thus, water-cooled unicables quickly fail if the water supply is interrupted. This factor is a disadvantage of water-cooled robotic GMAW guns, as the parts can be expensive and time consuming to replace should they become damaged.

Routine maintenance of the cables within the cable bundle can also be difficult, since they are all in close proximity to one another. And because these guns have internal water chambers in the gooseneck, that part is inherently weaker than the gooseneck on an air-cooled robotic GMAW gun and much more likely to bend in the event of a collision.

Still, for high-amperage applications that require high capacity cooling to protect the gun during long periods of welding, dealing with these disadvantages still make having a water-cooled robotic GMAW gun worthwhile.

Hybrid robotic GMAW guns (as shown here) offer the durability of an air-cooled model gun with the greater cooling capacity of a water-cooled one, making them an ideal fit for welding multiple thicknesses of materials. An Option In Between
For companies that weld multiple thicknesses of base materials and require both high and low amperage capabilities from a robotic GMAW gun, a hybrid air-cooled/water-cooled robotic GMAW gun is a good option. These GMAW guns have a durable gooseneck like an air-cooled model, but offer the higher cooling capacity of a water-cooled GMAW gun. They feature exterior water lines that run along the outside of the gooseneck to the nozzle, as opposed to through the gooseneck like water-cooled GMAW guns have. Hybrid air-cooled/water-cooled robotic GMAW guns typically offer 300 to 550 amperage welding capacity at 60 percent duty cycle (using mixed gases).

Hybrid air-cooled/water-cooled robotic GMAW guns also have features that provide easier maintenance compared to a true water-cooled product. For example, the water lines run independently of the power cable and are more accessible than with a standard water-cooled GMAW gun, so these guns do not need to be taken off of the robot for maintenance. Plus, if there are issues with water circulation, these guns can rely on the underlying air-cooled unicable to provide enough current-carrying capacity to avoid a catastrophic failure such as destroying a power cable or other components. Overall, the features of the hybrid air-cooled/water-cooled GMAW gun help provide a lower total cost of ownership for the gun.

One limitation of these GMAW guns, like a standard air-cooled model, is the limit to duty cycle. For applications that require continuous duty cycles, these GMAW guns would not be the best choice and a water-cooled product may have to be deployed.

Protecting the Assets
Regardless of which robotic GMAW gun is right for a given application, good preventive maintenance is critical to ensuring product longevity and reducing unscheduled downtime. In particular, most robotic GMAW gun manufacturers recommend using a nozzle cleaning station to prevent spatter build-up that can lead to quality issues or downtime (and costs) related to consumable changeover. Checking for loose connections along the length of the robotic GMAW gun—from the power pin to the nozzle—is also key to preventing quality issues or damage that could cause the gun to fail prematurely.

Remember, choosing the appropriate robotic GMAW gun to suit the requirements of the application is essential for optimizing the return on investment. Using the right robotic GMAW gun also provides for a more reliable system and can help manage the total cost of ownership, particularly by minimizing performance issues, costly repairs, unscheduled downtime and premature failures. In the end, it takes less time and money to protect a robotic GMAW gun with preventive maintenance procedures than it does to take the gun offline for repair or to replace it.

Contact Information
Tregaskiss is an RIA Supplier Member. For additional information, please contact Tregaskiss at 877-737-3111 or 519-737-3000, or click Tregaskiss.