Getting Started with Collaborative Robots - Part 4 - Assess Your Potential Applications
Documenting the actual process will allow you to evaluate if the process can be automated. This will also give you a starting point on cell performance and improvement opportunities.
For Advanced Manufacturing, Success Demands Innovation, Education and Public-Private Partnership
MICHAEL D. WHEELER for Photonics.com: Global manufacturing has undergone enormous changes in the past decade as many developing countries have joined the club of tier-one manufacturing nations, a recession stalled demand, and employment fell precipitously in leading economies. Yet manufacturing remains critical to the future of both developing and advanced worlds, driving innovation, productivity and competitiveness, and offering a pathway out of poverty.
Recent attention has focused on “advanced manufacturing,” which replaces traditional labor-intensive processes with ones based on the newest technologies. It encompasses a family of activities that depends on information, computation, software, sensing and networking, while making use of cutting-edge materials and emerging capabilities such as nanotechnology.
Advanced manufacturing is an especially potent propellant of future economic growth, distinguished by continual process improvement and rapid new product introduction. These critical features will lead to the building of lighter, more fuel-efficient automobiles, the creation of “needleless” tests for medical conditions like diabetes, and the fabrication of semiconductors with 10 times the current processing power. Cont'd...
Special Tradeshow Coverage for Advanced Manufacturing Conference & Expo 2016
Advanced Manufacturing Conference & Expo 2016 will be held from February 9th - 11th in Anaheim, California. This ManufacturingTomorrow.com Special Tradeshow report aims to bring you news, articles and products from this years event.
Robotics 2016: Doubling Throughput in Distribution and Factory Operations
Two existing bakery facilities were successfully integrated into one and finished goods capacity nearly doubled from 6,500 lbs. /hour to 12,000 lbs. /hour.
What Robots and AI Learned in 2015
By Will Knight for MIT Technology Review: The robots didn’t really take over in 2015, but at times it felt as if that might be where we’re headed.
There were signs that machines will soon take over manual work that currently requires human skill. Early in the year details emerged of a contest organized by Amazon to help robots do more work inside its vast product fulfillment centers.
The Amazon Picking challenge, as the event was called, was held at a prominent robotics conference later in the year. Teams competed for a $25,000 prize by designing a robot to identify and grasp items from one of Amazon’s storage shelves as quickly as possible (the winner picked and packed 10 items in 20 minutes). This might seem a trivial task for human workers, but figuring out how to grasp different objects arranged haphazardly on shelves in a real warehouse is still a formidable challenge for robot-kind. Cont'd...
Google to incubate its robotics and drone divisions under Google X
By Mike Wheatley for SiliconAngle: Google is planning an organizational reshuffle that will see its secretive robotics department and drone business folded into its Google X labs.
Google’s robotics division, and the drone group it created when it acquired Titan Aerospace in 2014, will both fall under the Google X umbrella when the reshuffle takes place some time next year, Re/Code reported.
Google X is the secretive part of Google that develops some of its most futuristic, bleeding edge technologies. These include its famous self-driving cars, Project Loon (Wi-Fi hot air balloons), and its airborne wind turbines. Google X operates as a standalone company under Google’s parent Alphabet Inc., which was created following Google’s corporate restructuring earlier this year.
Google X’s projects are largely experimental and extremely uncertain in terms of a business model. Nevertheless, Google obviously deems it the best place to be for its robotics division, which has been left leaderless ever since Andy Rubin quit the Web giant last year. Previously, there was speculation that the robotics division may become a standalone company under Alphabet, but today’s news would indicate that’s not going to happen any time soon. Cont'd...
Automating the Chemo Compounding Process
RIVA uses automation of sterile manipulations and isolation of the compounding area to solve major safety issues with manual compounding, which are accuracy of every dose measurements and assuring sterility of every finished compound.
Getting Started with Collaborative Robots - Part 3 - Get the team on board with robots
In this section, well discuss how to present the idea of automating your production with your workforce, and how to help diminish fears of working with robots.
Building the Steam Controller
From Valve:
When we first started designing hardware at Valve, we decided we wanted to try and do the manufacturing as well. To achieve our goal of a flexible controller, we felt it was important to have a similar amount of flexibility in our manufacturing process, and that meant looking into automated assembly lines. It turns out that most consumer hardware of this kind still has humans involved in stages throughout manufacturing, but we kind of went overboard, and built one of the largest fully automated assembly lines in the US. Our film crew recently put together a video of that assembly line, showcasing exactly why robots are awesome.
Getting Started with Collaborative Robots - Part 2 - How to Identify Potential Processes for Automation
At this point, we need to discuss the strengths and limitations of process automation with collaborative robots.
Getting Started with Collaborative Robots? Part 1 - What can collaborative robots do?
This is the first in a series of articles about Collaborative Robots
Think You Know Industrial Robots? Think Again
Jim Lawton for Forbes: Peter Drucker said “Culture eats strategy for breakfast” and in my experience there’s no industry where that wisdom holds more true than manufacturing. I’m not a hardened cynic, just a pragmatist, having spent the majority of my career bringing technology that disrupts the status quo – from inventory optimization and managing risk in the supply base to collaborative robots. Manufacturers are among the most skeptical buyers and for good reason – what they do is hard, complex and things are done the way they are done because it’s been proven to work. There are times though when the opportunity to transform the business is so compelling that – as Drucker said – executives need to spend whatever time is necessary to tear down the cultural barriers that are getting in the way of the strategy that capitalizes on the moment.
In the category of robotics and industrial automation, now is one of those times. It’s been more than 50 years since Unimate went to work at a GM plant unloading heavy parts and welding them onto automobile frames. Manufacturing has changed a lot and today is on an evolutionary path toward the 4th industrial revolution. Unfortunately, while executives may be ready to move quickly toward the factories of the future for first mover advantage, many automation engineers remain entrenched in 20th century thinking about robots — when they were highly customized solutions, designed to perform one task over and over again, with a price tag to match. Cont'd...
How Universal Robots Doubled Production at Tegra Medical
Medical device manufacturer Tegra Medical faced profit erosion as costs went up and customers demanded price cuts. Deploying three collaborative robot arms from Universal Robots to tend the machines manufacturingmedical instruments doubled throughput, freed up 11 full time positions and enabled the manufacturer to keep up with customer demand while keeping costs down.
MIP Robotics Launches Its First Model of New Generation Industrial Robot "MIP Junior",
MIP robotics is a startup founded in 2015 and based on research conducted for many years. The company aims to provide accessible, industrial robots, especially for SMIs (small and medium industries). In other words, like 3D printing in recent years, MIP wants to democratize industrial robotics.
The robots can be used to automate repetitive, arduous or dangerous tasks; indeed it is possible to set the standard gripper arms: suction cup, hook, screwdriver, blade etc. Application examples are numerous: storing goods in cartons, checking the tightening torque, making the automated cutting, removing non-compliant products etc. MIP allows its customers to increase their productivity (and hence margins) in order to improve the quality or reduce the hardship. The investment can be made profitable in only 6 month.
The "Junior " is a robot called "SCARA" (that is to say a horizontal arm) operating on a range of 600mm and fixed on a vertical axis in a standard 400mm high. These dimensions can be adjusted on demand. Its speed reaches up to 250mm/s with an accuracy of 0.5mm and can move up to 5kg. Junior is also characterized by its ease of use: for instance you can teach the robot the movements to be carried out by manually moving the robotic arm. Finally, the robot stops in case of impact, enabling collaborative applications if all safety conditions are met. While prices often start around €20,000 on the market, Junior is available from €8000. Full Press Release:
Drake: Robotics Planning, Control And Analysis Toolbox
From MIT:
Drake ("dragon" in Middle English) is a toolbox maintained by the Robot Locomotion Group at the MIT Computer Science and Artificial Intelligence Lab (CSAIL). It is a collection of tools for analyzing the dynamics of our robots and building control systems for them in MATLAB and C++, with a heavy emphasis on optimization-based design/analysis. Here is a quick summary of capabilities:
Simulation
Rigid-body dynamics including contact/collisions (hybrid+LCP) and kinematic loops
Basic aerodynamics/fluid dynamics
Sensor models (lidar, depth camera, imu, contact force/torque; cameras coming soon)
Hand-derived models for many canonical control dynamical systems
Easily add your own models/components
Some support for stochastic models
For all of the above we aim to expose sparsity and provide analytical gradients / symbolic analysis
Primary limitations: code is optimized for analysis / planning / control design (as opposed to speed, generality)...
... Most of these models/tools are described in the companion textbook from an MIT course/MOOC . We've also recently started populating the Drake Gallery (contributions welcome!)... ( git repo )
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