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At the beginning of the COVID-19 pandemic, car manufacturing companies such as Ford quickly shifted their production focus from automobiles to masks and ventilators. To make this switch possible, these companies relied on people working on an assemblyline. Two of these were the wedge and a pyramid shape with a curved keyhole.
Image: Amonthep/stock.adobe.com Discover how you can enhance and streamline your manufacturing operations, boost efficiency, and drive growth for medium to larger sized businesses. Taylor elaborates, “We work with ambitious manufacturers who are being held back by various common issues.
Capturing manual assembly data Silicon Valley startup Invisible AI helps manufacturers digitally capture data from manual assemblylines to provide valuable insights and drive improvements. You may have 20 or 50 cameras on a line, all communicating with each other, all on the same local network. Watch a demo.
Empowering a robot to ‘see’ allows it to precisely and consistently differentiate, pick, sort, move, weld or assemble various parts no matter their complexity. For instance, a multiple-step manual welding task on an automobile assemblyline might take ten ‘blind’ robots to perform since each part must be mounted in place before every weld.
The adoption of robotics helps to lower energy consumption in manufacturing. Compared to traditional assemblylines, considerable energy savings can be achieved through reduced heating. At the same time, robots work at high speed, increasing production rates so that manufacturing becomes more time- and energy-efficient.
AMR insights Autonomous mobile robots (AMRs) can play a key role in manufacturing because of their name: They’re autonomous and do not require constant human intervention the way an automated guided vehicle (AGV) would. Some AMRs can that meet these requirements, with capacity to handle payloads up to 1,000 kg and 360-deg obstacle detection.
AI-enabled mobile robots can transform sectors like discretemanufacturing, logistics and laboratories,” Segura said. It lifts all types of load carriers for easy implementation into existing industrial projects to optimize warehouse processes, streamline assemblylines and enhance complex material handling.
The research, part of NSF’s Future of Work at the Human-Technology Frontier program, will take a multidisciplinary approach with the help of Professors Bilge Mutlu (computer sciences), Shiyu Zhou (industrial and systems engineering) and Timothy Smeeding (public affairs), and Assistant Professor Lindsay Jacobs (public affairs).
Previous efforts to automate this process have relied largely on automating the assemblyline with one sample per chip moving through the entire data collection process. Conventional materials research requires a researcher to prepare a sample and then go through multiple steps to test each sample using different instruments.
Manufacturers of complex highly automated assemblylines, such as those used in Festo’s Scharnhausen Technology Plant to assemble VUVG valves, can reduce time to market by using the software. These assemblylines incorporate up to 20 handling gantries.
Courtesy: Massachusetts Institute of Technology (MIT) High and low grips Many modern robotic grippers are designed for relatively slow and precise tasks, such as repetitively fitting together the same parts on a a factory assemblyline.
Share Discretemanufacturing involves creating products by assembling individual, tangible parts. These parts are assembled in a specific sequence to produce the desired result. The production lines in discretemanufacturing produce products that are similar but not identical.
Mixed mode manufacturing refers to any production environment that uses more than one manufacturing mode and does so under the same roof or within the same system. For example, carrying out discretemanufacturing in one facility and process manufacturing in another is not mixed mode.
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