Feb 19, 2019

“Disruptive Technologies Are Changing Automakers’ Needs, Creating Opportunities for Suppliers” Autonomous, electric, and connected vehicles require new designs, new suppliers By Mark Shortt, Design-2-Part Magazine   Carmakers in North America, Europe, and Asia are doing a lot of things today that they’ve never done, or even attempted to do, before. When you consider that the crown jewel of their research and development efforts—self-driving cars—is rewriting the rules of how cars are designed, manufactured, and used, that starts to make more sense. “When you look at autonomous driving, it still is amazing to me that you could sit in a car and it drives itself,” said Ken Beller, vice president of sales and marketing at The Weiss-Aug Group, a group of manufacturing companies headquartered in East Hanover, New Jersey. “It stops at red lights and parks itself, and that’s truly amazing.” Self-driving, or autonomous, cars are part of a larger trend currently sweeping the global automotive industry: the development of what are known as ACES—automated, connected, electric, and shared—vehicles. In a major announcement last March, General Motors said that it plans to begin producing self-driving cars, without steering wheels or pedals, in 2019. Along with the car, GM plans to start a commercial service centered on an app that enables people to hail rides. General Motors said that the car, the Cruise AV (autonomous vehicle), is based on its Chevrolet Bolt electric vehicle (EV). It will be produced at the same plant where the Bolt EV is produced—GM’s Orion Township plant in Michigan. GM took a major step toward commercialization of the vehicle after it acquired Cruise Automation, a San Francisco-based developer of autonomous vehicle technology, in 2016. The car is part of GM’s efforts to enable a future with “zero crashes, zero emissions, and zero congestion.” General Motors’ efforts to commercialize autonomous cars at scale were bolstered last May, when the SoftBank Vision Fund announced that it would invest $2.25 billion in GM Cruise Holdings LLC (GM Cruise). In a statement announcing the funding, Michael Ronen, managing partner of SoftBank Investment Advisers, said that “GM has made significant progress toward realizing the dream of completely automated driving to dramatically reduce fatalities, emissions, and congestion. The GM Cruise...

Dec 18, 2018

By Jeff Reinke, ThomasNet Redford, Michigan, is the new home of Ford’s Advanced Manufacturing Center, focused on improving the company’s approach to building cars and trucks. The $45 million complex houses 100 experts working on integration strategies for various cutting-edge manufacturing technologies, including 3D printing, augmented reality (AR) and virtual reality (VR), robotics, and digital manufacturing. The Advanced Manufacturing Center contains 23 3D printing machines, and Ford is working with 10 3D manufacturing companies to develop applications with a range of different materials, from nylon powder to sand to carbon. One application currently under development could save the company more than $2 million. The soon-to-be-released Ford Shelby Mustang GT500 features two 3D-printed brake parts, while the F-150 Raptor includes a 3D-printed interior part. The company believes that as this technology becomes more economical, the use of such parts will become more and more prevalent. Assembly line workers at the Michigan Assembly Plant, where Ford builds the Ranger pickup, use five different 3D-printed tools that played a critical role in the launch of the Ranger. In fact, the company says that these tools knocked off weeks from an already tight timeline. Ford is also banking on augmented and virtual reality to help in simulating and designing assembly lines. By donning specialized gaming equipment, engineers can configure a virtual reality production line without leaving the Center, allowing engineers to identify potentially unsafe processes and fine-tune workflows long before an assembly line is put into play. AR and VR can also allow manufacturing teams to work collaboratively in facilities around the world, meaning employees on different continents could work in the same virtual space, at the same time. Finally, the new facility will allow the company to optimize the use of collaborative robots. Ford has more than 100 of them in 24 plants globally. For instance, at the Livonia Transmission Plant in Michigan, a co-bot performs a job that was so ergonomically difficult for employees that they could only perform that task for one hour at a time. The co-bot was a welcome addition to the production line. These co-bots also help the automaker reduce costs by eliminating the safety cages required by larger robots. Utilizing co-bots in...

Dec 17, 2018

Industrial robots are driving improvements in productivity, quality, and flexibility that are helping U.S. manufacturers to compete globally. At the same time, they’re spurring the growth of a new ecosystem of jobs, from mechanical design to AI-based computer vision. By Mark Shortt, Design-2-Part Magazine The robots are coming—that much is true. But manufacturers, by and large, don’t see them as the job-stealing invaders of the workplace that many people have imagined. It’s not that robots don’t excel in performing many tasks formerly done by people. It’s just that people also excel in certain areas where robots aren’t up to the task. And  in the manufacturing realm, industry leaders and company officials who have integrated robots into their plant’s operations say that their impact stretches well beyond the work that they’ve proven to do so well.   “These machines are going to have a huge impact into the broader economy,” said Tom Galluzzo, founder and chief technology officer of IAM Robotics, in a presentation at MIT Technology Review’s EmTech Next Conference in Cambridge, Massachusetts, in June. “They’re going to empower people to do the things that we’re innately better at—the creative thinking skills. And I think that’s where our employers have to take responsibility—to educate people and to empower them to do those kinds of creative thinking.” In manufacturing, people can focus on higher-level work because industrial robots are known to perform repetitive tasks with greater precision than their human counterparts. Manufacturers who use robotics in printed circuit board assembly, for example, often report greater peace of mind knowing that the robots are maintaining high quality while increasing the productivity of their operations. Sam Hanna, president of Quality Manufacturing Services, Inc. (QMS), a provider of electronics manufacturing services in Lake Mary, Florida, said that QMS has added robotics to its operation when a reasonable return on investment has justified the investment. The company has invested heavily in late-model surface mount pick-and-place equipment, a key contributor to quality as electronic components and packages continue to shrink in size. “We get consistent output, the machines never get tired, and they’re certainly faster than humans,” said Hanna. “The precision we can get out of machinery is far better than we can get out of...

May 23, 2018

By Larry Maggiano, Senior Systems Analyst, Mitutoyo America Corp. Featured on AdvancedManufacturing.org Intelligent factories have existed since manufacturing’s historical inception, but intelligence—defined as the acquisition and application of manufacturing knowledge—resided only with the factory’s staff. With the advent of numerical control (NC) and then computer numerical control (CNC) technologies, factory machines gained digital I/O capabilities but were still not smart. Digitally enabled machines, though increasingly productive, had no awareness of themselves, their environment, or the tasks being performed or to-be performed. In spite of these limitations, centralized factory intelligence has been achieved at modest scales through a deterministic low-level set of digital commands and responses. An experiment in large-scale centralized factory intelligence was General Motor’s 1982 Manufacturing Automation Protocol (MAP), operating over token bus network protocol (IEE 802.4). The MAP-enabled factory intelligence experiment ended in 2004 as it was difficult to maintain operational reliability. One of the most important reasons was a lack of system resiliency, a downside of required deterministic factory communication standards and protocols. Another reason was that the connected machines could not continue to operate at any level when instructions were not forthcoming from a central system. An analogy might be made to the mainframe-to-terminal infrastructure that became obsolete in the 1990s with the development of the PC and distributed computing. Several significant changes have enabled the development of smart machines for the intelligent factory. The first is the extension of IT’s ubiquitous Ethernet LAN infrastructure to the shop floor, enabling rapid 3D downloads of model-based definition (MBD), and uploads of process and product data. Secondly, today’s digital twins are smart in that they possess an awareness of not only their capabilities and operational status, but of work that can be performed on any particular MBD. In this manner, smart machines can bid on tasks, much like their human partners. A smart machine’s digital twin does not need deterministic low-level instructions, but instead responds to a submitted MBD, and, if selected, does real work with its physical counterpart. Lastly, three standardized core technologies–HTML, CSS and JavaScript—are recognized as enabling the widespread adoption of the Internet and the emergence of intelligent global systems. It is envisioned that similar standardized core technologies will enable...

Mar 7, 2018

By Ken Koenemann – VP of Supply Chain and Technologies, TBM Consulting Group Featured on Advancedmanufacturing.org Analytics solutions. The industrial Internet of Things. Robotics. Automation. Manufacturers looking for tech solutions that will help them control costs and gain a competitive edge have many great options. In fact, deciding what type of technology to invest in and why can seem overwhelming. Could you get a better ROI through automation and improved productivity, or through using analytics to identify inefficiencies and streamline processes? To glean the most from almost any new technology, make sure you have: A clear understanding of what’s happening in your business A vision for what you want the technology to do and why The right process structure and skill sets along with team alignment. Before investing in any new technology, ask these questions: What are the key drivers of operational and financial performance for your business? Do you clearly understand performance levels, reasons for misses and have processes for correcting them? Many manufacturers regularly fall short of their strategic goals, and it’s a good bet most of them also struggle with these questions. A lack of data usually isn’t the issue. Most manufacturing environments usually include some combination of ERP, CRM, CMMS, EMS and financial reporting systems and spreadsheets. The problem is the long time it takes to gather and analyze key performance indicators from the various sources. When that’s the case, predictive technology is invaluable and probably your best next investment: It will help you better understand what’s happening in your business and why to keep strategic goals on track, and it will position you to apply new technologies more effectively moving forward. Many cloud-based predictive solutions are also more versatile and relatively inexpensive and easy to implement compared with, say, a behind-the-firewall solution. Moreover, a well-executed solution can delivery similar types of insights quicker due to a shorter implementation timeline. Predictive solutions are helpful because they can help you improve understanding of most facets of your operations, from sales trends to reasons for downtime. One manufacturer with which TBM is familiar was regularly losing a day’s worth of production every few months, which added up to several hundred thousand dollars...