Mobile Computing – The Eyes That Empower People on the…

Mobile Computing – The Eyes That Empower People on the…

Aug 29, 2018

“Mobile Computing – The Eyes That Empower People on the Plant Floor” By Chris Ealahan, Sales Manager at Teguar Corporation Featured on Manufacturing.net The robots are taking over! Not so fast. In the real world of manufacturing, there is no man vs. machine terminator war when it comes to getting jobs done. Rather, there are functions that both sides do better than the other. A lot of these activities have to be done using on-the-spot deductive reasoning that, people, for the most part, are endowed with. The most successful manufacturing operations must have capable employees, but they must also be empowered to do their jobs. Just sending them out on the plant floor with a clipboard is not the way to do it. These technicians need ways to gather information and intervene when necessary that are as advanced as the systems they are interfacing. Mobile computing devices play a big role in enabling plant workers to stay on top of the operation as they traverse the vast expanse of the plant floor. People As Part of the System Just about all plants, regardless of size, are being managed with the help of Enterprise Resource Planning Software (ERP), such as Warehouse Management Systems. Enabling control and getting operational information to the ERP happens by the Industrial Internet of Things (IIoT), an array of connected electronics, site software, sensors, actuators, and connectors that make up its nerve system. The challenge has been getting sufficient visibility into the job at hand for the most efficient results. Advancements in cloud technology, independent of location, are providing real-time, contextual data directly to technicians’ devices. As a result, IIoT connected processes enable information-sharing and increase collaboration, along with helping technicians understand cause and effect. The job experience changes from simply receiving and completing tasks, to demonstrating increased levels of responsibility and increased comprehension of the system as a whole. Mobile Computing: the Tool for Accessing the ERP System Not too long ago, workers were discouraged from bringing cell phones and tablets into the work place, over a concern about distractions. A growing number of employees are being wired. Management is beginning to relent on the device ban and is slowly coming to...

Taking IIoT to the Edge

Taking IIoT to the Edge

Jul 25, 2018

By Jeff Reinke, Industrial Equipment News (IEN) Edge computing’s ability to supply real-time, plant-floor data will continue to drive it forward. The Industrial Internet of Things has unlocked a number of opportunities that the manufacturing sector can now leverage in streamlining operations, improving quality and cutting costs. However, perhaps the most unique benefit of the IIoT has been the ability to customize the application of these technologies according to the needs and preferences of a specific enterprise – even as the number of solutions falling under the scope of IIoT continues to expand. To discuss one such example, IEN recently sat down with John Fryer, senior director of industry solutions at Stratus, to discuss best practices for leveraging IIoT capabilities with Edge Computing strategies.  Jeff Reinke, IEN Editorial Director: The concept of a connected enterprise has been around for a while, but what do you think were the driving factors that brought the term “Internet of Things” into manufacturing’s lexicon? John Fryer, Senior Director of Industry Solutions, Status: Firstly, we should not forget that “connectivity” and “analytics” have been key components of industrial automation implementations since the first uses of digital controls over 40 years ago. PLC’s have been used to control plant floor activities in many industries, but often in isolated silos. The key elements of the “Internet of Things” are ubiquitous connectivity, almost unlimited computing power and advanced analytics, often using machine learning and artificial intelligence technologies. The advent of the Internet has driven exponential growth in digital connectivity, primarily in human to machine interaction. In recent years, this has been extended to machine-to-machine interaction and the introduction of machine learning to enable automated control of “things”. Perhaps the best examples are self-learning thermostats in homes, which can also be connected to safety systems, such as fire alarms.  Providing plant-wide connectivity with standard technologies, such as Ethernet (or variants) and using the Internet Protocols (IP) enables interconnection of disparate systems, both within the plant, and between plants and Enterprise systems. This makes it easier to deploy additional computing power at the Edge, within a plant, or in the Cloud, and to apply analytic and machine learning technologies to improve a whole range of production and business processes....

Desktop 3D Printer Offers Speed, Precision, Ability to Work in…

Desktop 3D Printer Offers Speed, Precision, Ability to Work in…

Jun 18, 2018

“Desktop 3D Printer Offers Speed, Precision, Ability to Work in Metal” Featured on D2PMagazine.com Airwolf 3D calls its newly released EVO a rugged ‘additive manufacturing center’ that is powered by an automotive-grade microcontroller FOUNTAIN VALLEY, Calif.—Airwolf 3D recently released EVO, its 5th generation 3D printer that is said to be so advanced that Airwolf calls it a desktop “Additive Manufacturing Center,” or AMC. “The EVO is completely new and it’s unlike anything out there,” said Airwolf 3D Co-Founder and CEO Erick Wolf, in a company release. “We took the technology that we perfected with our prosumer line of 3D printers and leveraged it to develop a machine that’s light years beyond anything else on the market. The EVO is faster, stronger, and more accurate than any desktop 3D printer—it delivers a premium 3D manufacturing experience at less than half the cost of machines that offer equivalent performance. Plus, it’s packed with new technology that dramatically changes the way we manufacture, including the ability to work in metals. The EVO far surpasses the capabilities of a traditional desktop 3D printer. It’s a true desktop Additive Manufacturing Center.” The EVO possesses Airwolf 3D’s signature suite of features—auto-leveling, large build size, high-temperature multi-material printing, and compatibility with water-soluble Hydrofill support material—but in an ultra-ruggedized unit that includes cutting-edge features available only from Airwolf 3D. Most notable among these is the industry-first PartSave™. Nicknamed “Zombie Mode,” PartSave solves one of the most frustrating problems with 3D printing. There are few things more disheartening than 3D printing a part for hours, only to have it fail completely if the printer stops because of a power outage or unplugging the machine. With PartSave, once power is restored, the machine resumes where it left off, enabling the part to finish. Another industry-first feature, the company said, is FailSafe™. If you run out of filament or experience a jam, FailSafe™ has you covered. Just place the print head at the height you left off and FailSafe will do the rest, restoring your print and completing the job with time to spare, according to Airwolf. The EVO also ships with a full-color 7–inch Matrix touchscreen display, new Tri-Heat™ Enclosed Build Environment, an oversized...

Smart manufacturing technology is changing business…

Smart manufacturing technology is changing business…

May 30, 2018

“Smart manufacturing technology is changing business processes” By Jim O’Donnell, TechTarget The future is here: AI enablement and smart manufacturing technologies are transforming business systems today, according to technology futurist Jack Shaw. Imagine a scenario where a plane in midflight from Paris to Boston gets a signal from an embedded sensor in an engine fuel nozzle that indicates excessive wear. Once the plane lands, it will need to be taken out of service for hours or even days as the airline locates and installs a replacement part. The entire process is time-consuming, expensive and inconvenient for passengers and crews. But thanks to smart manufacturing technology and AI-enabled business processes and systems, there is a better way, according to technology futurist and consultant Jack Shaw. The digital transformation to an AI-enabled business ecosystem is happening now, Shaw said in a presentation at the Smart Manufacturing Experience conference this month in Boston. An autonomous self-contained process Rather than the current costly and time-consuming process, the smart manufacturing technology ecosystem encompasses a self-contained and autonomous parts replacement process. To start the process, industrial IoT (IIoT) smart sensor circuitry in the engine’s nozzle triggers the aircraft’s autonomous maintenance system, which then messages the airline’s global maintenance system that the part will be needed when the plane lands in Boston, Shaw said. The airline’s global procurement system is notified. It scours thousands of websites to identify Federal Aviation Administration (FAA)-certified parts suppliers, negotiates the terms with the supplier’s AI-enabled order management system and executes a smart contract to procure the part. Once the procurement contract is authorized, a design file of the fuel nozzle part is downloaded to a 3D printer located near the Boston airport. The entire process — from the identification of a part defect to the design download to the 3D printer — takes less than four minutes and requires no human intervention, according to Shaw. But the smart manufacturing technology and AI-enabled ecosystem is not finished. Automatic procurement processes identify and select technical engineers who are experienced with replacing this particular part and available to do the work. The technical engineer who installs the part then uses augmented reality (AR) goggles that display a 3D video of the entire replacement process directly on...

How Factory Intelligence is Evolving

How Factory Intelligence is Evolving

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...