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August 26, 2019 |
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In this Issue
• Continuous Asset Optimization in Manufacturing
• How Machine Learning Is Revolutionizing Manufacturing In 2019
• New 'Smart Window' Material Selectively Blocks Light and/or Heat
• What 5G Means for Manufacturing
• More Stories
Industry News
Continuous Asset Optimization in Manufacturing
Continuous asset optimization (CAO) mixes smart manufacturing technologies with modern statistical, data-driven, and physics of failure modeling. Realizing CAO involves four distinct layers of data processing, with the lowest being the operations layer. The plant's operational data is acquired for analyzing the performance of an asset in the performance layer. The digital twin for CAO is vertically integrated, with operational data available in the operations layer employed for continuous computation of the "current values" of the internal state variables, which is a series of factors that define or determine the optimal performance of an asset or its sub-processes at any given time. The computed "current values" of the state variables are supplied as inputs to the optimization layer, which consists of an archive of models for the individual sub-processes defining the asset's operation. These models will express the current state of optimality of each sub-process based on an objective function. The sub-processes' future behavior is algorithmically predicted from this outcome and the knowledge of the sequence of discrete states possible from the current state. The composite behavior of the overall system is synthesized from the individual outcomes of the sub-processes, to form the final prediction layer.
Control Engineering (08/17/19) Seshan, Ananth
How Machine Learning Is Revolutionizing Manufacturing In 2019
The leading growth strategy for manufacturers in 2019 is improving shop floor productivity by investing in machine learning platforms that deliver the insights needed to improve product quality and production yields. Deloitte notes machine learning improves product quality up to 35 percent in discrete manufacturing industries. Forty-eight percent of Japanese manufacturers are seeing greater opportunities to integrate machine learning and digital manufacturing techniques into their operations than initially believed according to McKinsey. Using machine learning to streamline every phase of production, starting with inbound supplier quality through manufacturing scheduling to fulfillment is now a priority in manufacturing. According to a recent survey by Deloitte, machine learning is reducing unplanned machinery downtime between 15 – 30 percent, increasing production throughput by 20 percent, reducing maintenance costs 30 percent and delivering up to a 35 percent increase in quality. Manufacturers are gaining new insights into how they can become more sustainable using machine learning and predictive analytics that scale on cloud platforms. Discrete and process manufacturers who rely on heavy assets are using AI and machine learning to improve throughput, energy consumption, and profit per hour. Machine learning has the potential to reduce manufacturing’s chronic labor shortage while finding new ways to retain employees at the same time.
Forbes (08/11/19) Columbus, Louis
New 'Smart Window' Material Selectively Blocks Light and/or Heat
Researchers at the University of Texas at Austin's (UTA) Cockrell School of Engineering have created "smart window" technology that lets light penetrate while impeding heat, as well as the reverse. The work builds on a "smart" glass coating that could block visible light, near-infrared light (NIR), or both. The team embedded indium tin oxide nanocrystals in glass impregnated with niobium oxide, and produced an electrochromic material that can transmit or block light based on the electric potential applied. Later advancements yielded materials that can selectively allow the passage of light while blocking heat, and block light while permitting heat through. These new materials permit control of up to 90 percent of NIR and 80 percent of visible light, while transitioning between cool and warm modes takes only minutes. Designed with a porous, interpenetrating network, the material offers channels for electronic and ionic change, to facilitate selective blocking of light and/or NIR through different applied voltages. "These two advancements show that sophisticated dynamic control of sunlight is possible," says UTA's Delia Milliron. "We believe our deliberately crafted nanocrystal-based materials could meet the performance and cost targets needed to progress toward commercialization of smart windows."
New Atlas (07/24/19)
What 5G Means for Manufacturing
5G is expected to propel innovation across multiple fields, including manufacturing, where it is already being implemented and experimented with in efforts to improve efficiency, prevent maintenance, and generally lower costs associated with the manufacturing process. Jonathan Wilkins, director of global machine supply firm EU Automation says, “The technology could bring about a fundamental change in how manufacturers operate,” noting that 5G connectivity speeds open the door to building real smart factories. "Smart factories" will employ technologies like artificial intelligence (AI), robotics, analytics, big data, and the Internet of Things (IoT) and will be able to run mostly autonomously with the ability to self-correct. The concept of the smart factory has been around for quite some time, but technology and connectivity limitations have held back development. Wilkins explains, “Although 3G and 4G offered incremental improvements in speed and bandwidth, 5G will be the first cellular, wireless platform to offer reliable machine-to-machine and Industrial IoT systems.” The ability to handle more data traffic is also vital to the future of smart factories. 5G provides the connectivity parameters needed for reliable automated systems of the near future. Early studies by the American Society for Quality have shown smart manufacturing has increased efficiency for 82 percent of early adopters polled. Of those surveyed, 49 percent reported lower product defects and 45 percent said they had higher customer satisfaction.
Energy & Capital (07/24/19) Burgess, Luke
Virtual Reality's Benefits for Machine Maintenance in Processing Applications
Virtual reality (VR) and augmented reality (AR) can assist industrial maintenance engineers in process industries and reduce downtime for repairs. Maintenance staff can employ a VR headset or even their mobile phones to receive an augmented view of equipment, spotlighting the performance data of individual components and the best way to access them. The value of AR in machinery maintenance applies to any manufacturer with high levels of automation. AR is useful for locating malfunctioning equipment and the best means of accessing it, enabling the repair and maintenance process to accelerate, thus reducing the cost of sudden downtime. A purpose-built AR application enables engineers to view real-time system data from the industrial Internet of Things platform and visualize deficient components, so they can then make corrections with minimal disruption.
Control Engineering (08/20/19) Walker, George
Making Things Work as Part of the IIoT
The smart devices that comprise the Internet of Things (IoT) do not always have to be new. Experts say it is possible to give visibility to existing legacy devices for the purposes of improving overall equipment effectiveness (OEE) and giving control engineers greater visibility across the plant floor. Doing so can also enhance real-time performance monitoring, offer a real-time warning mechanism, and enable process analysis for predictive maintenance. "So, making the 'things' in the system smarter—by connecting them and gathering their valuable data—is the first step towards successful IIoT solutions," says Ivana Nikic, product marketing engineer at Moxa. Nikic adds, "Data analysis and artificial intelligence (AI) are now being used to study and adapt the manufacturing process automatically." Brendan O'Dowd, general manager at Analog Devices, says the proliferation of miniature and high performance semiconductor sensors, along with more extensive connectedness, is generating more data on machine and process performance. As a result, factories will become more agile and responsive to demands, more automated, require fewer human operators, and face less disruption. Meanwhile, legacy communication protocols between sensor nodes and PLCs, such as 4 to 20 mA control loops, are being replaced by ultrafast industrial variants of the Ethernet protocol. This will enable the rising integration of operational technology infrastructure in the factory with information technology in the enterprise.
Plant Engineering (07/30/19) Gill, Suzanne
The Importance of Closed-Loop Control in Directed Energy Deposition Additive Manufacturing
Sciaky Inc., a maker of Electron Beam Additive Manufacturing (EBAM) machines, says closed-loop control (CLC) is necessary to achieve quality in directed energy deposition (DED) processes. Sciaky has developed an Interlayer Realtime Imaging and Sensing System (IRISS) to remove variability in layer geometry, mechanical properties, microstructure, and chemistry of parts. The company believes the chief hurdle to the adoption of metal additive manufacturing (AM) is achieving effective control of settings and parameters. John O'Hara, global sales director at Sciaky, observes, "With each successive layer, the energy required to create and maintain the meltpool decreases. IRISS, our CLC, monitors the effects of this on the meltpool, and uses that information to change the inputs to the process in real time." He points out that on lengthy multi-day prints, it is costly if a power failure or any other stoppage occurs, causing parts to be scrapped. O'Hara says, "With IRISS, our CLC, the machine can see that although the last layer was printed at 8 kilowatts, now the meltpool isn't there and the entire part has cooled. It must ramp back up to 12 kilowatts because we're printing out a room temperature part now." Another advantage of the EBAM process is the ability to mix metal wire stock in-situ to create alloys in the meltpool. "What's interesting with this in-situ alloy mixing is that you can print with every layer having a different ratio," according to O'Hara.
Engineering.com (07/29/19) Maw, Isaac
Industry 4.0: Stop Letting Your Suppliers Own Your CAD
A company's control of its computer-aided design (CAD) technology is a valuable asset, says Aaron Hurd at Blueprint. He says suppliers want to own companies' CAD for parts because it creates a lucrative supplier relationship. For companies that lack access to their CAD files, using additive manufacturing becomes difficult for such use cases as tooling, job aids, and custom fixturing. Getting out of an existing supplier relationship when a supplier owns a company's data is challenging. Options include reengineering or reverse-engineering, or renegotiating supply contracts and exchanging designs for additional production volume. Companies should implement business rules and controls to ensure that CAD is captured for all designed parts prior to sourcing, centralize storage of CAD files, and include CAD capture as part of their engineering release processes. This can be achieved by various engineering systems, but even a SharePoint repository with basic version control could be used for smaller engineering organizations. Companies should also enforce a clause stating they own the intellectual property, including all drawings, designs, and CAD for the parts designed on their behalf. Hurd says Blueprint has seen major opportunities to use additive in product innovation, continuous improvement, and supply chain impeded when clients were unable to access their CAD and engineering designs.
3Dprint.com (08/05/19) Hurd, Aaron
Achieving Energy Efficiency Through Industry 4.0
Compressed air is a necessary component of automation that is commonly used in pharmaceutical, biological, and cosmetic production. The standard convention for monitoring compressed air has been with pressure sensors on the air preparation units. However, measuring air pressure only addresses part of the system, as air flow rates and volumetric consumption are also important. A new component, Festo's E2M module, brings air flow monitoring and measuring capabilities to process manufacturers, furthering current proficiencies and delivering new opportunities for efficiency, and enhanced energy and revenue savings. Data from the E2M module is brought onto a standardized, cloud-based dashboard for easy monitoring and benchmarking with Festo's IoT Gateway. This allows users to analyze trends, issue early warnings, and establish incident notifications. This process results in a true Industry 4.0 solution that can bring immediate benefits to a pharmaceutical, biological, or cosmetic facility. Fully integrated installation can have the same benefits as autonomous installation, with a few additions such as the measurement of pressure changes and automatic shutdown when the system is not in production or process. Easy and timely access to compressed air consumption data can lead to improved environmental footprints, lower energy costs, improved efficiency through predictive maintenance, and bolstered bottom lines.
Automation World (08/16/19) Correia, Craig
How Safe is Your Data in Industry 4.0?
The manufacturing industry is one of the most targeted sectors for cyberattacks. A recent MakeUK survey found that 48 percent of manufacturers have been subject to a cyberattack. These attacks wreak havoc on the victims, costing billions of dollars worldwide. The attacks can come in many forms, such as phishing scams, ransomware, and malicious software. A common principle in engineering is that, as a system gets more complex, the number of ways in which it can fail also increases. That is what happens when predictive maintenance and Industry 4.0 are introduced to any production environment. While this added layer of complexity bring several benefits, it also makes the entire system more vulnerable to cybersecurity threats. "It is frightening to imagine what could happen if a cybercriminal broke into an Industry 4.0 plant system environment to access and control each and every device associated with the local area network," says functional safety consultant Rafal Selega. While tehre is not a quick fix solution to the problem of data security, an general approach should include four steps: develop a security strategy early; map the system; follow industry standards; and pick software providers carefully.
Electronic Products & Technology (08/06/19) Christiansen, Bryan
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