Metal additive manufacturing (AM) is a process with demanding requirements for in-process material management, specifically with regard to the use of powdered metals. The Calibur3 system from Wayland Additive, enabled by the NeuBeam process, not only redefines how the electron beam (eBeam) process can be applied in a more stable and flexible way, but also offers a number of unprecedented powder-dispense capabilities for metal AM. 

The Calibur3 system allows users to measure powder dispensing and flow to optimize powder usage and extend overall powder recycling to achieve greater economies of scale. (There is an animation here.)

Wayland Additive has brought knowledgeable personnel on board to further the development of the NeuBeam process, the Calibur3 system, and the capabilities they can offer. Specific attention has been given to the disciplines of material science and mechanical engineering.

To enable raw water for use as cooling water, industrial facilities such as power, processing, and manufacturing plants prefilter raw water from rivers, lakes, gulfs, and coastlines to remove organic, aquatic, and other solids. It’s not as simple as it sounds.

The cooling water is typically used in a couple of ways. With once-through systems, water circulates through pipes, absorbing system heat before it is returned to its original source. Cooling towers can also utilize water from natural sources. These towers remove heat from machinery, heated process material/fluids, chillers, and other sources.

Industrial water filtration

Power plants with cooling towers as well as other industrial applications depend on reliable, efficient filtering of debris from the water to prevent excessive maintenance and downtime.

Because the cooling water originates from bodies of water, it can be dirty, with considerable debris, weeds, and trash. Strainers are required to remove the waste from the cooling water before it goes into heat exchangers and cooling systems, and to prevent spray nozzles from clogging.

If you’ve watched Grey’s Anatomy, then you’ve gotten a peek into the complex hierarchies that rule a hospital. Over 17 seasons, the show’s eponymous heroine, Meredith Grey, ascends from a lowly intern to chief of general surgery, learning from the presiding residents and older surgeons along the way. There’s rarely doubt about who is in charge, who has more expertise, or who should be supervising and training other staff.

Grey’s fictional journey illustrates the complicated dynamics of a healthcare setting, whether it’s a local clinic or a bustling city hospital. Doctors, nurses, other clinicians, and administrators are part of a system where tenure, expertise, and training dictate the chain of command. Those hierarchies can help teams provide care efficiently, but what happens when those traditional roles are disrupted?

Many techniques can be used to find the root causes of asset failures and other important events we want to analyze. Fault tree analysis is one of those techniques, and it is being utilized by many different companies to improve system reliability.

This guide aims to give a basic to intermediate introduction to the fault tree analysis process. It discusses uses cases, types, symbols, processes, examples, and helpful software solutions.

What is fault tree analysis?

Fault tree analysis (FTA) is a graphical as well as mathematical tool to analyze the potential for failure for a machine or a system. It is a top-down approach that tries to reverse engineer the root causes of a potential failure. It is used as a part of the root cause analysis process.

To meet increasingly strict compliance standards, such as the Food Safety Modernization Act (FSMA) and Global Food Safety Initiative (GFSI), food processors now regularly use adenosine triphosphate (ATP) testing to monitor equipment surfaces for microbial growth. Add to this the need to minimize cross-contamination of products or ingredients with allergens after production changeovers, and more processors are realizing that the traditional cumbersome means of cleaning conveying equipment may not be sufficient to meet today’s rigorous compliance requirements.

When conventional conveyors need to be disassembled, cleaned, and reassembled to reach all exposed internal surfaces, potential downtime can extend to days. If this proves too onerous, some food processors dedicate separate conveyor lines to specific products, which increases capital equipment costs, labor, and the production space required.

When Wharton management professor Adam Grant sat down to write his new book, Think Again: The Power of Knowing What You Don’t Know (Virgin Digital, 2021), he wanted to make the case for why executives should reconsider their approaches to how to manage people in a modern workplace and embrace new ideas, based on systematic evidence.

Grant is an internationally recognized thought leader in management and workplace dynamics, best-selling author, and the co-director of Wharton People Analytics. In an Ivy Exec webinar called “Inside the Mind of Professor Adam Grant” sponsored by the Wharton MBA for Executives Program, Grant sat down with Wharton dean Erika James, an organizational psychologist herself. The two discussed the importance of questioning your assumptions regarding how to engage and communicate in the workplace, to become a more evolved leader.

Following are five key takeaways from their discussion.

In 2017, in response to a Boston Dynamics video, billionaire Elon Musk infamously tweeted, “This is nothing. In a few years, that bot will move so fast you’ll need a strobe light to see it. Sweet dreams....”

Whether or not Musk’s ominous prediction comes true for Atlas (the robot in the video), he raises a good question. How critical is high speed in robotics?

Of course, when it comes to industrial robots, this question can mean close to nothing unless we define what type of robot we are concerned with and what application the robot is performing.

For example, speed considerations for a six-axis automotive paint robot are quite different from those of a delta robot performing assembly in an electronics factory. Applications such as painting and arc welding have maximum speeds due to the processes. A MIG welder can only lay down so many inches of bead per minute. A paint robot prioritizes smooth, sweeping motions over fast, jerky joint movements while spraying, for obvious reasons. But what about the many applications, such as pick-and-place or assembly, where there seems to be no ceiling to movement speed? Why don’t manufacturers choose robots that move so fast you can barely see them work?

Aresearch team has found that a method commonly used to skirt one of metal 3D printing’s biggest problems may be far from a silver bullet.

For manufacturers, 3D printing, or additive manufacturing, provides a means of building complex-shaped parts that are more durable, lighter and more environmentally friendly than those made through traditional methods. The industry is burgeoning, with some predicting it to double in size every three years, but growth often goes hand in hand with growing pains.

Residual stress, a by-product of the repeated heating and cooling inherent to metal printing processes, can introduce defects into parts and, in some cases, damage printers. To better understand how residual stress forms, and how it might be curbed, researchers at the National Institute of Standards and Technology (NIST), Lawrence Livermore National Laboratory, Los Alamos National Laboratory, and other institutions closely examined the effects of different printing patterns in titanium alloy parts made with a common laser-based method.

As a young man of 20 in his first job at a state-owned enterprise in China, Guoli Chen found senior management fascinating, but not in a good way. His boss’s boss did very little—unless one counts reading newspapers, drinking tea, and gossiping as work. “I wondered whether anyone could replace him without affecting the [organization’s] overall performance,” recalls Chen, now a professor of strategy at INSEAD.

He didn’t stick around to find out. After two years, Chen moved on. His second job couldn’t be more different, in culture as well as the lessons he learned. Working in an investment bank, Chen observed how the company’s venture capital arm picked firms chiefly on the strength of the founding team, especially the chief executive. “Given the uncertainty of the [firms’] business potential… the VC literally bet the success of their investments on the individual,” Chen says in an INSEAD Knowledge podcast.

In an essay titled “The end of artefacts,” Nobel laureate and National Institute of Standards and Technology (NIST) fellow William D. Phillips details how scientists came to realize the original vision of the metric system, or the International System of Units (SI)—a system of units “for all times, for all people.” With the redefinition of the kilogram in 2019, the new SI was rightly celebrated as a unifying achievement toward the democratization of science, with NIST and its international partners having collectively led the charge.