Sharona Hoffman’s picture

By: Sharona Hoffman

A career as a physician has traditionally been considered to be among the best vocations that talented students can pursue. That may no longer be the case. All too many doctors report that they are unhappy, frustrated, and even prepared to leave the profession.

That should worry all of us. The physician burnout crisis is likely to affect our quality of care and our access to healthcare providers.

According to a recent study, 44 percent of U.S. doctors suffered at least one symptom of burnout, and some studies have identified even higher burnout rates. By contrast, researchers have found only a 28-percent burnout rate in the general working population.

Jon Speer’s picture

By: Jon Speer

Medical device manufacturers must implement and maintain a quality management system to ensure they are producing safe and effective medical devices. Created and maintained by the International Organization for Standardization (ISO), standard 13485 outlines the guidelines for medical device quality management systems. ISO 13485:2016 has been adopted by regulatory agencies around the world as a universally harmonized standard.

However, the International Organization for Standardization itself is not a governing regulatory agency; unlike government agencies, ISO does not publish reports to the public of violations during audit findings. This fact makes it nearly impossible for device makers in this market to research and learn from others’ mistakes.

With more than 20 years of experience working in the medical device industry, I’ve seen my fair share of mistakes made during ISO 13485 implementation, with six mistakes in particular that commonly trip up device makers. You can learn from these missteps of others and avoid making them yourself:

Søren Block Olsen’s picture

By: Søren Block Olsen

Manufacturers face constant challenges of rising expectations as customers and regulators demand better quality and greater traceability throughout the supply chain. Exacerbating matters are unpredictable tariffs, which necessitate faster responses to changing trade barriers and regulatory requirements. These factors must all be accomplished at lower costs while coping with already thin margins.

The solutions to these challenges already exist within current systems. Unlocking the value of data already in systems generates actionable insights from quality control and quality assurance for operations and plant-floor management.

Improving the entire manufacturing process allows manufacturers to optimally monitor costs, remaining within a range of profitability. If data (i.e., business intelligence) show information outside the acceptable range, it can be quickly adjusted.

Multiple Authors
By: Jill Barshay, Sasha Aslanian

When Keenan Robinson started college in 2017, he knew the career he wanted. He’d gone to high school in a small town outside Atlanta. His parents had never finished college, and they always encouraged Robinson and his two older siblings to earn degrees. Robinson’s older brother was the first in the family to graduate. “My parents always stressed how powerful an education is and how it is the key to success,” Robinson says.

When Robinson arrived at Georgia State University in Atlanta, he wanted to major in nursing. “I always knew I had a passion for helping people,” he says. Biology had been his best subject in high school. “My dad, my mom would always kind of call me like the king of trivia because I’d always have just like random science facts.”

During his freshman year, Robinson earned a B average. But the university was closely tracking his academic performance and knew from 10 years of student records that Robinson wasn’t likely to make the cut for the nursing program.

Georgia State is one of a growing number of schools that have turned to big data to help them identify students who might be struggling—or soon be struggling—academically so the school can provide support before students drop out.

Ekim Saribardak’s picture

By: Ekim Saribardak

Transporting cargo over long distances has always been a logistical nightmare, but when the goods are of a delicate nature, the whole operation becomes significantly more challenging. Perishable foods, chemicals, pharmaceutical products, and other delicate goods all need special treatment during transportation to keep them in optimal condition; in many cases, constant monitoring of the cargo’s temperature is necessary to ensure its integrity until delivery.

Luckily, thanks to the technological advances of the last two decades, logistics companies no longer have to rely on rudimentary methods such as manually inspecting the cargo hold, which used to be a cause of excess downtime and loss of productivity, and wasn’t particularly reliable.

Andrew Edman’s picture

By: Andrew Edman

On factory floors all over the world, 3D printing has quietly moved from a prototyping novelty to an essential tool. Advances in printer technology and material science mean that today’s 3D printed parts are robust enough to hold up to real-world wear and tear, and precise enough for demanding production requirements. Today, when production engineers look to maintain quality, reduce cost, or boost efficiency, they are turning to 3D printing to get the job done on time and on budget.

Shortly after Ashley Furniture, the world’s largest furniture manufacturer, brought in the company’s first Formlabs stereolithography (SLA) 3D printer, one of their production engineers decided to try replacing machined alignment pins with 3D printed parts. If these held up to constant cycles and impact, the company could avoid the long lead times and minimum-order quantities of outsourcing the production of the alignment pins.

The engineer’s experiment was successful and led to more tests to find out where they could use 3D printing to improve fabrication and assembly processes. By examining how Ashley Furniture is driving best practices with 3D printing, we can better understand how to apply those insights to any manufacturing or assembly environment.

Peter Rose’s picture

By: Peter Rose

On May 26, 2020, the new European Union Medical Device Regulation (MDR) will finally take effect. By that date, all Class I manufacturers wishing to continue their trading activities within the EU market must have effectively completed the transition from the previous medical device directive and be fully compliant under EU MDR.

This statement alone may be surprising to certain Class I manufacturers, who assume that their products’ classification as low-risk devices under the previous directive will exempt them from all this EU MDR commotion. These presumptions are misguided because classification requirements listed in the EU MDR are relevant to all manufacturers, irrespective of past classification.

With this deadline in sight, it is crucial that all manufacturers familiarize themselves with these regulatory changes and promptly make a start on implementing necessary measures. Those that fail to achieve compliance on time will be left behind, and their products removed from the market. In light of this industry bustle, this article aims to advise Class I manufacturers about the primary alterations that the EU MDR will enforce, as well as offer practical steps that manufacturers can begin to follow.

Simon Côté’s picture

By: Simon Côté

The aerospace industry is known for manufacturing parts with critical dimensions and tight tolerances, all of which must undergo demanding inspections. Given the scale of the controls to be carried out on these parts, it is hardly surprising that quality people in the industry prefer to turn to coordinate measuring machines (CMMs). However, directing all inspections to the CMM may cause other problems: CMMs are hyper-loaded and can generate bottlenecks during inspections, slow down manufacturing processes, and cause production and delivery delays.

Is it possible to unload CMMs so that they are fully available for the final quality controls? How can we improve manufacturing processes to produce more parts faster, and above all, of better quality? In the event of a quality issue occurring during production, is it possible to identify the root cause more quickly to minimize the delays that could impact schedules and production deliveries?

Knowledge at Wharton’s picture

By: Knowledge at Wharton

From a lone statistician toiling over narrowly defined problems for the marketing department, to a C-level executive overseeing a mission-critical area impacting every function of the company, the meaning of “data and analytics professional” has changed a lot in recent years. A. Charles Thomas’s career has reflected those developments.

Thomas, who is General Motors’ first-ever chief data and analytics officer, shared where corporate data analytics has been, where it’s going, and the evolution of chief data officer roles, in a keynote at the recent Wharton Customer Analytics conference “Successful Applications of Analytics.” He spoke from his experience not only at GM, but also other major companies, including Hewlett Packard, the United Services Automobile Association (USAA), and Wells Fargo.

During the late 1990s, he said, data analysts were typically individual contributors working with transactional data involving marketing, credit, and retail. “The [data analyst’s] reputation was ‘a smart guy,’” said Thomas. “You want an answer, you come to Charles.”

Zach Winn’s picture

By: Zach Winn

Manufacturers are constantly tweaking their processes to get rid of waste and improve productivity. As such, the software they use should be as nimble and responsive as the operations on their factory floors.

Instead, much of the software in today’s factories is static. In many cases, it’s developed by an outside company to work in a broad range of factories, and implemented from the top down by executives who know software can help but don’t know how best to adopt it.

That’s where MIT spinout Tulip comes in. The company has developed a customizable manufacturing app platform that connects people, machines, and sensors to help optimize processes on a shop floor. Tulip’s apps provide workers with interactive instructions, quality checks, and a way to easily communicate with managers if something is wrong.

Managers, in turn, can make changes or additions to the apps in real-time and use Tulip’s analytics dashboard to pinpoint problems with machines and assembly processes.

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