Donald J. Wheeler’s picture

By: Donald J. Wheeler

On Sept. 29, 2020, the recorded worldwide death toll from Covid-19 reached 1 million. Six days earlier the United States reached 200,000 Covid-related deaths. So how did the United States with only 4 percent of the world’s population manage to capture 20 percent of the world’s deaths in this pandemic?

The 19 countries listed in figure 1 account for 85 percent of the Covid-related deaths worldwide, as reported by the European CDC. Here we can see how the U.S. death toll exceeds all others.

 
Figure 1: Number of Covid-related deaths reported by 19 countries as of Sept. 26, 2020

The short explanation for this dubious achievement is that between April 1 and the present, the United States had an average of 27 percent of the worldwide total number of confirmed cases of Covid-19. With that kind of market share, the high death toll was sure to follow. But a more detailed answer requires that we look at the number of deaths per capita and the rate at which these death tolls are growing.

Celia Paulsen’s picture

By: Celia Paulsen

A survey from 2014 found that small and medium-sized manufacturers do not like to compromise on quality when it comes to communications devices, vehicles, or tea (yes, tea—the survey respondents were probably British) but were more likely to skimp when it came to things like manufacturing equipment. Whether it is a new computer for the office or a welding station for the shop floor, purchasing new equipment is a decision about risk. A poor purchasing decision can result in a waste of resources and possibly a safety or cybersecurity incident.

Before you purchase or otherwise acquire a piece of equipment, whether it be a CNC machine or a cell phone, there are a lot of things to consider: How will it be financed? What special safety or cybersecurity concerns come with it? What will maintenance look like? How long is it expected to last?

It can be easy to overlook some aspect of risk involved in a purchase decision when overwhelmed with options. It can be especially difficult to know what to buy when comparing three different products that seem very similar.

NIST MEP has created a pre-purchase guide that might help.

Eric Weisbrod’s picture

By: Eric Weisbrod

The idea of digital transformation can be scary. The growth of technology is outpacing a comfortable pace of adoption for many manufacturers. But remaining content with the status quo often means being left behind. Digital transformation has become an imperative to give manufacturing organizations the flexibility and agility required to overcome business disruptions and adapt to rapidly changing and demanding global markets.

Digital transformation of quality management is a process that depends on something you already have: quality data. Your quality management system is key to optimizing all your quality operations, including supplier and materials management, production processes, quality checks, packaging, and shipping.

InfinityQS calls this holistic approach “manufacturing optimization.” It starts with improving the way you use data to answer the strategic, big-picture questions that truly matter to your business.

Limits of the status quo

The barriers to transformation are often a result of operational and resource challenges that typically boil down to one thing: everyone’s plate is already full. Whether managing and maintaining servers and IT projects, or running day-to-day production, no one has the time to take on new transformation projects.

Steve Wise’s picture

By: Steve Wise

The importance of data analysis in manufacturing operations can’t be overstated. Over the years, manufacturers have used statistical process control (SPC) methods and tools to study historical data and reveal differences between comparable items: shifts, products, machines, processes, plants, lot codes, and more.

The foundational benefit of statistical methods is predicting future behavior from historical data. That’s why control charts, box-and-whisker plots, Pareto charts, and the like are so valuable: They indicate that if processes are not changed, then performance (positive or negative) will continue as it is.

Control charts are brilliant tools for assessing performance over time, and their related “control limits” are predictions of normal future behavior. The problem is that many SPC software products struggle to move beyond just data collection to offer truly insightful data analysis.

Multiple Authors
By: Dirk Dusharme @ Quality Digest, Jason Chester

In previous articles of this series, we discussed how to master quality at the tactical and strategic levels. If you are like most readers, you probably nodded your head through article two’s tactical shop-floor view and vigorously shook your head through article three’s strategic view because your organization has the same challenges.

There is understandable hesitation from nearly any organization to make the transition to ultimately master quality at the enterprise level. This hesitation stems from organizations trying to view this transition as an all-or-nothing endeavor. As a result, that gets people seeing roadblocks that don’t necessarily exist.

Let’s take a look at a few.

Solve all the deployment issues in advance

Because previous deployments took a tremendous amount of time, resources, and expense, most organizations want to address every deployment problem before they even begin considering strategy.

That won’t happen. Ever. No matter what system you deploy, you will discover and learn things you could never have anticipated up front.

Jason Stoughton’s picture

By: Jason Stoughton

Remember that documentary you saw that finally explained metrology and why measurements are critical to practically every aspect of modern life? Yeah, neither do I. Probably because that documentary doesn’t exist... or does it?

The Last Artifact, a new one-hour film that PBS stations started broadcasting in September 2020, aims to fill that cinematic void by bringing metrology to the people. It tells the tale of measurement science and features researchers from metrology laboratories around the world, including several faces from the National Institute of Standards and Technology (NIST).


The crew of
The Last Artifact films NIST’s Kibble balance, a complex instrument used in the redefinition of the kilogram. From left, NIST researchers Stephan Schlamminger and Darine Haddad, sound recordist Parker Brown, director of photography Rick Smith, and co-director/producer Jaime Jacobsen. Credit: J. Stoughton/NIST

Jason Chester’s picture

By: Jason Chester

Before we get into a case study about how enterprisewide SPC software would work on both the shop floor and the C-suite, let’s talk about a long-held bias about “blue-collar” workers: That because they’ve traditionally been associated with manual labor, they should use manual tools; “white-collar” front-office workers, on the other hand, need the slick technology tools.

Imagine walking around the offices of a large manufacturing organization and finding salespeople managing customers’ information using a Rolodex. In a planning meeting, the CEO is using acetates on an overhead projector. In the procurement office, staff are issuing purchase orders using a Telex machine.

Now imagine walking the plant floor at that same manufacturer. The production supervisor is writing machine settings for the next shift on a board next to the machine. The quality engineer is writing the results of a critical quality check on a clipboard with a blunt pencil. A bunch of people stand around murmuring, scratching their heads, and wondering why a machine isn’t working properly.

In the first example, you might think you’d traveled back in time. The scenes are absurd. But the second example is a common reality.

Multiple Authors
By: Ryan E. Day, Dirk Dusharme @ Quality Digest, Taran March @ Quality Digest

In order to best illustrate how enterprisewide SPC software can help address shop-floor problems and then funnel the captured data to the corporate level where strategic issues can be analyzed, here is a case study of a hypothetical manufacturing facility. In it, the company makes effective use of SPC for data-driven decisions.

A global food products manufacturing company with 11 sites worldwide had chosen to master quality, both tactically and strategically, as its top goal. Each site collected and analysed data in the company’s enterprisewide SPC software, both to monitor and respond to quality issues at the site, and to share those same data with the corporate office.

At the company’s Prague site, the quality manager looked at her shop-floor data for the previous month. As figure 1 indicates, the software reported a total of 737 events, which at first glance seemed like a big deal to the manager. However, on closer inspection, she could see that these weren’t massive quality issues with the product or processes. However, there were 517 missed data checks. Although not a line-stopping issue, missed checks could result in noncompliance to agreements with customers or industry requirements.

[Read More]

Eric Weisbrod’s picture

By: Eric Weisbrod

In recent months, we’ve learned that manufacturing during a global health crisis puts organizations under immense pressure to maintain operational efficiency while upholding product quality and employee safety.

Initially, organizations focused simply on taking the steps required to survive. However, as organizations around the globe have pivoted to overcome those initial challenges, manufacturers are taking the opportunity to explore how they will not just survive but become more resilient—even thrive—going forward.

Recent operational challenges have shined a light on existing process weaknesses and technology limitations. Manufacturers are taking their cue and proactively identifying opportunities to optimize processes, empower workers, and make operations across the organization more effective.

Enact, InfinityQS’ cloud-native quality intelligence platform, offers plant leadership a variety of ways to make their operations more effective. Here are six Enact benefits that can help your organization make critical shifts that are necessary for the future of manufacturing.

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Jon Speer’s picture

By: Jon Speer

Risk can mean many different things depending on the situation. Flying on an airplane, biking on a busy road, driving in a car—all of these involve some level of risk.

Although risk is a variable we encounter in everyday life, it means something uniquely different to the medical device industry. Risk is a critical factor to consider throughout the life cycle of a medical device because it can mean the difference between life and death for patients.

Industry resources like ISO 14971 exist to help medical device professionals define and clarify risk management best practices. According to the internationally recognized standard for medical device risk management, risk is defined as “the combination of the probability of occurrence of harm and the severity of harm.”

There are varying levels of risk factors medical device companies must consider in practicing effective risk management. By following the established processes outlined in ISO 14971 and leveraging the best quality management tools, medical device companies can improve their overall risk management system.

[Read More]

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