Dirk Dusharme @ Quality Digest’s picture

By: Dirk Dusharme @ Quality Digest

Blame it on Moore’s law. We live in a digital Pangaea, a world of borderless data driven by technology, and the speed and density with which data can be transmitted and handled. It’s a world in which data-driven decisions cause daily fluctuations in markets and supply chains. Data come at us so fast that there is almost no way business leaders can keep abreast of changing supply chains and customer preferences, not to mention react to them.

Operating any kind of manufacturing today requires agility and the means to turn the flood of largely meaningless ones and zeros into something useful. The old ways of treating data as nothing more than digital paper won’t cut it in the “new normal.” We need to reimagine how we view quality.

Ryan E. Day’s picture

By: Ryan E. Day

It’s no secret that manufacturing companies operate in an inherently unstable environment. Every operational weakness poses a risk to efficiency, quality, and ultimately, to profitability. All too often, it takes a crisis—like Covid-19 shutdowns—to reveal operational weaknesses that have been hampering an organization for a long time.

The nature of the problem

It is not just a manufacturing company’s production facility that faces operational challenges, either. The entire organization must address a host of risks and challenges; shifting consumer and market trends necessitate improving agility and responsiveness; dynamic and global competition force innovation not only in product development, but also service and delivery; evolving sales channels, including online outlets, challenge established profit margins. And these challenges are not going away any time soon.

The real problem, however, lies not with the challenges themselves but with a company’s reluctance to see the operational weakness that makes it susceptible to a particular risk in the first place.

Eric Weisbrod’s picture

By: Eric Weisbrod

For nearly a century, statistical process control (SPC) has been the cornerstone of quality management and process control. But traditional SPC can’t keep up as the pace of manufacturing accelerates. Twenty-first century manufacturing lines produce multiple products and create thousands of data points in any given minute. Operations, quality, and Six Sigma teams are buried in an avalanche of data that they can’t possibly interpret.

Many organizations find that their teams are consumed by continually monitoring control charts and updating spreadsheets. They don’t have time to try to understand what all that data really mean—or how they can use them to drive meaningful action for their companies.

Even real-time data fall short when they’re siloed in different databases and accessible in only one location. The result is missed opportunities and wasted time as teams search for the details they need to achieve manufacturing optimization across the enterprise.

So how do you monitor what’s happening on the plant floor while it’s happening, without becoming so buried in data that agile analysis and response become impossible? And how do you scale your solution across multiple lines, shifts, and sites?

Steve Wise’s picture

By: Steve Wise

Quality data are the heart and soul of statistical process control (SPC), the industry standard methodology for measuring and controlling quality in manufacturing processes. Asking manufacturers to give up data is like asking them to give up water. It’s just something that is necessary for their survival.

However, like water, data can accumulate quickly under the right circumstances. When we get too much, we can drown. But with the judicial application of quality intelligence, we can dive into our data and come up with treasure.

The data deluge of digital transformation

For decades, manufacturers have collected data in a dedicated way, laboriously documenting essential process metrics and required quality checks. Traditional quality management methodology meant diligently performing quality checks, putting that documentation on paper or in a spreadsheet—and filing it until an auditor asked for it.

During the past 20 years or so, we have found new ways to collect more data faster. We have the ability to automatically, wirelessly, collect thousands—even millions—of data points per minute. It’s exhilarating.

Mary Rowzee’s picture

By: Mary Rowzee

During the first six months after the publication of its first edition in June 2019, the AIAG & VDA FMEA Handbook gained popularity in the global automotive industry. Both U.S. and European OEMs have started to require the AIAG VDA approach to failure mode and effects analysis (FMEA) in their programs. Like the AIAG Guidebook, fourth edition, the handbook provides guidance, instruction, and illustrative examples of the requisite analytical techniques. The activities and analyses historically involved in FMEA have been formalized as discrete steps in the handbook.

 The seven-step approach described in the handbook and outlined here guides the development of design, process, and supplemental monitoring and system response of FMEA through the sequencing (and the iteration) of described activities.

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Multiple Authors
By: M. Tina Dacin, Laura Rees

A small business has been given the green light to reopen amid the Covid-19 pandemic. What does it need to consider for employees and customers?

Small-business owners are reorganizing physical space to account for continued distancing requirements, and rethinking supply chains to deliver products and services in new ways to meet changing demand patterns. But they must not forget the hearts and minds of employees and customers.

That doesn’t mean replacing a focus on the bottom line, but it helps address the need for a new set of expectations and ways of communicating in terms of product or service offerings, delivery methods, and real-time feedback.

Based on our expertise in organizational behavior and past research we’ve conducted, we provide a set of recommendations to help small businesses thrive in our new Covid-19 economy by looking after the hearts and minds of the people most important to businesses: employees and customers.

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Mariah Hauck’s picture

By: Mariah Hauck

The latest Thomas Industrial Survey revealed the ongoing impacts of Covid-19 on North American manufacturing. Unsurprisingly, 89 percent of the 1,000+ North American manufacturers surveyed reported being affected by Covid-19. Business impacts include decreased demand, staffing issues, and fluctuations in the supply of materials and services.

Although the effects have been intense and widespread, the results show the crisis has fostered the reimagination of company supply chains and innovation in many manufacturing companies.

Most notably, the report revealed that one in four North American manufacturers are considering introducing industrial automation to their facilities as a result of Covid-19. Additionally, 64 percent of manufacturers report they are likely to bring manufacturing production and sourcing back to North America—a 10-percent increase of the same sentiment reported in the March 2020 survey.

Covid-19 impacts

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Maggie Pavlick’s picture

By: Maggie Pavlick

Masks, gowns, and other personal protective equipment (PPE) are essential for protecting healthcare workers. However, the textiles and materials used to make such items can absorb and carry viruses and bacteria, inadvertently spreading the disease the wearer sought to contain.

When the coronavirus spread among healthcare professionals and left PPE in short supply, finding a way to provide better protection while allowing for the safe reuse of these items became critical.

“Recently there’s been a focus on blood-repellent surfaces, and we were interested in achieving this with mechanical durability,” says Anthony Galante, a Ph.D. student in industrial engineering at the University of Pittsburgh and lead author of the paper in in the journal ACS Applied Materials and Interfaces.

“We want to push the boundary on what is possible with these types of surfaces, and especially given the current pandemic, we knew it’d be important to test against viruses.”

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Thomas Hellwig’s picture

By: Thomas Hellwig

The Covid-19 world is marked by a high degree of uncertainty and existential fear, a dearth of social interaction, the convergence of professional and personal space, a lack of physical activity, and an obsessive focus on hygiene and social distancing. For professionals, this amounts to a toxic combination that elevates stress levels and increases the risk of burnout. Virtually no one—and no organization—is immune.

Now more than ever, managers should become sensitive to the mental health of their teams, not to mention themselves. But few managers have formal training in this arena, which means their ability to directly intervene in the most severe cases is limited. What managers need first and foremost is a set of tools to help identify when an employee is seriously struggling. They can then take appropriate steps to ensure the sufferer has access to the necessary resources before the problem becomes so big that it’s overwhelming.

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Jessica Reiner’s picture

By: Jessica Reiner

For more than 20 years, a class of man-made, potentially cancer-causing chemicals called per- and polyfluoroalkyl substances (PFAS) has commonly been found in humans and the environment. These chemicals are used in a variety of industries and can be found in many consumer products, such as food packaging and cleaners. Many early studies showed PFAS could even be found in remote locations like the Arctic.

There is one that I remember well in which 21 of the top PFAS researchers wrote about the measurement challenges that were hindering research. I was in graduate school at the time, and this paper really resonated with me. The authors pointed out that data for these chemicals should be accurate, precise, and reproducible because it was likely these data would be used as a foundation for regulatory decisions. As I look at the current news, it seems that these regulatory decisions are now being made under the Environmental Protection Agency’s PFAS Action Plan.

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