Christopher Shoe’s picture

By: Christopher Shoe

According to a recent LNS Research survey, 37 percent of quality leaders cite an inability to measure quality metrics as their No. 1 barrier to achieving quality goals. Even worse, the survey showed four in five companies have poor visibility into real-time metrics.

These figures highlight a central problem in quality management: In an era of increasingly large data sets, how can manufacturers leverage these data for meaningful improvement?

It’s a question that’s especially relevant for manufacturers engaged in layered process audits (LPAs), a high-frequency verification strategy where teams conduct short audits every shift. With hundreds or even thousands of audits taking place during the course of a year, making sense of a large volume of data is a core challenge of LPA programs.

While plant managers often track metrics at a granular level, executives need to look at the data a little differently. Let’s look at four of the most important enterprise-level LPA metrics to track.

Samantha Maragh’s picture

By: Samantha Maragh

I didn’t understand what people were asking me when I was a kid. The question would come in several different forms. Sometimes it was, “What are you?” Other times it was, “Where are you from?” I would answer with things I knew to be true, like, “I’m a girl,” or, “I’m a person,” or, “I’m from Maryland,” in a sincere, but failed, effort to satisfy my questioner.

I later came to understand that these people actually wanted to know my ethnicity. I grew up in a stereotypical melting-pot USA kind of place, otherwise known as Howard County, Maryland, where many neighbors and classmates were of various ethnic backgrounds. Even in this melting pot, I was different. I am of mixed ethnicity: My mom’s half is Afro-Caribbean by way of Jamaica, and my dad’s half is East Indian by way of the West Indies. I couldn’t be placed in one bin, and I was keenly aware from the questions I received that I was different. This made me want to understand this “otherness,” and that is what sparked my love of human genetics.

Credit: Mark Esser/NIST

Pavel Kireyev’s picture

By: Pavel Kireyev

Good salespersonship is a species of street smarts. It’s about quickly sizing up your customers and pitching your wares in terms that reverberate with their unspoken needs and desires. As artificial intelligence (AI) and machine learning increasingly intersect with e-commerce, these priceless human skills are finding algorithmic analogues—not just at point of sale, but throughout the customer journey.

The results will be familiar to online shoppers everywhere. Netflix’s and Amazon’s algorithms leverage the data from each customer click to fine-tune their recommendations and drive consumption. The tech behemoths also deploy consumer activity data to sharpen their email and social media marketing. This is likely only the beginning because the technology’s predictive prowess is improving all the time.

Multiple Authors
By: Ian Chipman, Knowable Magazine

Imagine yourself in your local supermarket, doing your usual grocery run. In aisle after aisle, countless brands vie for your dollars and attention. Colgate, Crest, and Aquafresh toothpaste. Smucker’s, Welch’s, and Dickinson’s strawberry jam. Coke, Pepsi, and RC Cola soft drinks.

Like most consumers, you probably prefer one over another in dozens of categories that are collectively called consumer packaged goods. This class of goods includes things with a relatively short life cycle such as food, drinks, cosmetics, and cleaning products. These items are used and replaced quickly, compared with durable goods like appliances and cars. True product innovations in this realm are rare, and actual distinctions between brands are typically slim. Yet reaching for your go-tos is almost automatic, and economists have long tried to determine why.

It’s especially curious because, as research has repeatedly shown, consumers in blind taste tests routinely fail to pick out their preferred brands. And they will happily purchase name-brand products such as Advil even when identical generic products sit right next to them on the shelf for a fraction of the cost.

Alberto Castiglioni’s picture

By: Alberto Castiglioni

Ensuring the quality of a car’s performance and design, FARO 3D measurement technology solutions provide simple yet accurate ways of taking contact and noncontact measurements for quality control in automobile manufacturing and assembly.

Portable CMMs such as articulated arms can be used for rapid prototyping, analyzing car body panels, or inspecting a body-in-white, while large-volume laser trackers can be implemented for part inspection, alignment, machine installation, robot calibration, or reverse engineering tasks.

FARO has recently developed and introduced new portable metrology solutions that add measurement features and capabilities to its FaroArm product family: the FARO 8-Axis system and the FARO PRIZM Laser Line Probe.

The FARO 8-Axis system delivers innovative, real-time part rotation to streamline quality inspection processes.

The FARO 8-Axis system combines the portable FARO Quantum FaroArm or Quantum ScanArm portfolio products with a functionally integrated, yet physically separate, eighth axis.

Scott Cowen’s picture

By: Scott Cowen

It was a year ago that our country lost one of its most well-known and respected mavericks in recent political history. After John McCain passed away, many felt that his death left a void that would be hard to fill and wondered whether nonconformist leaders like him, who usually worry more about what’s right than about what’s popular, still exist. The McCain Institute for International Leadership even launched a nonpartisan campaign called #MavericksNeeded, reminding us all of the need to uphold principles of freedom and democracy, encourage moral reasoning, and bring progress.

One year later, we get our pick of politicians on the national stage who are willing to go it alone and ruffle some feathers. The four freshman Congresswomen known as the “squad” come to mind, and so might the four Republicans who crossed party lines when they voted with all Democrats in the House to condemn President Trump’s recent “go home” comments. Texas Democratic Representative Al Green has been called a maverick for trying to get Trump impeached three times without the necessary support from his party.

Paige Needling’s picture

By: Paige Needling

Amidst a sea of alarming cybersecurity statistics, there’s one that perfectly captures today’s reality. It’s from a 2019 Trend Micro survey, which says: “80 percent of all businesses expect to be hacked this year.” Not “perhaps” or even “likely.” But will be hacked.

And perhaps worse, only 39 percent of the 400 executives and board members surveyed (see figure 6) said their company has fully developed and implemented a cyber-defense strategy. The expectation of being hacked shows the vulnerability organizations across the board feel, not just those that have been breached or that may fit a profile of “high risk” businesses (e.g., banks or hospitals). Small and medium-sized businesses are particularly vulnerable because of their relative lack of resources compared to Fortune 500 companies.

Multiple Authors
By: Fabian Schumann, Jennifer Robison

The World Economic Forum (WEF) estimates that artificial intelligence (AI) will displace 75 million jobs across the globe by 2022, and that the pace will only continue to increase. A PwC report predicts that 38 percent of jobs in the United States—as well as 30 percent in the United Kingdom, 35 percent in Germany, and 21 percent in Japan—could be gone by 2030.

Does this mean organizations will just require fewer people in the future? Many current predictions say no. The WEF estimates that automation will actually create 58 million more jobs than it replaces by 2022. McKinsey calculates that rising incomes could create 250 million additional jobs by 2030.

Although many jobs will become obsolete—either because the job can be fully automated or because a few people with the right tools can do the work of hundreds—new jobs will be conceived to fulfill new customer needs, leverage new technologies, and execute new business strategies.

However, pink-slipping employees whose jobs were automated and recruiting new people with a higher skill set in tech may be a losing strategy.

Jody Muelaner’s picture

By: Jody Muelaner

How would you like to go hands-free, maintain visual focus, and save time? These are just some of the benefits of using voice command to control machinery. Increasingly sophisticated natural language processing, based on artificial intelligence, also means that it is becoming possible to issue complex commands by simply telling a machine what you want it to do. This removes the need to memorize specific command words or learn complex menu systems and sequences of instructions.

During the past few years, voice-assisted technology has become very popular in the consumer market. Products such as Apple’s Siri, Amazon’s Alexa, the Google Assistant, and Microsoft’s Cortana have become household names—quite literally, as people use them to turn on the lights and control the heating. This technology is also appearing in the industrial market, where things can be considerably more challenging.

Steven Brand’s picture

By: Steven Brand

The food industry is evolving rapidly, with consumers demanding quality, authenticity, and transparency from food manufacturers. And they’re not just demanding it; they’re “voting with their dollars,” supporting companies that align with their personal beliefs. To keep up with consumer demand—and to keep up your bottom line—it’s important to understand their needs and make changes that support them.

In doing so, you can improve your product quality, reduce waste, inspire brand loyalty, compete more effectively, and avert potential media or food-safety disasters. Let’s look at six ways to improve product quality in food manufacturing.

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