Jon Speer’s picture

By: Jon Speer

The European Medical Device Regulation (MDR) is a new set of regulations that governs the production and distribution of medical devices in Europe, and compliance with the regulation is mandatory for medical device companies that want to sell their products in the European marketplace.

If your company was already compliant with the Medical Devices Directive (MDD), don't be fooled into complacency: The MDR represents brand-new regulations with significant changes.

For those seeking to better understand why the regulations have changed, and what some of the major changes are, let’s take a look at some of the most common questions we hear from our users.

Jay Arthur—The KnowWare Man’s picture

By: Jay Arthur—The KnowWare Man

When I first learned quality improvement back in 1989 at Florida Power and Light, the consultants who trained us taught a very specific way to draw a Pareto chart. They’d been trained in Japan, the place where quality improvement first took root during the 1950s, so I took it for granted that the way they drew Pareto charts was the authentic and best way to do so.

A Pareto chart combines a bar graph with a cumulative line graph. Using the way we were taught to draw a Pareto chart (figure 1), the bars are touching, making it extremely easy to visually compare levels from one bar to the next. The bars span the entire available space along the x axis. The cumulative line graph springs from the bottom left corner of the first big bar, and each subsequent point is plotted from the corresponding top right corner of its bar.

James J. Kline’s picture

By: James J. Kline

The term “risk-based thinking” (RBT) is familiar to those in the quality profession. This familiarity comes in part from its inclusion in ISO 9001:2015, the International Organization for Standardization (ISO) quality management system standard. Although numerous articles and several books have been written on how to implement ISO 9001:2015 in the private sector, little has been done with regards to the public sector.

This reflects two facts. First, the idea of systematically managing the risks governments face is relatively new. Second, where risks are being managed by government organizations, there is no consistent approach. Some are using ISO 9001:2015 and others are using ISO 31000. ISO 31000, revised in 2018, is an enterprise risk management standard.

This article looks at what public-sector organizations are thinking about, and doing, to manage risks.

Nicole Radziwill’s picture

By: Nicole Radziwill

As early as 2015, McKinsey’s “Digital America” report projected that adoption of Industry 4.0 technologies in manufacturing alone was expected to increase domestic GDP by more than $2 trillion by 2025. This estimate, developed from expectations surrounding productivity enhancements, waste reduction using methods from lean manufacturing, and new business models enabled by technologies like 3D printing and practices such as remanufacturing, is on track to not only be metbut exceeded.

Isaac Maw’s picture

By: Isaac Maw

In manufacturing today, data analysis tools can give management the information it needs to make better decisions in areas such as maintenance and labor. Unfortunately, however, many data analytics systems require large sets of historical data to generate accurate and useful results.

According to Rebecca Grollman, a data scientist at Bsquare, anomaly detection is different. These algorithms can begin generating useful information without needing to be trained on historical data. Although simple, anomaly detection can be used for applications such as detecting machine stoppage, sensor malfunctions, tracking production output, and more. Engineering.com recently spoke with Grollman about this solution. 

How essential is historical data in typical data science applications?

Multiple Authors
By: Vip Vyas, Diego Nannicini

Is your enterprise dominated by passive thinking and prescribed routines? Or is it one that generates fresh thinking and unlocks insights into the future?

The viral popularity of TED Talks—with more than a billion views to date—highlights the innate hunger we have for discovering breakthrough ideas.

When it comes to making that high-stakes decision or tackling the most pressing challenges facing your firm, whose experience, inspiration, and insights do you seek? Just as important, why do you look up to those particular individuals or organizations? What do they possess that draws your attention?

What if this wisdom and intelligence resided in your own organization? What does it take to become a thought leader within one's firm?

Alex Bekker’s picture

By: Alex Bekker

Do you know what a retailer and a tightrope walker have in common? They both have to balance. For the tightrope walker, the logic is clear. But what’s the balance that a retailer is looking for?

A typical dilemma of shortages vs. storage costs

Although the dilemma of shortages vs. storage costs is applicable to any product category, it’s much more painful with perishables. If their quantity can’t meet the demand, retailers should be ready to see a frown from an unhappy customer who didn’t find her favorite dairy, fruit, or vegetable on the shelves.

However, staying on the safe side by ordering more perishables is hardly a cost-effective solution. Perishable products require special storage conditions, and their shelf life seldom exceeds a couple of days, which means retailers must address disposal issues. So, it’s easy to understand why retailers, by all means possible, try to find the optimal balance between storing too much and too little.

Ryan E. Day’s picture

By: Ryan E. Day

Current business conversation often focuses on data and big data. Data are the raw information from which statistics are created and provide an interpretation and summary of data. Statistics make it possible to analyze real-world business problems and measure key performance indicators that enable us to set quantifiable goals. Control charts and capability analysis are key tools in these endeavors.

Control charts

Developed in the 1920s by Walter A. Shewhart, control charts are used to monitor industrial or business processes over time. Control charts are invaluable for determining if a process is in a state of control. But what does that mean?

William A. Levinson’s picture

By: William A. Levinson

Anthony Chirico1 describes how narrow-limit gauging (NLG, aka compressed limit plans) can reduce enormously the required sample size, and therefore the inspection cost, of a traditional attribute sampling plan. The procedure consists of moving acceptance limits t standard deviations inside the engineering specifications, which increases the acceptable quality level (AQL) and therefore reduces the sample size necessary to detect an increase in the nonconforming fraction.

Nicola Olivetti’s picture

By: Nicola Olivetti

According to a report by PwC, industrial sectors worldwide plan to invest $900 billion in Industry 4.0 each year. Despite these growing technology investments, only a few technologies are significantly mature to drive measurable quality impacts. Digital visual management (DVM) is one of them, being the fundamental link that bridges the lean culture and quality management in the digital age. 

What is digital visual management?

The vast majority of all the information and communication is visual. The human brain processes visual information significantly faster than text. When a relevant image is paired with audio material, two-thirds of people retain the information three days later.

Organizations dedicated to continuous improvement take advantage of this reality and use DVM to engage staff, provide insight into key information, and to ensure improvement projects are moving forward as scheduled.

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