Featured Product
This Week in Quality Digest Live
Innovation Features
Edd Gent
Increasingly visible and accessible, but with caveats
Matt Fieldman
German system offers tips for U.S. counterparts
Belinda Jones
Reaping the benefits of manufacturing intelligence
Marni Baker-Stein
Closing the education-to-hiring gap

More Features

Innovation News
VSL hosts special edition of show at new center in Rotterdam
Latest line touts comprehensive coverage, ease of use
Same price, double the resolution and accuracy
Low-cost prevention of catastrophic failures
Diagnoses LVDT failures, disconnects, or short circuits
Using noncontact, interferometric technology
Quality doesn’t have to sacrifice efficiency
WFL continues a legacy of success

More News

Nicole Radziwill

Innovation

Your Data Are Your Most Valuable Assets

Getting started with Quality 4.0

Published: Wednesday, October 10, 2018 - 11:03

Data science and machine learning have surged in prominence during the past few years, and digital transformation seems to be on everyone’s agenda. Have you ever wondered why? Even though quality engineering has long been a data-driven pursuit, we now have the potential to get even deeper insights from our data because of several recent innovations.

Here are just a few of them:
• Computing power per dollar has increased steadily (e.g., through adoption of GPUs).
• Open-source software packages with powerful machine learning algorithms are freely available, reliable, robust, and well-maintained.
• Infrastructure for data storage and management is readily available and cost-effective.
• Cloud-based software, platforms, and infrastructure help companies focus on their core competencies and scale rapidly when needed.
• Algorithms are often more revealing when Big Data is available.

It’s easy and cheap to collect data, but using them to generate actionable insights can be more challenging. Think, for example, about the digital displays available to a production manager supervising a factory. The factory has multiple product lines, with hundreds of variables and attributes to monitor, as well as reaction plans to oversee and track. Although software systems are available to make these tasks easier, getting it right can still be daunting. Synthesizing data across multiple subsystems in your operations, or multiple divisions in your organization, to uncover opportunities for improvement can be messy, uncertain, or even impossible.

Quality 4.0 aims to break down these barriers by providing “organizational omniscience” and real-time performance innovation. (Radziwill, 2018a; 2018b.) Our new technology-infused quality management strategies will answer questions like:
• How can we leverage connected, automated, intelligent systems—made up of people and machines—to make processes more efficient and effective, save time and money, and produce better products more consistently?
• How can we use emerging technologies to support engagement and collaboration that help connected and empowered individuals achieve the organization’s goals?

Quality 4.0 will help us more quickly assess compliance and customer satisfaction, adapt to changes in the environment and the market, and optimize business processes through systems integration, whether the object we’re working with is a process, a product, a person, or an intelligent software system. The accompanying digital transformation will help us enrich human intelligence while leveraging machine intelligence, automate processes that were previously labor intensive, and connect more richly to our processes and to each other.

One day, smart, hyperconnected, and intelligent agents will be deployed in environments where humans and machines cooperate effortlessly to achieve their shared goal of continuous improvement. With real-time visibility and transparency, you’ll be able to take operations one step further by anticipating process and product issues before they happen. You can trigger contingency plans, adapt to environmental changes, and discover and prioritize opportunities for continuous improvement based on anticipated impact and the potential for reduced risk.

As a result, Quality 4.0 strategies emphasize real-time visibility, intelligent decision support, and improved communication between people, systems, and machines. Nikon, for example, recently announced a Quality 4.0 strategy emphasizing real-time measurement: automating measurement systems and inspections, and centralizing the results in an accessible data warehouse. By digitizing as much as possible, Nikon aims to shorten the time required to make decisions about production processes. This will improve availability and productivity.

Some organizations that are struggling with compliance, continuous improvement, or building a quality culture may worry that they will miss out on the business value promised by Quality 4.0 initiatives. Fortunately, it’s not too late at all. The foundation for Quality 4.0 is digital data, supported by an integrated management system that can serve as the nexus for your quality data and records. Having all of your environment, health and safety, and quality data in one place gets people working together and reduces the need for data integration later. (BLR Media, 2018) Cloud-based systems further reduce risk, allowing your organization to scale without the burden of keeping key systems functioning.

If your data are on paper, or if you’re drowning in it, your data can’t work for you. Where should you begin?

During the Oct. 16, 2018, webinar, “The Quality 4.0 Revolution: Reveal Hidden Insights Now With Data Science and Machine Learning,” we’ll show you what data scientists do, what kinds of problems in quality and process improvement can be solved with machine learning, and how to get started—even if your processes are still manual and your data analysis is still primarily in Excel. No technical expertise is necessary. Register for the webinar here. We hope to see you there.

Additional reading
“Implementing New EHS Software: Revealing Value, Gaining Buy-in, and Engaging Employees,” Intelex Insight Report, BLR media, 2018.

Radziwill, N.  “What is Quality 4.0?” (Aug. 7, 2018a).

Radziwill, N. “Let’s Get Digital: The many ways the fourth industrial revolution is reshaping the way we think about quality.” Quality Progress, pp. 24–29, Oct. 2018b.

Discuss

About The Author

Nicole Radziwill’s picture

Nicole Radziwill

Nicole Radziwill is senior VP and chief data scientist at Ultranauts, and an internationally recognized expert in digital transformation and next generation quality. Formerly VP of the Global Quality and Supply Chain Practice at Intelex Technologies in Toronto, and a tenured associate professor of Data Science and Production Systems, she is an elected academician with the International Academy of Quality (IAQ), a Fellow of the American Society for Quality (ASQ), and a past chair of the ASQ Software Division. She has a Ph.D. in Quality Systems and is the author of data science and statistics textbooks used in more than 30 universities, as well as “Connected, Intelligent, Automated: The Definitive Guide to Digital Transformation and Quality 4.0,” from Quality Press (2020).