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Kari Miller

Management

An Introduction to Smart Quality Management

Smart factories will need smart quality assurance

Published: Tuesday, March 20, 2018 - 12:01

Industry 4.0, also known as smart factory 4.0, is labeled as the fourth industrial revolution, yet many don’t understand it or how it will affect the things they do; quality management is no exception. The executives in your organization, however, are most certainly monitoring this paradigm-shifting strategy. Quality professionals should be as well to ensure they are part of their company’s Industry 4.0 dialogue.

As quality professionals forge into this new era, it’s critical to have a solid understanding of the premise and aspects of Industry 4.0 and its implications for production, the extended supply chain, and their quality management systems (QMS).

The what

If you lifted the roof of a “smart factory,” you would find a manufacturing organization built on intelligent, individualized products and processes that can self-direct their way through the supply chain. Smart factories are integrated and collaborative, using the industrial internet of things (IIoT) to aid in vertical and horizontal integration of the organization’s value chain as well as the augmentation of its capabilities. Cyber physical systems (CPS) are key to smart factories because they enable communication between humans and machines throughout large networks, typically via the internet of things (IoT). They monitor physical processes, create virtual representations, and make decentralized decisions.

The role of technology

To convert an organization into a smart factory, capable of meeting the expectations of Industry 4.0, most organizations are going to require a platform upgrade within their supply chain and quality management operations. Technology investments will include the modernization of existing equipment, implementation of sensors, artificial intelligence (AI), machine learning (ML), and enterprise-level solution platforms. It also should be anticipated that with Industry 4.0, using both internal and external IoT data will dramatically increase in volume, and will be transformed into information. Predictive analytics that enable prevention will be achieved, and continuous improvement and learning will be the norm.

Managing data and analytics

For quality management systems and professionals to succeed and contribute bottom-line benefits to the organization, quality processes and data need to be embedded, integral parts of the ecosystem. Under Industry 4.0, massive amounts of data will be available to quality personnel in real-time, and from multiple sources simultaneously, and those data must be used to enable quick, situational decision making. Quality departments will need to embrace data (both internal and external) and technology, and use them to drive innovation while improving overall quality.

With the advent of Industry 4.0, quality will become increasingly right-now focused, and less rear-view oriented.

According to LNS Research, companies that have already adopted a quality management system have begun their move to Quality 4.0 by leveraging new types of data such as signal data from manufacturing equipment and connected products, combined with new analytics such as machine learning. These leaders have built initiatives like zero defects, smart manufacturing, and connected products.

The challenges of security

With the massive amounts of data to be managed under Industry 4.0, ensuring data integrity while protecting patient health information (PHI) and company intellectual property (IP) will be critical. In the medical device industry, smart products will be able to accept and send data between machine and human, so it’s imperative that the incoming data aren’t harmful to the device, and therefore the patient. The manufacturer will be challenged to ensure that the information transmitted from the device continuously provides the data needed, without exposing patient and IP information. A delicate balance of digital trust will be required to ensure data privacy and information transparency.

The effect on regulatory compliance

In what way and to what degree will regulatory compliance be affected by Industry 4.0? Most regulatory bodies are working diligently to assess how to leverage deep utilization of artificial intelligence and machine learning. This task won’t be easy because it is very different from what is the norm today. The effort is summed up by Bakul Patel, the associate center director for digital health at the U.S. Food and Rug Administration (FDA), in an article from I magazine, “Medicine Is Going Digital, and the FDA Is Racing to Catch Up.”

“We’ve been trying to translate the current regulation paradigm for digital,” Patel says. “But what we have today, and what we’re going to have tomorrow, are not really translatable. We need to take the blinders off, start with a clean sheet of paper.”

The importance of risk management

Any quality professional today can describe the pressing need to build operational quality risk management into every QMS process, as evidenced by the latest updates to standards such as ISO 13485:2016 and the European Union’s medical device regulation (EU MDR). Industry 4.0 is going to make embedding operational quality into traditional QMS processes a must, ultimately improving operational efficiency and product quality by allowing AI and ML to do what they’re intended to do: speed up the learning process and make appropriate decisions based on all that the smart product, process, or machine has learned.

The influence on validation

To focus in on Industry 4.0’s influence on quality operations (some are adopting the term “Quality 4.0” or “EQMS 4.0”), consider the effect of artificial intelligence and machine learning on validation. The current validation philosophy is that we should always experience expected results, and our validation processes and techniques are geared toward demonstrating that we will always achieve expected results. In the Industry 4.0 near future, we should expect to experience unexpected results. The power of AI and machine learning algorithms is that they learn, and they just may learn something that the algorithm’s originator didn’t initially anticipate. Learned results may be valid, even if unexpected.

The human factor: Change management is critical

For Industry 4.0 initiatives to be successful, a cultural shift will be required, one that calls for additional investment in both people and change management. It will be critical to involve employees throughout the organization, including the quality team, in the change process because different skill sets will be required in the new paradigm. Corporate leadership will need to demonstrate and execute the new company strategy and cultural vision, one behavior at a time.

Aligning industry 4.0 with QMS

The era of Industry 4.0 is upon us, and its quality equivalent, Quality 4.0, is going to leave indelible marks on the life sciences industry, among others. Quality’s participation in Industry 4.0 has its benefits. It is estimated that by embracing and participating in the technologies, data availability, and other elements of Industry 4.0, Quality 4.0, and the practical quality management application, EQMS 4.0, manufacturers can potentially reduce their total cost of quality by 22 to 50 percent.

The opportunity is exciting. although the results won’t be achieved overnight, now is the time to determine whether your organization’s quality investments are aligned with its Industry 4.0 and Quality 4.0 strategies. Gaining organizational support for investments in quality management and EQMS 4.0 technologies by demonstrating how those technologies will improve overall quality, is critical to success.

Transformation is key if your quality investments are to deliver the required results. Further, the quality team’s active participation in planning initiatives will make clear how quality assurance and QMS contribute to enhanced product quality, increased customer satisfaction, and strategic organizational objectives.

Discuss

About The Author

Kari Miller’s picture

Kari Miller

As Regulatory and Product Management Leader for IQVIA Quality Compliance, Kari Miller is responsible for driving strategic product direction and delivery of industry best practices and regulatory compliance solutions for quality management. She focuses specifically on translating market and industry requirements into industry-leading enterprise quality management solutions that meet the needs of the heavily regulated life sciences market. She also is responsible for the Quality Compliance product road map, product partner relationships, and overall product direction. Miller earned a Bachelor of Science in business administration and a Bachelor of Science in psychology from Marian College, Fond du Lac, Wisconsin.