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Quality 101

Quality 4.0

The Concept of Quality 4.0 Continues to Evolve

By Dr. Milton Krivokuca
QM 0123 Quality 101 Quality 4.0

Image Source: gorodenkoff / iStock / Getty Images Plus via Getty Images

December 28, 2022

The topic of Quality 4.0 is rapidly becoming a legend due to its mysterious nature; it seemingly has no formal description. Very few people can confidently say that they have seen it or used it. Discussions and presentations related to Quality 4.0 leave individuals with an appetite to learn more but unsure of where to begin. I am a quality practitioner with over 20 years of industry-related quality experience. My career has transitioned from manufacturing to academics, where quality is the focus of my teaching and research efforts. Personal observations shared in this article have been developed through research and feedback from several presentations to peer groups of quality practitioners.

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Don’t Let Quality 4.0 Intimidate You

Dr. Milton Krivokucha shares how he got interested in the subject, and what manufacturers should know before implementing it.

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My research for published information on Quality 4.0 provided numerous results. It was, however, disappointing that the availability of in-depth academic research was absent. Most of the published case studies were developed and sponsored by commercial interests and focused on successful applications of commercial software packages. As a result, my research was redirected to current publications from a technical perspective.

Subjects related to data science I have explored were predictive analytics, Blockchain, and other contemporary issues, and Industry 4.0 elements associated with the digitization of industry. Most of these publications were peer-reviewed and written by subject matter experts from industry and academia located primarily in the United Kingdom, Europe, and India. North American quality experts contributed very few publications on this topic. Of most interest to me was the lack of references to quality tools or methodologies. The evolution of digitization was presented in a focused way from a siloed approach of technical experts. Fundamental improvement methodologies such as PDCA or Lean did not receive recognition for how these established improvement methodologies could support the development of digitization.

These findings stimulated further research needs. My efforts next focused on the human resource element. Digitization has not entirely replaced the need for human interactions in processes. Artificial intelligence as a complete replacement for humans remains a distant object. The research focused on human resources and organized cultural and generational human diversity as the current issue. The need for people analytics to assess employee’s progress and performance was a topic of concern recognized by human resource fellows.

One globally recognized author suggested that human resource professionals turn to their engineering departments to help them establish metrics and fundamental statistical process control issues related to human resource analytics. Again, quality received no recognition to the existence or potential quality can provide to assist with the challenges of human resource analytics in Industry 4.0. Human resource publications provided another siloed approach to achieving digitization.

Digital transformation is not an abstract or theoretical journey. Achieving digital transformation requires tangible and quantifiable objectives and executed activities. This challenge can be completed with the support of proven quality tools and methodologies: no new set of tools and metamethods are necessary. In addition, a formal working definition and guidelines for quality practitioners should continue to be developed as a subset of the current global quality body of knowledge.

The underlying issues of Industry 4.0 from the technical and human resources perspective were identified, but not discussed in detail. For leaders and team members, soft skills are a critical success factor. The diverse human attributes of culture and generations, skill levels, personality styles, professional goals, empathy, work-life balance priorities, and team contributions are among the many soft skills present in today’s workforce and directly impact the results of technical processes. Questions remain unanswered: How is this skill learned? Are they learned? Can they be discovered? What is their current maturity level, and do they need to be further developed? Answers to these questions are not straightforward.

Leadership must know of the technical, human, and soft skill factors impacting inner processes. The organization can perform a self-assessment to determine its internal strengths and weaknesses with a focus on the organization’s digital strategy. The digital system begins at the top and works through a structured approach; it can be developed and deployed throughout the organization. This development and deployment of internal processes is a quality management system objective. Quality management systems include the requirements for cross-functional collaboration and recognize structured improvement methodologies and tools to support the implementation of a digitization plan in alignment with the organization’s existing technical, human, and soft skill resources.

Elements of the QM BOK provide a foundation for analyzing data and developing human capital to support innovation with existing facts for taking a proactive role in leading companies through Industry 4.0 in the 21st century. Leadership, team building, knowledge management, and quality tools require a focused emphasis on Quality 4.0, along with new areas such as:

  • Predictive analyticsis to foresee future events and situations. (Design of Experiments in Q 4.0)
  • Supervised learning:These are problems where exists a target variable (continuous or discrete) to predict or classify data.
  • Unsupervised learning: These are problems where a target variable does not exist that we want to predict but want to understand “natural” groupings of patterns in data. (Special Cause or Common Cause Variation)

The concept of Quality 4.0 continues to evolve. My research continues as I seek feedback on my presentations. The objective of the article is to provide a starting point, and shares the results of many hours of research. Quality is an undervalued and under recognized resource, and efforts to raise awareness of the value of quality as it contributes to organizational excellence are needed. Immediate action is necessary for our dynamic society.

KEYWORDS: Artificial Intelligence (AI) automation Industry 4.0 manufacturing metrology predictive analytics Quality 4.0

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Dr. Milton Krivokuca is Interim Quality Program Coordinator and subject matter advisor of the Master of Science Quality Assurance program at California State University Dominguez Hills, Carson, CA. He has also taught master’s classes in critical thinking and quality theories at several universities. Additionally, he has presented contemporary quality topics at conferences in Europe, Middle East, Africa, and Asia, locations throughout the United States and Canada. He is past chair of ASQ, Quality Management Division, an ASQ Fellow, ASQ Los Angeles Section 700 Simon Collier Quality Award recipient and 2020 ASQ Section 701 Orange Empire Quality Guru of the Year. Quality 4.0 Thought Leader. Dr. Krivokuca was awarded the ASQ 2024 Grant Medal for Meritorious Contributions to Quality Education.

He is also the 2024 Quality Professional of the Year

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