Tag Archives: Quality 4.0

Quality 4.0: Reveal Hidden Insights with Data Sci & Machine Learning (Webinar)

Quality Digest

What’s Quality 4.0, why is it important, and how can you use it to gain competitive advantage? Did you know you can benefit from Quality 4.0 even if you’re not a manufacturing organization? That’s right. I’ll tell you more next week.

Sign up for my 50-minute webinar at 2pm ET on Tuesday, October 16, 2018 — hosted by Dirk Dusharme and Mike Richman at Quality Digest. This won’t be your traditional “futures” talk to let you know about all of the exciting technology on the horizon… I’ve actually been doing and teaching data science, and applying machine learning to practical problems in quality improvement, for over a decade.

Come to this webinar if:

  1. You have a LOT of data and you don’t know where to begin
  2. You’re kind of behind… you still use paper and Excel and you’re hoping you don’t miss the opportunities here
  3. You’re a data scientist and you want to find out about quality and process improvement
  4. You’re a quality professional and you want to find out more about data science
  5. You’re a quality engineer and you want some professional preparation for what’s on the horizon
  6. You want to be sure you get on our Quality 4.0 mailing list to receive valuable information assets for the next couple years to help you identify and capture opportunities

Register Here! See you on Tuesday. If you can’t make it, we’ll also be at the ASQ Quality 4.0 Summit in Dallas next month sharing more information about the convergence of quality and Big Data.

Value Propositions for Quality 4.0

In previous articles, we introduced Quality 4.0, the pursuit of performance excellence as an integral part of an organization’s digital transformation. It’s one aspect of Industry 4.0 transformation towards intelligent automation: smart, hyperconnected(*) agents deployed in environments where humans and machines cooperate and leverage data to achieve shared goals.

Automation is a spectrum: an operator can specify a process that a computer or intelligent agent executes, the computer can make decisions for an operator to approve or adjust, or the computer can make and execute all decisions. Similarly, machine intelligence is a spectrum: an algorithm can provide advice, take action with approvals or adjustments, or take action on its own. We have to decide what value is generated when we introduce various degrees of intelligence and automation in our organizations.

How can Quality 4.0 help your organization? How can you improve the performance of your people, projects, products, and entire organizations by implementing technologies like artificial intelligence, machine learning, robotic process automation, and blockchain?

A value proposition is a statement that explains what benefits a product or activity will deliver. Quality 4.0 initiatives have these kinds of value propositions:

  1. Augment (or improve upon) human intelligence
  2. Increase the speed and quality of decision-making
  3. Improve transparency, traceability, and auditability
  4. Anticipate changes, reveal biases, and adapt to new circumstances and knowledge
  5. Evolve relationships and organizational boundaries to reveal opportunities for continuous improvement and new business models
  6. Learn how to learn; cultivate self-awareness and other-awareness as a skill

Quality 4.0 initiatives add intelligence to monitoring and managing operations – for example, predictive maintenance can help you anticipate equipment failures and proactively reduce downtime. They can help you assess supply chain risk on an ongoing basis, or help you decide whether to take corrective action. They can also improve help you improve cybersecurity: documenting and benchmarking processes can provide a basis for detecting anomalies, and understanding expected performance can help you detect potential attacks.


(*) Hyperconnected = (nearly) always on, (nearly) always accessible.

Quality 4.0 and Digital Transformation

The fourth industrial revolution is characterized by intelligence: smart, hyperconnected agents deployed in environments where humans and machines cooperate to achieved shared goals — and using data to generate value. Quality 4.0 is the name we give to the pursuit of performance excellence in the midst of this theme of technological progress, which is sometimes referred to as digital transformation.

The characteristics of Quality 4.0 were first described in the 2015 American Society for Quality (ASQ) Future of Quality Report. This study aimed to uncover the key issues related to quality that could be expected to evolve over the next 5 to 10 years. In general, the analysts expected that the new reality would focus not so much on individual interests, but on the health and viability of the entire industrial ecosystem.

Some of the insights from the 2015 ASQ Future of Quality Report were:

  • A shifting emphasis from efficiency and effectiveness, to continuous learning and adaptability
  • Shifting seams and transitions (boundaries within and between organizations, and how information is shared between the different areas)
  • Supply chain omniscience (being able to assess the status of any element of a global supply chain in real time)
  • Managing data over the lifetime of the data rather than the organization collecting it

Image Credit: WEF DTI Executive Summary, http://reports.weforum.org/digital-transformation/wp-content/blogs.dir/94/mp/files/pages/files/170328-dti-executive-summary-slideshare.pdf (Slide 6)

The World Economic Forum (WEF) has also been keenly interested in these changes for the past decade. In 2015, they launched a Digital Transformation Initiative (DTI) to coordinate research to help anticipate the impacts of these changes on business and society. They recognize that we’ve been actively experiencing digital transformation since the emergence of digital computing in the 1950’s:

 

Because the cost of enabling technologies has decreased so much over the past decade, it’s now possible for organizations to begin making them part of their digital strategy. In general, digital transformation reveals that the nature of “organization” is changing, and the nature of “customer” is changing as well. Organizations will no longer be defined solely by their employees and business partners, but also by the customers who participate – without even explicitly being aware of their integral involvement — in ongoing dialogues that shape the evolution of product lines and new services.

New business models will not necessarily rely on ownership, consumption, or centralized production of products or provision of services. The value-based approach will accentuate the importance of trust, transparency, and security, and new technologies (like blockchain) will help us implement and deploy systems to support those changes.