Categories
Carnival of Quality Management Articles and Blogs

Carnival of Quality Management Articles and Blogs – October, 2019

Welcome to October, 2019 edition of Carnival of Quality Management Articles and Blogs.

Our core subject of Quality Management – Road Ahead to Digital Transformation during the year 2019, we have covered The Basics of Digitization, Digitalization and Digital Transformation, The foundation of the Digital Quality Management, Quality 4.0 and Industry 4.0 technologies Big Data Analytics, Cloud computing, Robotics, Augmented Reality, Simulation and Additive Manufacturing.

We will now take up fourth of the nine disruptive technologies of Industry 4.0 – Industrial Internet of Things IIoT)

The industrial internet of things (IIoT)[1] is the use of smart sensors and actuators to enhance manufacturing and industrial processes. The driving philosophy behind IIoT is that smart machines are not only better than humans at capturing and analyzing data in real time, they are better at communicating important information that can be used to drive business decisions faster and more accurately.

IIoT holds great potential for quality control, sustainable and green practices, supply chain traceability and overall supply chain efficiency. In an industrial setting, IIoT is key to processes such as predictive maintenance (PdM), enhanced field service, energy management and asset tracking.

Each industrial IoT ecosystem consists of:

      • Intelligent assets that can sense, communicate and store information about themselves;
      • Public and/or private data communications infrastructure
      • Analytics and applications that generate business information from raw data; and
      • People.

While the word “industrial” may call to mind warehouses, shipyards and factory floors, IIoT technologies hold a lot of promise for a diverse range of industries, including agriculture, healthcare, financial services, retail and advertising.[2]

Here are a few examples of current and upcoming IIoT technologies and concepts:

  • Digital twins – The practice of creating a computer model of an object such as a machine or a human organ or a process like weather. By studying the behaviour of the twin, it is possible to understand and predict the behaviour of the real-world counterpart and address problems before they occur.
  • Electronic logging device (ELD) – Onboard sensors that monitor speed, driving time, and how often individual drivers use their brakes, helping to conserve fuel, improve driver safety and reduce idle resources. If the driver makes a dangerous manoeuvre or is at the wheel for too long, the driver is alerted and the dispatcher is notified. This technology can replace the paper logs that drivers were once required to fill out every day.
  • Intelligent edge – The place at which data is generated, analysed, interpreted and addressed. Using the intelligent edge means that analysis can be conducted more quickly and that the likelihood that the data will be intercepted or otherwise breached is significantly decreased.
  • Predictive maintenance – A system that involves a machine or component with sensors that collect and transmit data and then analyse that data and store it in a database. This database then provides points of comparison for events as they occur. The system eliminates unnecessary maintenance and increases the likelihood of avoiding failure.
  • Radio-frequency identification (RFID) – A system that involves tags and readers, like a smarter version of barcode technology. Readers identify RFID tags using radio waves, meaning the tags can be read by multiple readers at once and over a longer distance than traditional UPCs. RFID tags make it possible to easily track and monitor the things on which they are attached.

The advent of the IIoT is a once-in-a-lifetime business disruption—one that requires new capabilities and will provide incredible opportunities.

To truly leverage its new direct customer relationship and make the full transition to an IIoT-enabled, customer-centric and service-orientated organisation, a manufacturing business must fundamentally transform its strategy and organisational culture.[3]

Drivers of IIoT[4]

  • Technology of Smart Sensors, Robotics & Automation, Augmented/Virtual reality, Big Data Analytics, Cloud Integration, Software applications, Mobile, Low power Hardware devices and Scalability of IPv6-3.4X 10^38 IP address, etc.is a major driver for the Industrial Internet.
  • Customer Behavior: The edge that IIoT gives to enterprises over their competitor helps them achieve better customer satisfaction and retention through value addition.
  • Macro-Economic Drivers: Government policies like Industry 4.0, Smart Factories, Make In India, Make In China 2025 & Smart Cities, Japan’s Industrial Value Chain Initiative Foum, Support of Green initiatives, Rising Energy & crude oil prices, Favorable FDI policies, Policies by regulatory bodies, etc. works totally in favour of the IIoT evolution.

Introduction to the Industrial Internet of Things (IIoT) – Head of the Institute of Manufacturing (IfM)’s Distributed Information and Automation Laboratory (DIAL), Professor Duncan McFarlane, is a pioneer of the internet of things (IoT) and was part of the research team that coined the term “internet of things” 20 years ago. In this webinar Professor McFarlane provides an introduction to the IoT and the IIoT and the opportunities and challenges facing industry.

IIoT currently is focusing on either managing or affecting the quality of the products via improved asset performance management, process-oriented analytics, or smart manufacturing environments which are placed to make excessive gains in bringing down the operating costs and better upliftment.[5]

The ways and factors how IIoT has been affecting the Quality of production

It’s all about the analytics when discussing the impact Big Data and IoT will have on manufacturing quality. In fact, the biggest payback of Big Data and IoT from an ROI perspective ties directly into advanced analytics. The fact of the matter remains that IT – like you – must do more with less resources. Having a holistic quality management system in place will help your company set the stage for IT to deliver the analytical tools necessary to yield actionable insights. To benefit the value chain, insights from data collected via IoT must be actionable – and more importantly, automated.[6]

In 9 ways the IoT is Redefining Manufacturing, Brian Buntz succinctly enumerates examples of companies who are implementing or benefiting from IoT capabilities. Each example shows how IoT is reshaping or redefining industry practices. One example of particular interest is Proactive Quality Assurance, enabled by placement of sensing and measuring devices in critical areas throughout the supply chain and production process…With IoT, the ability to monitor and analyze process and product quality at critical points in the supply chain and production processes, and detect when sub-standard materials are introduced or product attributes deviate from specifications promises significant cost reductions.[7]

The organizations that have already deployed and embedded enterprise quality management software (EQMS), have utilized the right metrics to measure quality or are on the right path need to note that the next wave is something entirely different than the health and performance of the QMS. The next wave is actionable data direct from the product in the field.

The question being asked by every organization with awareness and understanding of IoT today is how will we capture, process and derive meaningful intelligence from this stream?[8] This is reasonable as there will be significant volume looping back but this is not big data per se since it is not unstructured–quite the opposite. The incoming stream is by design and is therefore structured originally by us, the OEM. The real question is how do we take the stream and drive accurate and meaningful outcome in the form of improvement?

The answer is to approach the IoT with the mindset that it will supercharge the quality management system by tightening the closed-loop approach so that engineering is more closely connected with the rest of the value-chain than ever before. Improvement action or CAPA as we know it today becomes the vehicle for designing for quality based on the new channel of intelligence.

We will now turn to our regular sections:

For the present episode we have picked up article, Peter F. Drucker On Doing The Right Thing  by William Cohen, Ph.D. on Decision Making column of Management Matters Network …. “Drucker felt that managers should incorporate the ethics of responsibility enunciated by the physician Hippocrates, which in turn is validated by the test of seeing in the mirror,  into their personal philosophy and professional lives.”

We now watch ASQ TV, wherein we look at a few recent videos:

Jim L. Smith’s Jim’s Gems posting for September 2019 is:

    • Stick-to-itiveness – The ability to demonstrate persistence or perseverance – Charles Monroe “Sparky” Schulz became widely regarded as one of the most influential cartoonists of all time! But he had faced an all-round. lack of success in school and whose work was repeatedly rejected. He created the “Peanuts” comic strip and Charlie Brown was the little cartoon character whose kite would never fly and who would never succeed in kicking a football. Sparky had stick-to-itiveness. He never gave up.
    • Effective quality auditors are catalysts for change – It’s rare that managers, or even most quality auditors, discuss how closely tied the findings of manufacturing audits are to the long-term ability of their companies to compete in this highly competitive market…To be truly effective, quality auditors must throw off their perceived notions of how their information is being used. Instead, they must see it as a way to revolutionize how their companies can compete in a global economy. There is no turning back from this challenge.

I look forward to receiving your inputs / suggestions that can further enrich our discussions on the subject of Digitalization in the Quality Management

Note: The images depicted here above are through courtesy of respective websites who have the copyrights for the respective images.

[1] industrial internet of things (IIoT)

[2] What is IIoT?

[3] Industrial Internet of Things

[4] What is Industrial Internet of Things?

[5] Knowing the IIoT affect on Quality Management System

[6] How Does Quality Management Link into the Internet of Things?

[7] From reactive to proactive quality management with IoT

[8] Internet of Things: Why Quality Management Leaders Need a Strategy Now