Manufacturers of complex products like aircraft and satellites must achieve perfect quality to meet customer specifications. This requires navigating dynamic production, quality, and supply chain issues while meeting regulations. Achieving perfect quality today requires Quality 4.0, which captures more data using advanced technologies to identify issues early. Quality 4.0 takes a data-driven approach to quality throughout the production process to transform work and minimize defects. When properly deployed, it delivers cultural change by more deeply integrating quality into product design, engineering, and manufacturing.

1. Achieving Perfect Quality in Manufacturing
By Becky Kelderman
Manufacturers of highly engineered, complex products such as aircraft or satellites must
deliver each product to perfection and customer specifications. Therefore, quality must
always be the top priority and seamlessly incorporated into every design, change,
production and quality control process. The challenge is that product expectations and
complexity have increased substantially over the past few years, while costs are
continuing to be analyzed. Accomplishing this objective requires manufacturers to be
adept at navigating highly dynamic production, quality and supply chain issues while
meeting regulatory requirements. Achieving perfect quality today requires an Industry
4.0 approach to quality – capturing an increasingly higher volume of data and metrics
while using advanced technologies to understand this data, make predictions and
identify potential issues before it is too late.
Despite the latest advances in technologies and manufacturing strategies, managing
complex, frequently changing production orders is quite difficult. There is a host of
factors that can impair the delivery of quality products to end users. Not only are there
significantly more complex parts to source from suppliers around the world, but greater
consideration must now be applied throughout the assembly process to bring it all
together.
Adding to these challenges, manufacturers now face unprecedented uncertainty and
disruptions that have emerged in 2020. Supply chain disruptions, quality assurance
visibility and regulatory compliance adherence must now all be done with limited staff
that has created new challenges with achieving visibility into supply chain operations.
Simplify the complex to drive perfect quality
The Fourth Industrial Revolution, or Industry 4.0, ushered in a new wave of innovation
and advanced technologies, including the Industrial Internet of Things (IIoT), the digital
thread, artificial intelligence and predictive analytics. Each of these advances have
become increasingly critical to how manufacturers operate. Industry 4.0 has a quality
companion, Quality 4.0, first introduced by LNS Research in 2017.
Quality 4.0, like Industry 4.0, takes a data-driven approach to quality performed during
the production ecosystem, including how to manage and improve the product,
processes, planning, compliance, standards and more. It builds upon, rather than
replaces, traditional quality methods. Additionally, it uses many of the same new
technologies as its industrial counterpart; machine learning, connected devices, big
data, cloud computing, augmented reality and more to transform an organization’s work
processes as well as minimizing its product defects.
The emergence of Quality 4.0, when properly deployed, delivers change the workplace
culture by increasing the reliance upon data and more deeply integrating quality as part

2. of the entire approach to creating products. This includes how a product is
conceptualized, engineered and built. It uses process-focused machine learning to
reduce waste, minimize re-work and optimize production parameters. In addition, it
addresses product performance issues after delivery, making use of feedback from the
field to update product software remotely, maintain customer satisfaction and ultimately
secure repeat business. Quality 4.0 has quickly become an inseparable companion to
Industry 4.0.
However, quality is not a concept that applies only to select segments of the
manufacturing process. It is bigger than that. The inclusive span of Quality 4.0, once
implemented, can instill a comprehensive approach to quality in the manufacturing
organization, making the transformative power of data an integral part of the corporate
mindset.
Manufacturing excellence through data, automation
Take for example a company that builds sophisticated electronic data analysis and
signal processing systems. They become key components of products in a variety of
aeronautic, marine, surface and space station applications for both U.S. and
international customers. These are typically mission-critical devices with zero tolerance
for failure. However, meeting the requirements of multiple programs for 20 different
customers is a significant challenge. The customers not only bring their own stringent
product specifications to the company, but they also bring mandates for compliance with
regulatory requirements and fluctuating schedules, as well as constantly evolving
demands and modifications for their made-to-order products. So, the company has
elected to automate much of its operating quality program.
Implementing a manufacturing execution system (MES) can help streamline and
remove paper-based procedures on the shop floor. In their solution, performance and
quality-related data are collected in real time as work is performed. Automated quality
control procedures, including statistical process control charts, immediately flag out-of-
control conditions to shop floor mechanics. Corrective action procedures are triggered
automatically.
This closed-loop quality system is essential to achieving higher levels of quality,
improving cycle times and assuring regulatory compliance with industry standards.
Additionally, metrics are reviewed daily at each work center to identify areas for
potential improvement.
Plus, MES facilitates these work orders, guiding product flows through the shop floor,
providing real-time visibility of the work in process and tracking each activity. Skilled
mechanics and machines, working in the plant’s spotless environment, perform detailed
production processes that can be as specialized as fastening microchips as small as a
speck of pepper to newly imprinted circuit boards. Regardless the process or detail that
is involved, every production process generates data, which then becomes quite
valuable in the quest for ever-increasing quality standards.

3. Other examples of technologies used to drive quality control include improved clean
manufacturing cells, enhanced parts cleaning equipment, high-quality manufacturing
systems, a selective solder machine and a solder robot. Each of these activities take the
place of much manual labor formerly required to make precise electrical connections.
Collectively, each of these processes can now have a quality component deeply
integrated into every process that is performed.
The path forward
The Industry 4.0 concept represents a massive change for industrial enterprises. Years
ago, quality issues affecting consumer products as well as highly engineered goods
focused primarily on the handiwork of plant floor employees, and only then when they
involved product flaws. The idea of focusing quality and operational excellence on
product design, market research, suppliers, the services surrounding the product or any
of the other factors affecting customer satisfaction were simply out of the question.
Product designs were understood as emanating from a higher authority; quality in
manufacturing was about executing those designs on the assembly line, regardless of
their shortcomings.
Today, many companies are rethinking how business gets done. What was status quo
in 2019 may never be the same. Increasingly, manufacturers are getting smarter.
Greater knowledge is available, and that means better intelligence to enable products to
be built right the first time, with greater efficiency and performance than what was
possible just a few years ago.
It’s critical that quality remain a core focus of digital transformation in manufacturing,
integrated into specific aspects of the Industry 4.0 vision. This includes within process
design, intelligent poka-yoke, and an integration of quality data in the digital thread (or
threads). Ultimately, the industry is moving toward a future where the integration of
quality management practices throughout the manufacturing process will soon be so
integrated that they may soon be one and the same.