In this guest blog post, Robert Fink, Executive Vice President at Predisys, discusses the dramatic increase in quality-related events in manufacturing, how they affect consumer sentiment, and the evolution of quality management practices.
Recent media narratives demonstrate a remarkable surge in quality-related incidents related to manufacturing. Each day brings news of FDA violations, product recalls, quality lapses among suppliers, and production delays. Such stories make headlines across major news outlets daily – not simply coincidental journalism but an indication of a dramatic increase in quality-related incidents that have a significant impact on the manufacturing landscape, garner attention of regulatory agencies, and influence consumer behavior.
Recalls on the rise
The Sedgwick 2023 Brand Recall Index shows an alarming surge in recalls across various manufacturing segments. Especially concerning is the data showing significant recall spikes from one quarter to the next (Q4 of 2022 compared to Q1 of 2023):
- Automobile recall events rose 3.4 percent year-on-year from 237 events in Q4 to 245 in Q1.
- Consumer product recalls saw a 20.5 percent surge – increasing from 78 events in Q4 to 94 in Q1.
- FDA recall events rose 23.2 percent, with 95 events reported in Q4 and 117 in Q1.
- Medical device recalls rose 4.6 percent year-on-year during Q1, increasing from 241 recalls during the fourth quarter to 252 during the first.
Recalls, among the more conspicuous quality issues, have an instantaneous and direct effect on consumers. Further, they can harm brand profiles and stock prices. According to McKinsey's estimates, one medical device company on average each year experiences a 10 percent drop in share value because of a major quality event within the past 10 years.
Manufacturing organizations know the cost of a recall is multifaceted: It involves public disclosure and rectification of the issue through either a product fix or replacement, and it causes damage from a public perception perspective, which can affect market share and stock price. That said, the continued rise in recalls suggests the art of producing quality, defect-free products is becoming increasingly difficult.
Quality surpasses price in the eyes of the consumer
Studies of consumer preference such as Price vs Quality: What Matters Most to Consumers? show an increase in quality-related issues have influenced a shift in consumer mindset. Quality now holds more priority over product pricing in decision-making processes and purchasing behavior, and consumers are willing to invest more in products with undisputed quality assurance.
Driving factors in the decline of quality
A logical follow-up to the increase in quality-related instances would be to explore what is driving this surge, specifically within the manufacturing processes themselves.
Answering this complex and often-contradictory question lies within two disparate narratives. On one side, manufacturing processes or systems have changed very little over the past several decades, yet on the other there has been an explosion of technological innovations being rapidly implemented into new products by organizations competing to be first to market with innovative tech.
The manufacturing landscape complexity increases exponentially when new components, especially ones featuring cutting-edge technology, enter the manufacturing mix. Yet even though technology continues to advance quickly, many manufacturers disproportionately depend on manual inspection processes that only identify quality issues to a limited depth. Furthermore, many invest in quality instrumentation but experience fundamental problems when using their instruments effectively.
For example, test instruments require precise calibration for effective quality issue identification and contextualization. Unfortunately, uncalibrated test instrumentation often displays issues as "no fault found," signifying a recognition of a fault but an inability to pinpoint specific problems. This creates an unproductive cycle and constant rework ensues.
Faults or failures during the manufacturing process vary over time, as the process varies or new variables are introduced. For test instrumentation to be calibrated properly, tools that enable rapid and thorough analysis are required to identify the root cause. Once the root issue is found, test instrumentation can be updated to recognize and contextualize newly created issues. Quality instrumentation is not something that is purchased and just works without care; it relies on contextualization to identify patterns or trends in test results to classify issues appropriately.
The technological impact
Technology's rapid proliferation into the manufacturing landscape can best be illustrated through its application in the automotive industry. Beginning in the 1960s with the addition of simple sensors in the assembly process, an average vehicle featured two to three sensors per car. It progressed with the introduction of onboard computers added in the 1980s (typically one or two per automobile). Cars now typically contain 70 or more sensors and 100 or more computers. With this in mind, the complexity involved in ensuring all facets of an automobile are functioning properly has become dramatically more difficult.
Even as embedded technology has rapidly evolved, manufacturing inspection processes remain largely unchanged. While more components may undergo testing, quality assurance methodologies and practices have failed to keep pace with technological development – leading to an exponentially rising rate of quality-related events.
Consumer expectations have played a central role in the common feature of increased technology in the manufacturing process, particularly with high-dollar products such as automobiles, appliances, or electronics. Consumers now anticipate an array of technological features when purchasing such goods – placing additional quality burdens on manufacturers.
How the management of quality must evolve
Although various tools exist to assist manufacturers with this complexity, thoughtful sourcing plays an essential part in driving positive changes to quality-management practices.
Management of quality can no longer rest solely with ERP modules or QMS systems; their efficacy has been diminished by manufacturing's increasing complexity, often featuring after-the-fact reporting only and lacking key contextualization points and analytical modules for in-depth data analysis. Deep root cause analysis frequently requires data export/import to tools like Minitab that require time, expertise, and user training/expertise for deeper root cause analyses.
One major challenge stemming from disparate systems is the fact these systems are typically owned by varying business units and sharing data is not always a given, or routine. Additionally, different systems use differing data taxonomies or formats that require substantial time spent cleaning before analysis becomes possible.
As today's manufacturing environment consists of highly technical components and consumers with unwavering expectations of quality, a paradigm shift is long overdue. Manufacturers must dramatically transform how they manage quality, increasing their ability to identify, contextualize, and address quality issues. With the continual rise of quality-related events, at least one new manufacturing regulation has been issued weekly since 1981, according to the National Association of Manufacturers research Regulation’s Impact on Manufacturing (83 parts of Code of Federal Regulations with over 23,000 quality controls or restrictions). Today’s manufacturers face an intricate regulatory environment they must navigate successfully to succeed.
Although regulations aim to safeguard consumers against quality impacts, governance alone will never suffice; fundamental changes must occur for manufacturers to consistently deliver high-quality products with features consumers seek.
Quality data, statistical process control (SPC), and real-time analytics become essential pillars for manufacturers navigating this ever-evolving environment successfully. A significant shift is also required, from simply conforming with specifications to producing products of true quality that meet stringent specification tolerances – no longer can reactive approaches to quality be tolerated within such a dynamic environment; proactive attitudes must replace reactive ones in terms of producing items that meet quality benchmarks in production processes and evaluation metrics.
Manufacturers in a dynamic environment face not only technological complexity but also an imperative to develop and cultivate a proactive mindset. Reactionary approaches to quality are insufficient given regulation complexity and volume and customer expectations with high demands for excellence. Committed continuous improvement coupled with cutting-edge tools and technologies enable manufacturers to weather storms more successfully while remaining market leaders.
As manufacturers head down this journey, success requires them to utilize technological prowess and regulatory acumen and to embrace an unwavering dedication to providing products of unparalleled quality. By doing this, manufacturers can not only meet but surpass public and consumer expectations in this era where quality assurance means progress and innovation.
Critical aspects of a quality management foundation
Manufacturers need to overcome the difficulty of keeping up with consumer demands for technological features without hindering production rates by following some key imperatives:
- Quality instrumentation such as automated test equipment (ATE) should be calibrated to identify defects autonomously; otherwise manufacturers risk getting stuck in an endless cycle of rework.
- Quality data must be accessible and analyzed immediately to be actionable, rather than waiting several weeks or months to perform root cause analysis on quality incidents.
- Insights into both process- and product-related quality data is equally crucial. When combined, it can create transformative insights that yield transformative solutions.
- Data from test systems, legacy systems, and other sources must be contextualized and communicated clearly for optimal analysis results. Analytics require consistent taxonomies of data for optimized usage.
- Predictive analytics are an asset for organizations. Although organizations should build up readiness through descriptive and prescriptive analytics approaches first, those that develop predictive quality analytical capacities will quickly surpass their competition.
- Quality is everyone's responsibility in an organization and provides an early indication of potential profits; thus, quality data must be made widely accessible so all stakeholders can access and understand its evolution.
- Discrete manufacturing typically includes multiple suppliers in addition to an OEM, so modern platforms like Microsoft Azure enable quality platforms that extend throughout a supply chain and enable inspection reduction by replacing it with more accurate forms of quality validation. When deployed properly, inspection becomes significantly less necessary and more precise methods of quality validation become possible.
- Digitized inspection records offer multiple advantages over paper records, including reduced compliance burden and significant depth to full spectrum analytics.
Predisys was among the pioneers to enter enterprise-grade SPC and quality analytics decades ago, investing significantly in R&D to develop an advanced solution that helps manufacturers attain quality beyond conformity. Thanks to the quality engineering staff and a strong partnership with Microsoft, Predisys remains an industry leader today in quality software.
Available in the Azure Marketplace, the Predisys Analytical Suite uses the Azure cloud infrastructure from a deployment perspective. The solution is a managed application that is deployed in the customer’s Azure tenant, providing the client with unequivocal data ownership and the world class-security protocols native to Azure.
The Predisys Analytical Suite enables data collection from existing quality infrastructure utilized in manufacturing, including automated test equipment, semi-automated test equipment where data is often further enriched by an operator prior to entry such as a coordinate measuring machine, manufacturing execution and enterprise resource planning systems, file import, and manual entry. All inbound quality data is normalized and made ready for analytics in near real time. These features along with the Azure infrastructure enable the application to rapidly scale throughout an organization’s footprint or through the entire supply chain. Advanced analytics and SPC charting are autonomously created in real time for immediate root cause analysis and analytics. The platform also features predictive analytical features that allow customers to become proactive from a quality perspective and not completely reactionary.
By empowering users to connect process inputs to product quality outcomes, the Predisys Analytical Suite on Azure is revolutionizing how quality is built into manufacturing. Visit the Predisys website to learn more.