By | October 26, 2020

The fault in our cars—one of the most ubiquitous of all consumer products—is something companies cannot take lightly.


For most of us, cars are our second biggest investment after our homes, and it is probably not an exaggeration to say that faults and defects in our cars are a source of major headaches and we have little tolerance for it. The automobile market, like hundreds of thousands of other products, is saturated with options, and manufacturers are fighting tooth and nail for our dollars. The quality and reliability of these products is something that companies simply cannot ignore, and, of course, this is true for new and innovative products, too.


Quality should never be left ‘up in the air.’


In 2018 at the International Motor Show in Geneva, Switzerland, Dutch aircraft company PAL-V unveiled the PAL-V Liberty vehicle that looks like a cross between a helicopter and a three-wheeled motorcycle. The very idea of a flying automobile actually goes back 100 years when inventor Glenn Curtiss designed and built an “autoplane,” but it never achieved full flight.

A century later, it appears we are finally close to seeing Curtiss’ dream reach new heights. The PAL-V is scheduled to “hit the skies” in Europe in 2019 with an initial launch of just 90 units, so, there won’t be many of these “cars” maneuvering through the troposphere anytime soon, but if or when they do debut, the sky’s the limit for possible new commuting options—as well as some new potential faults that would need to be explored thoroughly before liftoff. (Full disclosure: We are using this flying vehicle as an example only; Sphera has not evaluated this machine.)

For the automobile industry in general, failure modes and effects analysis (FMEA)—basically defined as a systematic approach to identify defects in products and processes and help prevent or mitigate them—has been a vital part of the manufacturing process for over six decades now. Stemming from the automotive sector in North America and practiced globally is the Advanced Product Quality Planning (APQP) standard. In Europe, there is the German Verband der Automobilindustrie (VDA) standard. As Quality Digest detailed in an article last year, “Generally, the Germans have been historically focused on DFMEA [design FMEA] and the Americans on process FMEA (PFMEA). Although this is generally true, during the past five years, efforts have been made in the U.S. automotive industry to focus on DFMEA as well.”

There are ongoing efforts to amalgamate these two methods into one international standard, and the hope is that there will be clarity on that sooner rather than later.

The Door Is Ajar, But Why?

A lot can go wrong with automotive product design, from the innocuous parts such as doors, handles, lighting, wipers, etc., to the immensely complex integrated systems housed inside the dashboard.

Similarly, the manufacturing process also needs to be thoroughly risk-evaluated and tested before a ride is ready to hit the roads or the skyways in our example. The recent recall of the latest model of the perennially popular Toyota Camry because of out-of-spec parts shows that quality, safety, reliability and a company’s reputation are all on the line with every production cycle. The root cause faults may appear to be unremarkable at face value, but the outcome can be severe.

One recent extreme case is the Takata air bag recall where the National Highway Traffic Safety Administration (NHTSA) determined the root cause was the lack of a chemical drying agent in the propellant used in the air bags. The outcome was multiple deaths, millions of recalled vehicles and bankruptcy for Takata. A relatively less severe case is Tesla’s proactive recall of its 123,000 Model S electric cars because of excessive corrosion of the power-steering bolts.

Companies grapple with potential safety, financial, environmental and reputational risks through all phases of their product’s development, and FMEA plays a crucial role in helping them meet organizational standards and state or federal compliance regulations.

No Quotas On Quality

A modern premium car has over 30,000 mechanical and electronic parts. Additionally, as sophisticated as the production processes already are, they’ve become even more complex to accommodate an increasingly greater variety of product models to meet customers’ demand and to speed production rates in the race to be first to market. The quality, reliability and safety of cars  and  indeed  any consumer  product  depends on a well-thought-out enterprise quality management solution that ties together the various inductive and deductive Operational Risk techniques. This inevitably includes execution of various types of FMEA (concept, design, process, machinery, service, safety, software, etc.), which is an inductive type, to identify and address potential risks in all stages of the product development cycle from cradle to grave.

An FMEA, like any other content, is dependable only when its information is relevant and meaningful because of systematic analysis by the right experts. It must be generated on a standardized quality management platform across the organization that drives consistency and compliance across the myriad development and manufacturing activities. Then it must be mined appropriately with the correct application of the business intelligence tools.


A basic FMEA issue is when workers are more concerned with checking a box than executing the FMEA procedure with the required rigor. FMEA must be completed at the right time by the right number of people with the right expertise. Wrong or ambiguous data defeats the purpose of the quality program. The devil is in the details, and whether it is a complex flying car or a simple toy, the level of detail and accuracy of the FMEA content used at the right time drives its efficacy.

Facilitation Orientation

The common bathtub model that describes the failure characteristics of hardware over time is well- understood in  terms of  “burn  in,” “useful life” and “wear-out” phases. The quality standards and methodologies prescribed by the AIAG-APQP, VDA, Design for Six Sigma (DFSS) program, lean manufacturing approach, International Organization for Standardization (ISO) and Society of Automotive Engineers (SAE) standards,  etc.,  provide  the framework of techniques and procedures for product development and manufacturing to optimize quality and reliability. FMEAs play a special and irreplaceable role in countering failures in manufacturing beyond engineering design, best practices and statistical analysis tools.

With the advent of cyber connectivity in cars, autonomous driving and artificial intelligence technologies, the automobile risks have grown exponentially. According to a recent article in MIT Technology Review: “These vehicles will have to anticipate and defend against a full spectrum of malicious attackers wielding both traditional cyberattacks and a new generation of attacks based on so-called adversarial machine learning.”

There are a 100 million lines of software code in a typical modern automobile. All this calls for new and improved risk assessment techniques to analyze these technologies, which can perhaps be a variant of FMEA, or a hybrid of FMEA and hazards and operability analysis—better known as a HAZOP—or another risk analysis approach.

There are numerous proposed models to describe the failure characteristics of software in terms of test/debug, useful life and obsolescence phases. The automotive specific ISO 26262 functional safety standard addresses safety critical hardware and software components. And the IEEE papers “SW FMEA for ISO-26262 Software Development” and “Integrated Analysis of Software FMEA and FTA” are steps in the right direction.

While we are many years away from reaching the “useful life” phase of any “Jetsonian” flying cars or “roadable aircrafts” for the masses, the future of commuting might very well be a “cloud”- based endeavor if the potential failures can be identified and addressed. It just as well could remain a lofty goal for the foreseeable future.

James Tehrani contributed to this article.