Not too long ago, the Indianapolis 500 took place. It is, of course, one of the highlights of the automobile racing circuit. If you follow automobile racing, you will be aware of a certain characteristic of every auto race, and, surprisingly, can tell us something interesting and valuable about our approach to quality.
It might not be what one would expect, such as the quality of the automobile, although that’s important. It is also not the quality of the crew and how fast and well-coordinated they are during pit-stops, although that too is crucial. Could it be that the key distinction has to do with understanding that life is different at different speeds?
After a few turns around the racetrack, two or three racers invariably form a group in the front. Some distance behind them, there is another group containing most of the other racers, and then another small group brings up the rear. All these groups of racers are traveling at different rates of speed. The crucial point to note is that an obstacle on the race course, let’s say, a soft drink can, means something different to each of these groups.
Generalizing (in order to make a point) we can assert that this obstacle can seriously damage someone in the first group, but it might go unnoticed by the last. During the same interval of time, the front group has covered much more ground than the last group, and at the speed, they are driving, could go out of control when encountering an anomaly on the race course. Their reactions must be instantaneous. The slowest group has time to react to changes or anomalies before spinning out of control, so that the gap available to them, the time between noticing an anomaly and responding to it is larger, in contrast to the leaders.
It’s all about reaction time: Quality versus Quality Assurance
The crucial distinction between “quality” and “quality assurance” is reaction time. How many processes are happening during one day in your external and internal production network?
The likelihood is that it will be difficult to count the number of actions that are critical to quality, and important to satisfying your customer on any given day.
Much of what we call “Quality” is about the effort to collect documentation at every stage of the process. Reports flow in, perhaps in varying formats, from all parts of your supply chain. They are organized, reviewed and filed. Many of them are related to government requirements. However, no matter how comprehensive the reports are (which may vary in thoroughness and reliability) there may be no suitable analysis available to support the real-time reactions necessary to avert disaster.
In contrast, to deserve the label of “quality assurance”, quality professionals must monitor processes so that there are no gaps between a quality issue (or even a trend in the wrong direction) its analysis, follow-on alerts, and an appropriate response. QA must be dynamic, akin to the immediate response that top level race car drivers have that allows them to correct their lines and stay at the front of the pack. In other words, signals must not only arrive from all the stages of the manufacturing processes in a timely manner, they must be understood when they arrive, and trigger a response that prevents the subsequent links of a supply chain from being contaminated, or from reaching the market.
Time, the Wild Card
If we have our driver’s license, we’ve likely been asked the question about how big the distance between us and the driver in front of us has to be in order to avoid a collision. In fact, on a dry road, traveling at 65 miles per hour, it would take us over 200 feet to stop our car. The calculation assumes that we see the obstacle, however and that we take corrective action in time to avert the crash. Every year, we hear about massive pileups of cars, chain reactions caused by an inability to either see an obstacle (because of fog) or to react to it in time.
Quality assurance methods can shrink that time gap in manufacturing. Those methods are very different than quality document collection. Therefore, Quality Assurance depends, initially, on our understanding of the size of the challenge we are facing, and our ability to calculate the probability of how a “crash” at any one point will destabilize the rest of the production network. The challenge is to quickly evaluate the degree of risk and respond to it. The more complex the supply chain, the more important it is to calculate the probabilities of each link functioning the way they should. One of the most common and easily made mistakes is to assume that the probability of a successful outcome is calculated by adding up the reliability of each link and averaging the sum. For example:
In fact, the probability is calculated by multiplying the percentages.
If even one link, which individually is calculated to be 99.9 percent reliable, is added to this chain, the result is 87.333 reliable.
Key tools for Quality Assurance
Given how steep the drop-off in quality can be relative to response time, especially if your company is at “the front of the pack,” it’s important to identify with precision what it will take to turn the myriad documents and reports into a dynamic response.
Specification Validation and Statistical Process Control (SPC)
Performing specification validation requires agreement upfront about the specifications governing the materials and parts in play. Then, the testing regimen must be executed to ensure specification compliance before materials/parts move to the next tier of external sourcing or to the next phase of internal production.
Statistical Process Control (SPC) procedures can help you monitor process behavior. When the process is electronic, SPC allows you to not only record data in close to real time; it allows you to see anomalies. More importantly, SPC can help you differentiate between normal variations, since these are always present and intrinsic to any process, and “special cause” variations, which stem from causes external to the process, and something unusual has occurred that requires a dynamic, and decisive response before the anomaly contaminates the entire production process. It is also useful for identifying any attempts at manipulating statistics, something that is more likely to succeed when your system relies on individual paper documents or their electronic equivalents. Recent court events confirm that quality document adulteration is here and can have serious implications.
A clear path forward is available from EMNS. The Software-as-a-Service GSQA® provides manufacturers the best practices in supplier quality and supply chain quality assurance currently in use across 70 countries for monitoring external and internal production QA. GSQA’s highly automated SaaS (Software-as-a-Service) solution simplifies quality assurance and compliance activities with customers, suppliers, co-manufacturers, internal production facilities. GSQA’s unique e-COA® with ASN immediately validates material/parts test results against specifications (material validation) at any checkpoint in the supply chain.
GSQA® also provides automatic SPC analysis, regulatory document compliance, web-based nonconformance management and forward/backward/where-used traceability for full product genealogy. GSQA® real-time analysis and alerts help reduce material variability and all its challenges 24×7 around the world and may be appropriate in your world if day-in and day out quality assurance is essential.