We make decisions every day. Our project teams and organizations have many individuals making decisions every day. Most of these decisions have little to do with product reliability, yet a surprising number of design, marketing, production, and customer care decisions that have a direct impact on product reliability performance.
As a reliability professional, do you work to make better decisions? Do you work to enable the individuals designing, producing, marketing, etc your organization’s products to make better decisions concerning reliability?
If not, why?
Let’s outline a few ways to estimate the value to you and your organization to improve decision making concerning reliability.
Decisions, Uncertainty, and Results
Let’s say we are working on a product design and a key component is available from two vendors. They have similar capability and functionality, yet there is little information available concerning component reliability.
The design team will have to decide on a vendor and may include information about pricing, functionality, availability, and other readily available bits of information. The team also knows the reliability of part is critical to the system’s reliability performance.
Given this scenario, the decision may be a hunch or coin toss with respect to reliability.
Now let’s say there is a 50/50 chance that one vendor has adequate reliability and the other does not. Of course, this could become more complex as both could be just fine or both dismal concerning reliability in our application. Also, the difference in component reliability performance may be close or distant or variable.
Let’s keep it simple, and say there is a 50/50 change one vendor has a reliability part while the other does’t. We don’t know which, at the moment. Thus, at the moment, there is a 50% chance of having a successful product concerning it’s reliability performance and we enjoy the benefits of product sales and associated profit. And, there is a 50% chance of enjoying higher than expected warranty returns, rework, maybe a recall, if it’s really bad, loss of sales and damage to the brand.
50% for a $100k profit over the first year, or a 50% chance of an extra $100k in warranty expenses makes the decision mute, just roll the dice and ship, you are expected to break even.
What is a Better Decision?
I’m defining a better decision as one that leads to desired results more often. Better as in avoiding making the wrong choice more often.
This not the same as making a perfect decision. In order to select a vendor and ship the product we have to make a decision and cannot wait till we have all the information to make the right decision with 100% certainty.
Better means we have better information then previously that enables us to make informed decisions that shift the chance of making the right decision up just a bit.
How a Change in Uncertainty Creates Value
If we learn just little more about the component reliability performance of the two vendor’s components we alter the chance of selecting the right vendor concerning reliability.
Let’s say in our simple example the two vendors provide results of a simple life test. The testing isn’t perfect for our application and stresses, yet does show one vendor as being a bit more robust in general.
Let’s say this alters the chance of selecting the right solution from a 50/50 chance to a 75/25 ratio. That means we have a 75% chance of enjoying the $100k profit and a 25% chance of enjoy a $100k increase in warranty costs. That becomes a present value of 0.75 x $100k – 0.25 x $100k or $50k expected return on the decision up from $0 before. That is a change of $50k, which is the value of the additional information.
3 Ways a Reliability Engineer Can Reduce Uncertainty
First, determine the cost of a field failure. Not a total warranty expense, nor impact to your customer, instead work out the cost of failure per unit that fails. Also, estimate the cost per failure per unit shipped. I find the second approach sets the cost of failure in the same units as a bill of material costs, component costs.
In either case, when design engineers know the cost of failure along side the purchase cost of a component then can quickly assess the relative impact or merit of component reliablity claims. It informs their vendor selection decision.
Second, improve the ability of your team to gather and understand reliability information from vendors or life testing. Passing a test with any number of samples under some concocted set of conditions doesn’t help anyone estimate reliability performance. A data sheet MTBF value, likewise, is of little value.
Help your team ask the right questions of vendors concerning reliability and help your team to interpret responses correctly. A bit of training, either one to one or in small groups or by example, all helps.
Third, for critical to reliability elements of your product work directly with the team to reduce the uncertainty of the pending decisions concerning reliability. Need a better, more accurate, reliability estimate? Maybe pursue better information from the vendor, conduct your own testing, gather relevant field data from previous products, find or build a physics of failure model, etc. Help your team reduce the unknown about the reliability aspects for an upcoming decision.
This is a short article with a simple example. In your world this is likely a bit more complex, yet the concept remains. Our work to improve the information and ability of our teams to make better decisions improves the reliability performance thus results.
Our goal as reliability professionals is to enable every decision that impacts reliability to be better.
There are decisions being made today. How are you going to improve the odds of those decisions being made such that they realize the desired reliability performance? There are many ways we can reduce uncertainty, which are your favorites?
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