RAMS Technical Paper
The purpose of this tutorial is to highlight key traits for the effective management of a reliability program. The basic premise is no single list of reliability activities will work for every product. Every product development and production team faces a different history, constraints, and a different set of variables and uncertainties. Such that what worked for the last program may or may not be appropriate for the current project. There are a handful of key traits that separate the valuable programs from the merely busy programs. These traits and the underlying structure can provide a framework to create a cost effective and efficient reliability program.
A product’s design, supply chain and assembly process in large part establish the product’s reliability performance. A product well suited for the use application will meet or exceed the customer’s durability expectations. The myriad of decisions by the entire design and production team creates the eventual product reliability performance. The structure for these decisions is the focus on this tutorial.
Considering that each activity of a design team takes resources such as time and money to accomplish, focusing the use of these resources on activities of high value is a common strategy. Including product reliability in the value proposition permits the entire team to weigh the importance of product reliability and the appropriate use of tools to accomplish both the business and product reliability objectives.
The basic premise of this tutorial is the underlying concept that no one set of reliability activities is appropriate for every product development situation. Selecting and integrating the best tools permits the execution of an effective and efficient reliability program.
The traits of very good reliability programs and examples of very poor practices in this tutorial serve to illustrate how to approach establishing an effective reliability program. Highlighting the basic structure along with guidelines on how to tailor a reliability program will permit the repeatable creation of reliable products.
This paper develops a process based cost model for warranty events and applies it to a number of product instances in the computer and related high tech businesses. It identifies the principle support ‘meta-processes’ that typically contributes>70% to the total cost of warranty. From this model the key warranty cost drivers are identified and the set of strategies are derived that product development teams can use to reduce the cost of warranty for products under development. Proven frameworks for applying the model and warranty cost reduction strategies during the product development cycle are presented.
Case study instances are presented that illustrate how product development teams have applied the model, strategies and frameworks that reduced the total warranty costs by 35% are discussed.
The total cost of warranty for computer and related hightechnology US based companies is now ~$8B per/year .
For many companies, their warranty costs approaches what they spend on new product development and often matched their net profit margins; this is particularly true for the ‘commodity’ type businesses such as PCs or personal printers. Many companies are moving toward an extended warranty strategy to manage warranty costs. But, this is no panacea. While extended warranty repairs costs may be considered an operational expense and not a ‘warranty expense” from a SEC [10-K] perspective, the effects of poorer product quality than planned impacts the business’s bottom line with the same force as warranty costs.
In the past few years the available choices of service processes used to resolve warranty issues has expanded to include phone support, Web based and customer self-fix schemes. This trend has been driven by need to reduce warranty cost and accelerated by the maturation of the internet. As both consumer and commercial products continue to increase the software/firmware to hardware component mix, these less costly processes need to be utilized more and more Why? The costs per repair of these service processes range over 1-1/2 orders of magnitude; from $30/call for a warrant resolved over the phone to >$700 for on-site repairs. More importantly, the repair process costs are the largest contributor to the total cost of warranty; part cost contribution is typically less than 30% for most products.
Because of the business impact of the cost of warranty, product development teams are now being challenged to design products that are both less costly to repair (business metric: warranty $s) and more reliable (business metric: annual failure rates, AFR). To more easily meet this challenge will require warranty costs models that make explicit not only the impact of AFR on cost, but also the effect of the process costs associated with the repair of specific failure modes.
Currently used warranty cost models are dominated by traditional Failure Modes and Effects Analysis (FMEA), cost pool based models or models utilizing statistics and simulation forecasting techniques . FMEAs are heavily used by the hardware engineering community in the Aerospace, Military and Auto business segments. Cost pool based models are most frequently used by the financial and supply chain communities. FMEA is a proven methodology for first identifying failure modes or failure mode scenarios [2,3], then developing strategies to mitigate the risk for each failure mode during a product’s development cycle instead of after product launch. The most popular FMEA methodologies use the RPN scheme to prioritize the failure modes, or when cost is used , the method is mute on how a product team calculates cost of repair. Cost pool based models aggregate warranty costs into large cost pools such as monthly costs for labor, call centers, material, labor and inventory/logistics. These cost pool based models  are a natural fit for warranty cost reduction efforts for the supply chain and procurement areas. Yet, none meets the full needs for modeling of the development team: the model needs to have the following characteristics:
• The customer’s problem being resolved is explicit.
• The support processes used to diagnose and resolve the warranty event are explicit.
• Estimating warranty costs is relatively quick and easy to do, especially when evaluating design alternatives.
This paper develops a service process based warranty cost model for warranty events that is grounded in both the customer’s problem and the support process used to resolve it. It will identify the primary ‘meta-processes’ used by most computer and high-tech businesses to service warranty events. Typical standard costs for each of these will be discussed. We will demonstrate that these process based cost models are particularly useful for the computer and other high technology businesses for both the commercial or consumer market spaces. They are less useful for the Automotive, Aerospace or Military business segments because of the support strategies used in those market spaces.
From this model, the key cost drivers will be extracted from which we will also develop the primary strategies that product development teams can use to both improve product reliability and deduce its warranty costs.
Results from case studies will demonstrate how product development teams have used this model to develop design alternatives and action plans to reduce warranty costs. While presenting the case study a few frameworks will be introduces that the development team used to evaluate what strategies may be affective for reducing costs of specific event types and to identify dependencies deeded to realize the planned cost reductions.
When introducing a product into a new market, determining the current market players’ reliability performance may lead to a competitive advantage. Or, if your competition is using reliability as a marketing lead, does your product match their performance or do they have the advantage?
Using Competitive Analysis, we can determine areas of strength as well as areas of weakness so that we can develop a plan for reliability improvement. Competitive Analysis often uses tools such as Reliability Predictions, Failure Modes and Effects Analyses (FMEAs) and Highly Accelerated Life Tests (HALTs) to compare your product with that of your competition.
The objective of a Competitive Analysis is to compare your product to competitors’ from a reliability perspective. The best time to perform a Competitive Analysis is on engineering prototypes or early production.
Two valuable analytical techniques used during the Competitive Analysis are the Teardown Analysis and Competitive HALT.
In the Teardown Analysis, we choose specific attributes to compare two or more products and then take each product apart in order to analyze and compare them with regard to the chosen attributes.
A Competitive HALT is used to compare levels of robustness for two different products.