Blog - Accendo Reliability

Product Reliability Participants – Part 1

An effective product reliability process requires a strong team, at every level. The team of employees within an organization that participate and impact product reliability is a vast and widespread group of people. They include members of the design team, design managers, quality and reliability engineers and managers, procurement engineers and managers, warranty managers, failure analysis specialists, members of the marketing and sales staff, members of the finance and manufacturing teams, and field service and call center staffs. [Read more…]

by Fred Schenkelberg Leave a Comment

Reliability Organization – Part 2

Decision Focus and Value

Last week I discussed how the aspects of the structure of an organization relate to product reliability. Related to that, this week the discussion will remain on the level of a reliability organization but will look at something a bit more intangible – how decision-making policy and practice affects product reliability. [Read more…]

by Fred Schenkelberg Leave a Comment

Reliability Organization – Part 1

Both organizational structure and decision-making policies have an impact on improving product reliability. The former is more quantifiable whereas the latter involves more intangible subtleties. First, in this post, I’ll discuss the connection between organizational structure and reliability, and in a follow-up post, I’ll address reliability and decision focus, still within the structure of an organization. [Read more…]

by Fred Schenkelberg 1 Comment

Equal Variance Hypothesis

Hypothesis testing of paired data may include two populations that have the equal standard deviations. The t-test for differences considered in a previous post used the standard deviation of the differences. In this test, we want to consider if one population is different in some way than the other and we use the samples from each population directly. [Read more…]

by Fred Schenkelberg 1 Comment

Paired-Comparison Hypothesis Tests

Hypothesis testing previously discussed (link to past posts) generally considered samples from two populations. Maybe the experiments explored design changes, different component vendors, or two groups of customers. Occasionally you may find data that has some relationship between the samples, or where the samples are from the same population. Paired (or matched) data involves samples that are related in some meaningful way. [Read more…]

by Fred Schenkelberg 2 Comments

Influence and Reliability

Reliability professionals today have a challenge. Engineering and operations staff members are taught to think for themselves, to make decisions, to get things done. The entire staff is highly educated, motivated and willing to lead a team or organization to results. In order to be effective as a reliability profession, we have to engage those independent and fast moving individuals. We have to compel others to listen to and understand reliability predictions, risk assessments and models. If they listen and act on the information we provide, they then may fully consider the impact of decisions on reliability performance. [Read more…]

by Fred Schenkelberg Leave a Comment

Reliability Program Structure

A product reliability program is a process. Like any process, it has inputs and outputs, generally some form of an objective, and feedback. Furthermore, the process may or may not be controlled, or even a conscious part of the organization. Reliability may just happen, good or bad. Results may or may not be known or understood.

In some organizations, the reliability program may be highly structured with required activities at each stage along the product lifecycle. In other organizations, reliability is considered as a set of tests (e.g. environmental or safety compliance). In some organizations, reliability is effectively a part of everyone’s role. [Read more…]

by Fred Schenkelberg 1 Comment

Hypothesis Tests for Variance Case I

Statistics is the language of variation. Everything varies, and we use variance (σ²) to describe the spread of the data. For any experimental work aimed at making improvements, whether in the design, manufacturing process or field performance, there are two ways to make improvements. Move the center of the distribution, or reduce the spread of the data. [Read more…]

by Fred Schenkelberg 3 Comments

Hypothesis Tests for Proportion

This is also called the “p test”

When comparing proportions that are from a population with a fixed number of independent trials and each trial has a constant probability of one or another outcome (Bernoulli experiments) then we can use a p test. p is the probability of success, and 1-p is the probability of failure. Caution: stay consistent once you define success otherwise, like me, you’ll have a bit of confusion. n is the number of trials. [Read more…]

by Fred Schenkelberg Leave a Comment

Reliability Goals

The target, objective, mission or goal is the statement that provides a design team with focus and direction. A well-stated goal will establish the business connection to the technical decisions, related to product durability expectations. A well-stated goal provides clarity across the organization and permits a common language for discussing design, supply chain, and manufacturing decisions.

Let’s explore the definition of a ‘well-stated reliability goal.’ First, is it not simple MTBF, “as good as or better than…” or ‘a 5-year product’. These are common ‘goals’ found across many industries, yet none permit a clear technical understanding of the durability expectations for the product.
The common definition for reliability is [Read more…]

by Fred Schenkelberg 12 Comments

K Out of N

The design of a product includes the arrangement of all of the product elements. When considering the reliability of a system, the arrangement matters. Many systems are arranged serially. This means that with the failure of any one element, the system will not work. See the article on Series Systems for more details. [Read more…]

by Fred Schenkelberg 2 Comments

HALT Value

It’s always necessary to estimate the value of specific reliability activities. It is needed to justify the investment required to accomplish the task. Prototypes, diagnostics equipment, and environmental chambers are expensive. The difficulty is an inability to know what will be found, before conducting the experiment.

Not doing the test means the certainty of not finding anything. That is often not enough motivation to invest, to learn something about the reliability performance. The following scenario is just one situation, along with a few ideas to help you estimate the value of investments in reliability work. [Read more…]

by Richard Coronado Leave a Comment

Design of Experiments

Design of Experiments (DoE) and the Analysis of Variance (ANOVA) techniques are economical and powerful methods for determining the statistically significant effects and interactions in multivariable situations. DoE may be utilized for optimizing product designs, as well as for addressing quality and reliability deficiencies. Within the DoE framework, the practitioner may explore the effects of a single variable or analyze multiple variables. [Read more…]

by Richard Coronado 3 Comments

FRACAS

The Failure Reporting and Corrective Action System (FRACAS) is a closed-loop process whose purpose is to provide a systematic way to report, organize and analyze failure data. Implementation of a FRACAS has increasingly become commonplace within an industry. The requirement for implementation of some type of FRACAS within a DoD program was first established in 1985 with MIL-STD-2155. However, in 1995 that standard was reestablished with no changes to content as a handbook, MIL-HDBK-2155, and was recommended as guidance. Today, multiple software solutions exist that provide all the functionality required of a FRACAS. [Read more…]

by Richard Coronado 1 Comment

Reliability Allocations

After the system has been drawn in block diagram form, subsystem and component reliability goals and targets are established. This is a common practice in the development of complex systems, particularly when different design teams or subcontractors are involved. Reliability allocation involves setting reliability objectives for components or subsystems in order to meet a system reliability objective and should occur in the initial stages of design or prior to designing major system upgrades. [Read more…]