Hardware Test and Reliability

One of the best ways to achieve high product reliability is to build it in from the beginning. Items such as material selection, geometry, and system architecture are essential for product longevity, and, in many cases, evaluation in these areas can begin without a prototype.

Other focus areas in the design for reliability space include identifying use cases, stresses, and knowledge gaps. By beginning the right work sooner, more answers can be available when they are needed.

Examples of services you can leverage in the Design for Reliability space include:

• Design Reviews

• Material Selection

• Use Case Definition

• Custom Test Development

Establishing the right manufacturing practices is critical for product reliability. Even the most reliable designs can become unreliable if manufacturing processes are not dialed in. Additionally, manufacturing in high volumes is the first opportunity to understand low-dppm failure modes that may not be detectible during the design phase, when typically only lower volumes are available.

Examples of services you can leverage in the Reliability for Manufacturing space include:

• Ongoing Reliability Testing (ORT)

• Custom Test Development

• Failure Analysis

Field data provides valuable insights into how a product is performing and actually being used in the field. The opportunities provided by field data are numerous, and include confirming assumptions about product use cases and performance, identifying new use cases, identifying new failure modes, and quantifying metrics that could not be quantified in the design and manufacturing phases.

Field data can be used to improve products and get ahead of major issues.

Examples of services you can leverage in the Field Reliability space include:

• RMA Process Design

• Field Data Architecture

• Data Analysis

• Warranty Returns

• Failure Analysis

• Remediations

Your data sheet says your product has a warranty of a certain number years, but how can you be sure that your product will actually last for that period of time?

It starts with developing the right specs, for example, by translating use cases into engineering requirements against which the product can be evaluated.

Examples of services you can leverage in the Spec Development space include:

• Use case evaluation

• Spec Development

• Custom Test Development

Because every product is unique, standard tests may not cover every situation your product will encounter. Standard tests could be too harsh, not harsh enough, or simply different from what you need.

Using the wrong test can result in engineering time spent fixing issues that will never appear in the field or, conversely, missing a failure mode that later results in high volumes of customer returns.

Custom tests can help build confidence that your product will perform when your customers need it most.

Examples of services you can leverage in the Custom Test Development space include:

• Custom test design specifically tailored to your product’s needs

• Test Execution

• Data Analysis

• Failure Analysis

Data is at the heart of Reliability Engineering. In order to truly understand product performance, Reliability Teams will often need to augment their data with data produced by other teams. For example, even determining a simple metric such as how long a device from a certain manufacturing cohort was in the field before failure may require integrating data from multiple departments such as manufacturing, supply chain, customer support, and engineering.

Integrating data from multiple departments for reliability purposes presents unique challenges. Even if a company has a mature data architecture, reliability teams often require higher data quality standards, higher accuracy, and more information from unstructured data than some of their counterparts.

While data teams are critical, reliability data architecture development typically benefits from reliability-specific subject matter expertise.

Examples of services you can leverage in the Reliability Data Architecture space include:

• Leading cross-functional efforts to understand which data is needed to define critical reliability metrics

• Business system architecture to add, standardize, or otherwise modify critical aspects to enable reliability analysis

• Analytics engineering

• dbt development, including writing all dbt code

• Dashboard development

• Automated reliability analysis scripts (i.e. LDA)

• Development and Implementation of a Data Quality system for reliability data models

• Data maintenance

• Tech Stacks: Snowflake, BigQuery, dbt, Hex, Deepnote, Tableau, Looker

Some reliability teams have more data than they are able to process. If this describes your team, then please reach out.

Examples of services you can leverage in the Data Analysis space include:

• Performing standard reliability data analyses

• Data analysis automation. For example, developing Python scripts and dashboards