Electronics integration is prevalent in many markets, perhaps none more so than the automotive industry. As a result, physics-based computer aided engineering (CAE) tools have taken vehicle, subsystem and component evaluations off the road and into the lab, allowing for increased design complexities – and necessitating major reliability testing process changes.
Rethinking Reliability Testing
Simply put, traditional Design-Build-Test-Fix (DBTF) methods can no longer keep pace with the advancements in automotive electronics, or the competitive pressures for efficiency and effectiveness these advancements create. To address these shortcomings, a number of automotive manufacturers are transitioning to physics-based modeling.
The immediate benefit of replacing trial and error with virtual simulation using Physics of Failure (PoF) is twofold – saving time and money by eliminating physical prototypes, and freeing automotive engineers to easily and economically pursue a number of design ideas to determine best options. On a broader level, PoF paired with CAE tools allows automotive manufacturers to combine virtual and physical testing for faster, more accurate product development based on life expectations, reliability distributions and risk prioritization.
The Physics-based Solution
Optimizing virtual simulation, testing and reliability assurance for electronic automotive applications requires a sophisticated but user-friendly CAE tool, like Sherlock Automated Design Analysis™ software. Sherlock integrates design rules, best practices and a physics-based understanding of product reliability into a comprehensive multi-step model analysis:
Design capture: Standard PCB CAD/CAM design files are used to automatically define the laminate, layers, thickness and density of a computer-generated circuit board model. Sherlock also imports the bill of material (BOM) parts list that contains supplier part numbers and JEDEC package types.
Define reliability goals: Critical to the entire process is clearly delineating two key metrics – desired lifetime (the time a customer is satisfied with a product) and product performance (survivability of the desired lifetime).
Define environments: Two prevalent approaches exist for defining environments, using industry specifications like SAE J1211, or using actual measurements based on similar products in similar environments. For automotive applications, the latter is typically chosen to gauge temperature cycling since it more accurately reflects actual conditions.
Generate inputs: Sherlock allows the user to detail thermal, vibration and shock stress profiles. An automotive electronics profile, for example, might focus on the outside of the engine compartment with minimal power dissipation and daily temperature cycling providing the primary degradation-inducing load.
Perform analysis: Based on the user-defined reliability requirements and environment, Sherlock is capable of analyzing:
- Conductive Anodic Filament Formation (CAF)
- Failure Rate via MIL-HNDBK-217, SR-332 or IEC-62380
- Plated Through Hole Fatigue
- Solder Joint Fatigue
- In-Circuit Test (ICT)
Interpret results: Sherlock’s physics-based modeling produces a detailed, application-specific PoF life curve that, unlike single point constant failure rate estimates, helps automotive engineers determine if a design is capable of surviving the intended test and use environment conditions, as validated by real testing.
Sherlock provides automotive manufacturers with validated reliability modeling that is faster than DBTF and, moreover, aligns with the engineering practices and complex products of today’s automotive industry. Contact us today to learn more about how Sherlock can work for you.