BQR CARE Deep Dive: Unified RAMS Analysis for…

The Problem With Fragmented RAMS Tools

Reliability, Availability, Maintainability, and Safety (RAMS) analysis for a complex system involves multiple interdependent analyses: FMEA to identify failure modes and their effects, FMECA to rank failure modes by criticality, Fault Tree Analysis to model the logic of hazardous events, Reliability Block Diagrams to calculate system availability, and testability analysis to ensure that failures can be detected and isolated.

In many Indian engineering organizations, these analyses are performed using disconnected tools, spreadsheets for FMEA, standalone fault tree software, custom scripts for RBD calculations, and manual methods for testability assessment. Each tool has its own data format, its own component database, and its own assumptions about the system architecture. When a design change modifies a component’s failure rate or adds a new failure mode, every tool must be updated independently.

Data consistency across analyses depends entirely on the engineer’s diligence, and in a complex system with thousands of components and hundreds of failure modes, manual consistency is unreliable.

BQR’s CARE (Computer Aided Reliability Engineering) platform eliminates this fragmentation by unifying all RAMS analyses in a single integrated environment with a shared system model and a common component database.

FMEA and FMECA

CARE’s FMEA module supports both hardware FMEA (per MIL-STD-1629A, IEC 60812) and functional FMEA (per SAE J1739, AIAG-VDA). The system model is built hierarchically, system, subsystem, assembly, component, with failure modes, failure rates, and local effects defined at the component level. CARE propagates failure effects upward through the hierarchy automatically, determining the next-higher-level effect and the end effect at the system level.

The FMECA extension adds criticality analysis per MIL-STD-1629A Task 102. Each failure mode is assigned a severity classification, a failure mode ratio (the fraction of the component’s total failure rate attributable to this mode), and a detection probability. CARE computes the criticality number for each failure mode and generates Pareto charts ranking failure modes by criticality, enabling the design team to focus risk mitigation on the failure modes that contribute most to system risk.

For automotive applications following the AIAG-VDA FMEA methodology, CARE supports the seven-step process including structure analysis, function analysis, failure analysis, risk analysis (with Action Priority numbers replacing the traditional RPN), and optimization.

Fault Tree Analysis

CARE’s FTA module constructs fault trees using standard gate types, AND, OR, k-out-of-n (voting), inhibit, priority AND, and exclusive OR. The tree can be built top-down (from the undesired top event to basic events) or generated automatically from the FMEA data by tracing failure effect propagation paths.

Qualitative analysis identifies the minimal cut sets, the smallest combinations of basic events that cause the top event. Quantitative analysis calculates the top event probability, the importance measures (Birnbaum, Fussell-Vesely, Risk Achievement Worth, Risk Reduction Worth) for each basic event, and the time-dependent unavailability when component failure and repair rates are specified.

CARE also supports Common Cause Failure (CCF) modeling using the beta factor method, Multiple Greek Letter method, and alpha factor method, essential for systems with redundant components that may share common failure mechanisms (environmental stress, manufacturing defects, maintenance errors).

Reliability Block Diagrams

The RBD module models system availability using series, parallel, standby, k-out-of-n, and complex (bridge) configurations. For each configuration, CARE calculates steady-state availability, mean time between system failures, and the expected number of system failures over a mission time.

Monte Carlo simulation handles complex configurations that cannot be solved analytically, systems with dependent failures, non-exponential repair time distributions, limited repair resources, or complex standby switching logic. The simulation runs thousands of system life histories, computing the statistical distribution of availability, downtime, and failure frequency.

Testability Analysis

Testability analysis determines how effectively the system’s built-in test (BIT) and external test equipment can detect and isolate failures. CARE’s testability module maps the relationship between failure modes and test observables (test points, BIT indications, performance parameters), computing fault detection coverage, fault isolation resolution, and ambiguity group sizes.

For Indian defense programs where testability requirements (such as failure detection within 95% and isolation to a single LRU within 90%) are contractual obligations, CARE provides the analytical evidence that the test strategy meets these requirements, or identifies the gaps that require additional test points or diagnostic logic.

Multi-Standard Compliance

CARE supports the reliability and safety standards most commonly referenced in Indian defense, aerospace, rail, and automotive programs:

MIL-STD-882E: System Safety
MIL-STD-1629A: FMEA/FMECA
IEC 60812: FMEA (international)
IEC 61025: Fault Tree Analysis
IEC 61078: Reliability Block Diagrams
SAE J1739 / AIAG-VDA: Automotive FMEA
EN 50126/50128/50129: Railway RAMS

Reports generated by CARE are structured for audit review, with full traceability from top-level safety requirements through fault tree gates to component-level failure modes and their sources.

Integration With fiXtress and apmOptimizer

CARE’s component failure data can be imported directly from fiXtress, which calculates failure rates based on actual electrical and thermal stress rather than assumed nominal conditions. This integration ensures that the system-level RAMS analysis uses the same component reliability data as the design-phase prediction, maintaining consistency across the product lifecycle.

For operational systems, CARE’s FMEA and FTA outputs feed into apmOptimizer for maintenance strategy optimization, closing the loop from design-phase reliability analysis to operational maintenance planning.

Why Buy BQR CARE From GSAS

GSAS is BQR’s authorized engineering partner in India. We provide CARE licenses with INR invoicing, deployment support, and application engineering assistance from offices in Bengaluru, Hyderabad, Chennai, Pune, Mumbai, and Delhi NCR. Our reliability engineering team helps with initial system model setup, data import from existing spreadsheet-based analyses, and standards-specific configuration.

Contact sales@gsasindia.com or call +91 80 6590 1783 for a technical consultation.