Reliability & Data Analysis

Astrimar is able to support challenging design and operations, using effective risk and reliability management to help mitigate the inherent technical risks and manage uncertainty. The analysis of qualification, integrity and failure data is also key to assessing reliability performance and improve estimates of equipment failure probability.

We strongly believe that risk and reliability analysis should be used as an integral part of the design process or asset management to support the development of solutions to improve reliability and functionality.

Data analysis is essential to support reliability analyses and management of risk. Since the collection and availability of good reliability performance data is so crucial, Astrimar has been involved in developing strategic industry databases. 

Astrimar uses traditional techniques such as Chi-squared and Weibull analysis to estimate equipment failure rate over time and predict future failure probability.  Astrimar also develops bespoke analysis models to make best use of data available, combined with knowledge of degradation processes, to generate the best-informed estimates of reliability over time.

There is a vast range of risk and reliability tools and techniques that can be applied to support the engineering design process and operations decision making.  We use our experience and expert knowledge of the tools and techniques to identify which tool is best for each individual problem.

In addition to the standard reliability data analysis methods mentioned above, we can also provide risk and reliability-based analyses such as:

  • Common Cause Failure Analysis (CCFA) - to identify and assess components at risk of (near) simultaneous failure from a common event
  • Event Tree Analysis (ETA) - to describe how failure events propagate through a system and determine likely consequences
  • Failure Modes, Effects (and Criticality) Analysis (FMEA/FMECA) - to identify system, design or process failure modes for assessing and managing the risk.
  • Fault Tree Analysis (FTA) - to identify the technical cause of specific unwanted events and predict reliability performance.
  • Predictive Maintenance Analysis - to make best use of condition data to support risk-based predictive maintenance and asset management strategies. 
  • Reliability, Availability and Maintainability Analysis (RAM) - to quantify a system’s ability to remain in an operational state.
  • Reliability Centred Maintenance (RCM) - to optimise maintenance based on potential failure mode criticality, supported by data to mitigate risk.
  • Reliability Value Analysis (RVA) - to understand cost and consequences of failure and identify the value of improvement opportunities.
  • Risk Based Decision Making (RBDM) - to support complex project and engineering decisions at each stage, accounting for uncertainty
  • Root Cause Failure Analysis (RCFA) - to resolve problems affecting reliability by assessing facts relating to a failure or event at root cause.
  • Structural Reliability Analysis (SRA) - to predict design reliability when physical prototypes and qualification tests are impossible.
  • Technology Readiness Assessment (TRL) - to assess current level of readiness of technology for project use, based on qualification maturity
  • Technical Risk Assessment and Categorisation (TRC) - to assess what is new or changed from previous projects, that introduces uncertainty or risk to reliability.

Astrimar provide a service to tailor a FMEA / FMECA to meet your requirements, so that the FMEA / FMECA process can help you understand your current risks and plan value enhancing actions to mitigate or manage those risks.  Purchase our FMEA / FMECA preparation service through: