Design for Reliability (DFR) can be described as a systematic, streamlined, concurrent engineering programme that supports product and process design (typically from early in the concept stage all the way through to product obsolescence) to ensure that customer expectations for reliability are fully met throughout the life of the product with low overall life-cycle costs. It relies on an array of reliability engineering tools along with a proper understanding of when and how to use these tools throughout the design cycle.
The DFR process encompasses a variety of techniques and practices, describing the overall order of deployment that an organisation needs to follow in order to design reliability into its products. This process is supported by the ReliaSoft DFR Suites, comprising tools that integrate with the ReliaSoft Synthesis Desktop Platform for storing and transferring data between applications through a centralised database.
Failure Mode, Effects (& Criticality) Analysis (FMEA/FMECA)
Failure Mode and Effects Analysis (FMEA) and Failure Modes, Effects and Criticality Analysis (FMECA) are methodologies designed to identify potential failure modes for your product or process, to assess the risk associated with those failure modes, to rank the issues in terms of importance and to identify and carry out corrective actions to address your most serious concerns.
Although the purpose, terminology and other details can vary according to type (e.g. ProcessFMEA – PFMEA, Design FMEA – DFMEA, System FMEA, Product FMEA and FMECA), the basic methodology is similar for all. The fundamental steps, from assembling the team and gathering relevant information, to evaluating the risk from issues identified and distributing the information, can be facilitated by our comprehensive FMEA / FMECA training and consulting services and ReliaSoft’s comprehensive Xfmea software.
Life Data Analysis (Weibull)
In life data analysis (also called “Weibull analysis”), you can make predictions about product life within the population by “fitting” a statistical distribution to life data from a representative sample. This distribution can then be used to estimate important life characteristics of your product such as reliability or probability of failure at a specific time, the mean life for the product and failure rate. ReliaSoft Weibull++ software is extremely popular for a wide range of statistical analysis.
Accelerated Life Testing
In typical life data analysis, you may record product performance in tests when operating under normal conditions to quantify life characteristics and make predictions about all of the products in the population. However, if these tests would take too long for your development lead time, you can use quantitative accelerated life testing techniques to capture life data under accelerated stress conditions, which cause the products to fail more quickly.
ReliaSoft’s ALTA software solution and our accelerated life testing training and consulting services can assist with your accelerated testing programme and subsequent life data analysis. These tests can be either physical or virtual (simulation) based.
System Reliability and Maintainability Analysis
With Systems Reliability techniques, you can construct a global model from individual ‘black-box’ life distribution models to predict times-to-failure of the entire system. This information can be used to identify critical components, bottlenecks and redundancy within any system – enabling the planning of maintenance schedules and improving overall reliability performance.
In life data analysis, the objective is to obtain a distribution that describes the times-to-failure of a component, subassembly, assembly or system. This analysis is based on the time of successful operation or time-to-failure data of the item, either under in-use conditions or from accelerated life tests.
With the leading ReliaSoft BlockSim software, we can assist with the construction of models (life distributions) from lower level life data analysis through our dedicated systems reliability training courses and consulting services.
Design of Experiments (DOE)
When variation is anticipated or to be identified during testing, good experimental design is fundamental. A range of methodologies are available to help you assess the relationship between different parameters influencing a product or process and their effect on performance. By the careful selection of variables and the experiments that are consequently performed, your designs can be investigated and optimised effectively.
For both physical (prototype / shop trial) and virtual (simulation) testing, Wilde offers dedicated software to assist the selection of variables and analysis of results. ReliaSoft DOE++ software can be applied to a wide range of physical and virtual testing techniques, while there are integrated DOE modules for ANSYS simulation products. For both solutions, we can provide comprehensive training and consulting services.
Reliability Growth & Repairable System Analysis
A well-structured reliability growth programme helps you find reliability problems by testing, incorporating corrective actions and monitoring the increase of the product’s reliability throughout the test phases. Reliability growth analysis is the process of collecting, modeling, analysing and interpreting data from this programme, whether sourced from development testing and/or collected from the field.
Reliability growth is the improvement in the reliability of a product (component, subsystem or system) over a period of time due to changes in the design and/or manufacturing process. We provides ReliaSoft RGA software, training and consulting services to apply reliability growth models and conduct the analysis.