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Introducing Relyence 2018 Release 3!

Home » Introducing Relyence 2018 Release 3!
New Release writing in sky

Introducing Relyence 2018 Release 3!

June 14, 2018 217Plus, FMEA, FRACAS, MTBF, News, Reliability, Reliability Prediction

We’re starting off the summer with a hot new release of our Relyence reliability software tool suite! We’ve been hard at work adding features to further advance our commitment to being the best-in-class solution for your reliability analysis needs.

Relyence 2018 Release 3 offers a number of new capabilities for our Reliability Prediction and FMEA (Failure Mode and Effects Analysis) modules. And, as always, we continue to enhance all our products with feature requests from our customers across the globe.

If you are not yet a Relyence customer, you can try out all of our products for free for 14 days – no strings attached! If you are presently a Relyence customer and would like to check out new features and/or modules you have not purchased, simply create a “demo” Analysis for access to all of Relyence’s features and functions.

217Plus Reliability Prediction Standard

Relyence Reliability Prediction supports the most widely accepted global standards for MTBF analysis, including MIL-HDBK-217, Telcordia, and China’s GJB/z 299. Relyence 2018 Release 3 adds on support for the 217Plustm prediction standard.

The 217Plus reliability prediction standard was developed by Quanterion Solutions, Inc. Initially started under Department of Defense contracts with the Reliability Analysis Center (RAC) and Reliability Information Analysis Center (RIAC), 217Plus was originally released under the name PRISM.

The failure rate models of 217Plus have their roots in MIL-HDBK-217, but have enhancements for including the affects of operating profiles, cycling factors, and process grades on reliability.

The official 217Plus standard name is Handbook of 217Plus Reliability Prediction Models. An example equation for capacitors in 217Plus is:

λP =πG* πC * (λOB * πDCO * πTO * πS +λEB * πDCN * πTE +λTCB * πCR * πDT )+λSJB * πSJDT +λIND

where λp is the failure rate in failures per million calendar hours.

For the equation above, the following list describes the variables:

  • πG is the reliability growth factor
  • πC is the capacitance factor
  • λOB is the operating base device failure rate
  • πDCO is the operating duty cycle factor
  • πTO is the operating temperature factor
  • πS is the stress factor
  • λEB is the environmental base failure rate
  • πDCN is the non-operating duty cycle factor
  • πTE is the non-operating environment temperature factor
  • λTCB is the cycling temperature base failure rate
  • πCR is the cycling rate factor
  • πDT is the delta temperature factor
  • λSJB is the solder joint base failure rate
  • πSJDT is the solder joint delta temperature factor
  • λIND is the induced failure rate

The equations, variables, and data parameters vary based on the specific device being modeled. As noticeable from the above equation, 217Plus takes into account a wide variety of factors that influence device reliability. As with our other prediction standards, Relyence does not require you to know all the data parameters to compute failure rate and MTBF. Relyence will use a built-in set of default values for unknown parameters. Or, you can set your own defaults if you prefer. As you gather more device data, you can go back and update your analysis to continually refine your reliability prediction.

Once the device failure rates are evaluated, they are summed up to determine a base system failure rate. At this point, further analysis can be done at the system level if more data is available, such as test or field data. By factoring in this information, the 217Plus analysis will provide a more accurate predicted failure rate estimation. At the system level, 217Plus can incorporate environmental stresses, operating profile factors, and process grades. Once again, if this data is not known, default values are used.

As with MIL-HDBK-217, there is a Part Count section of 217Plus intended to be used in early design when all data parameters are not yet finalized. The Part Count method offers a simpler approach to prediction calculations. The Part Count section of 217Plus includes a number of tables for device failure rates that are based on the combination of environment and operating profile of the system. In this case, a table lookup will provide the failure rates for your devices without the need for equations.

Relyence Reliability Prediction fully supports the 217Plus prediction standard, including Part Count analysis. Additionally, Relyence Reliability Prediction allows you to use different prediction standards within one Analysis. Because prediction standards vary in the devices modeled, the environments supported, as well as various other features, this is an important benefit. By supporting the cross model approach, Relyence allows you to take advantage of the unique features of all the prediction methodologies. Ultimately, this enables you to model your system most efficiently and accurately.

Piece-Part FMECA

FMEAs come in a broad range of formats. Therefore, Relyence FMEA is built on an adaptable framework to meet the varying needs of all FMEA analysts. Relyence FMEA provides templates for a number of well-known FMEA standards, such as SAE J1739, ARP5580, AIAG, and MIL-STD-1629A. You can use these templates as is, or customize them to your needs. Or, you can easily create a completely custom format for your unique requirements. Relyence FMEA software allows you to perform any type of analysis you choose: Design FMEAs, Process FMEAs (including Process Flow Diagrams and Control Plans), FMECAs, as well as completely custom FMEAs.

FMECA, or Failure Mode, Effects, and Criticality Analysis, extends failure mode analysis by adding in the “criticality” component. The core function of a FMEA as a bottom-up, analytical approach for risk assessment remains the same; however FMECAs include additional data and calculations for quantitative criticality analysis. FMECAs can be performed at a functional level or at a piece-part level.

When performed at the piece-part level, FMECAs breakdown a system into component subassemblies, and then down to the device level. At the device level, you then consider each possible failure mode and its resulting effects on its parent component, and then ultimately on the system. Piece-part FMECAs are highly detailed, very organized, and exceptionally comprehensive.

In Relyence FMEA 2018 Release 3, we’ve introduced a powerful new way to complete your piece-part FMECAs. Your Analysis Tree displays a complete system breakdown, including all parts. Each part’s FMECA Worksheet can be systematically completed for a fully detailed piece-part analysis. In conjunction with Relyence FMEA’s powerful Knowledge Banktm capability, your piece-part FMECAs are more consistent and automated than ever before.

Using Relyence FMEA in conjunction with Relyence Reliability Prediction provides a powerful combination pack for complete piece-part FMECAs. You can define your system down to the part level using the streamlined Relyence Reliability Prediction interface, and that same breakdown is automatically transferred to Relyence FMECA. Additionally, all your calculated part failure rates are automatically available in your Relyence piece-part FMECA. Then, those failure rates values are used as a basis for computing criticality metrics including probability of occurrence rates, and mode and item level criticality values. The combination of Relyence Reliability Prediction and Relyence piece-part FMECA provides a quantitative, metrics-based approach to risk assessment.

You can also use Relyence FMEA as a stand-alone tool to perform your piece-part FMECAs. The system breakdown remains the same, and you can choose how to perform your criticality analysis – using a qualitative approach, or in a quantitative manner – the choice is yours. Either way, with Relyence 2018 Release 3, piece-part FMECA analysis have never been easier!

FMD-2016

The “Failure Mode/Mechanism Distributions – 2016” (FMD-2016) is a publication from Quanterion Solutions, Inc. that contains field failure mode and mechanism distribution data on a variety of electrical, mechanical, and electromechanical parts and assemblies. Often, this data is used to assist in performing FMECAs, especially piece-part level FMECAs. FMD-2016 includes hundreds of thousands of records of field-based data on the failure modes of components and their distributions.

FMD-2016 data provides a baseline set of failure modes and probabilities that are available in Relyence FMEA. As you are completing your piece-part FMECA in Relyence, you can access the FMD-2016 library directly. Bring up the Search window and filter through the database of components to locate a match. Relyence then automatically retrieves the associated failure modes and distribution percentages. This information is automatically populated into your FMECA Worksheet. You can use the data as is, or modify as needed to match your particular situation.

The extensive FMD-2016 library provides an efficient way for you to start your piece-part FMECA. You can then concentrate on the main objective of your FMECA: considering how underlying failure modes affect your system, and then how to eliminate or mitigate those that are most critical.

FRACAS Summation Calculation

One of the unique features of Relyence FRACAS (Failure Reporting, Analysis, and Corrective Action System) is the ability to perform calculations based on field data. While the core capability of any FRACAS is to track and manage issues, Relyence FRACAS takes process control to a new level with the ability to perform metrics-based analysis of your incident data.

Relyence FRACAS can compute:

  • Failure Rate
  • MTBF
  • MTTR
  • MTTF
  • Repair Time
  • Trend Score

Trend score is a unique Relyence metric that indicates if your system is improving or degrading. A trend score of zero indicates your incident reports are constant over time, a negative trend score indicates your system is experiencing a decreasing incident report trend (improving), and a positive trend score indicates the your system is experiencing an increasing incident report trend (degrading). In Relyence, trend scores are color-coded for easier analysis: green is an improving trend; red is a degrading trend. This is an important indicator you can use for a proactive approach to issue management. Spot a degrading trend? Intervene early on with a corrective action plan before issues reach a critical level.

With Relyence 2018 Release 3, you can also generate a summation total of any FRACAS-based data you prefer. For example, you may want to sum up the repair costs of all your reported issues. Any numeric data that you log with your failure reports can be summed up to provide an overall total.

Remember to use the powerful and popular Relyence Dashboard to keep track of your systems! You can add this FRACAS Total to your Relyence FRACAS Dashboard Calculation Result widget so you can monitor and keep track of your most critical metrics.

Free Trial

Relyence offers a free fully functional trial of Relyence 2018 Release 3. You can register today for a free trial. Feel free to contact us, or call today at 724-832-1900 to speak to us directly about your requirements or to schedule a free webinar.

Tags: 217Plusfmdfmd-2016fmeaFMECApiece-part FMEApiece-part FMECA
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