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MADE FOR RELIABILITY

Use reliability analysis to inform design and service decisions.

MADE provides a model-based RAMS environment for evaluating reliability and availability across the product lifecycle, helping engineering teams create traceable reliability targets, compare design configurations and identify poor performing items before they become operational risk.

MADE reliability analysis over the product lifecycle
Reliability AllocationSet apportioned targets from system goals.
RBD AnalysisModel reliability and availability behaviour.
FTA ValidationReview calculations through fault logic.
Poor Performer InsightIdentify items that miss reliability targets.
THE CHALLENGE

Reliability is too important to manage as a milestone document.

Reliability is a key determinant in total cost of ownership. Yet reliability analysis is often performed as a static milestone activity rather than a controlled, consistent and traceable process aligned to the current design configuration.

MODEL-BASED RELIABILITY

Move from disconnected analysis to lifecycle traceability.

MADE RAM combines Reliability Allocation, Reliability Block Diagram modelling, Reliability / Availability Analysis and Fault Tree Analysis so engineers can generate design and service recommendations from a single system model.

Model

Capture the physical and functional structure of the system.

Allocate

Develop reliability targets using top-down reliability allocation.

Compare

Compare operational reliability data against design targets.

Improve

Identify poor performers and refine the design or maintenance strategy.

KEY BENEFITS

Make reliability performance visible across the lifecycle.

MADE provides a controlled framework for evaluating reliability and availability across product design, analysis, maintenance planning and service support.

Evaluate reliability and availability

Assess system reliability and availability across the product lifecycle using repeatable model-based analysis.

Support maintenance scheduling and costing

Use reliability calculations to inform maintenance planning, downtime reduction and lifecycle cost decisions.

Set apportioned targets

Allocate reliability targets based on system-level reliability goals and compare performance against those targets.

Find poor performing items

Identify components, functions or assemblies that do not meet reliability expectations and prioritise redesign effort.

RECOMMENDED RESOURCE

Download the MADE for Reliability brochure.

See how MADE supports Reliability Allocation, Reliability Block Diagram modelling, Fault Tree Analysis, reliability / availability analysis, poor performer identification and maintenance planning.

Download Reliability Brochure
LIFECYCLE RELIABILITY ANALYSIS

How MADE supports reliability analysis over the product lifecycle.

The following lifecycle workflow reflects the brochure section and allows key imagery to be included as individual visual panels.

Capture the reliability structure

Construct a Reliability Block Diagram linked to the physical and functional structure of the system.

Hierarchical system structure to functional model and reliability block diagram
Compare targets and performance

Generate reliability targets and compare them with operational performance using time-to-failure data.

Reliability target development and operational reliability comparison
Identify poor performers

Gain insight into reliability performance and identify items that need redesign or improvement.

RBD analysis and identification of poor performing items
Review RBD calculations using FTA

Verify the probability of failure from RBD analysis using hardware-based Fault Tree Analysis.

Fault Tree Analysis verification of Reliability Block Diagram calculations
Derive a maintenance plan

Use reliability calculations in a Classic Reliability-Centered Maintenance process to support trade studies on downtime and maintenance cost.

Classic reliability-centered maintenance plan derived from reliability calculations
Calculate lifecycle cost

Compare maintenance plans and costs against design-stage estimates to refine the maintenance approach.

Maintenance cost estimates over the system lifecycle
RELIABILITY OUTPUTS

Generate the outputs reliability teams need to influence design.

MADE helps teams produce reliability evidence that can be reviewed, compared, updated and reused throughout the product lifecycle.

Reliability allocation

Allocated reliability targets to advise design and acquisition decisions.

RBD analysis

Current reliability data analysed through RBDs and compared against targets.

Poor performer lists

Identification of key degraders based on targets and system-level reliability impact.

Fault Tree Analysis

Functional and hardware-based FTA to support verification and deeper reliability review.

Maintenance planning

Reliability calculations that support Classic RCM, Backfit RCM and maintenance action planning.

Cost estimates

Maintenance cost estimates that help quantify the lifecycle impact of design and service decisions.

WHY MADE FOR RELIABILITY?

Reliability analysis connected to the system model.

MADE is a model-based integrated toolset that generates reliability analyses from the system model, helping teams keep track of design reliability in real time and in context.

Optimise availability and reliability

Use reliability analysis to improve system availability and reliability across the expected operational life.

  • Analyse how failures propagate through the system.
  • Review the reliability impact of design alternatives.
  • Support design downtime reduction and reliability optimisation.

Create a managed reliability framework

Manage reliability data across the product lifecycle rather than relying on static documents or disconnected spreadsheets.

  • Capture reliability and availability data in the MADE modelling framework.
  • Maintain traceability from analysis outputs to system configuration.
  • Automatically generate key design reliability outputs.

Build reliability confidence into every design decision.

MADE helps engineering teams connect reliability targets, system structure, failure behaviour, maintenance planning and lifecycle cost into one model-based decision support environment.

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