AY ENGINEERING & SERVICES · INDEPENDENT CONSULTANCY

Equipment availability is decided long before the first failure.

As a CMRP® certified reliability consultant, I help industrial companies maintain and support their assets through standards-based methods and tailored solutions.

Avionics · Rail · Electrical energy

An initial 30-minute discussion, with no obligation. Confidentiality assured.

LIFE CYCLE RISK ANTICIPATION

λ(t)
1.00.50λ / λrefEarly lifeUseful lifeWear-outNormalised time →

Normalised illustrative model · synthetic imagery · no client data

AvionicsRailElectrical energy

Services

Support that fits your needs.

I tailor my services to your needs, from a focused assignment to ongoing support, with a scope and outcomes defined together.

Audit and assessment

I analyse your installed base, support arrangements or data quality to identify gaps and define priorities.

An assessment and a prioritised action plan.

Engineering studies and analysis

I assess equipment reliability and availability, ageing-related risks, spare parts requirements and life cycle costs.

Documented assumptions and quantified results.

Technical support

I help your teams structure reference data, management rules and tools for monitoring maintenance and support.

Tools and practices suited to your organisation.
Discussion of your requirements

AREAS OF EXPERTISE

Engineering analysis and decision support.

FMD / RAM

Reliability, availability, maintainability

  • Failure mode identification.
  • Loss-of-function risk quantification.
  • Ageing-related risk assessment.
  • Equipment unavailability estimation.
  • Equipment repairability assessment.

Decision
Asset and maintenance task prioritisation.

Deliverable
Failure analysis, reliability model and maintenance plan informed by reliability-centred maintenance (RCM).

MCO

In-service support

Sustained equipment performance during operation.

Decision
Trade-offs between repair, replacement and preventive maintenance.

Deliverable
Maintenance plan, availability indicators and action plan.

SLI / ILS

Integrated logistics support

Life cycle support resource planning.

Decision
Support resource sizing and cost comparison.

Deliverable
Life cycle cost (LCC) analysis, spare parts requirements and support data.

OBS

Obsolescence management

Anticipation of support withdrawals and component shortages.

Decision
Selection of a monitoring, stockholding or replacement strategy.

Deliverable
Obsolescence management plan using IEC 62402 and repairability register.

DATA

Data quality audit and improvement

Transformation of scattered data into usable information.

Decision
Identification of data corrections for decision-making.

Deliverable
Source inventory, data flow mapping, quality audit and prioritised action plan.

LABORATORY

Engineering scenario exploration.

Three learning exercises based on simplified assumptions, for illustration rather than design sizing.

Inherent availability

99.01 %

A = MTBF / (MTBF + MTTR)

Steady state; excludes logistics delays and preventive maintenance.

OPEX / CAPEX

Cost analysis - Detailed OPEX

Break down annual operating and support expenditure, including estimated hidden costs and cumulative costs over the selected period.

Direct annual costs
Hidden and indirect annual costs

Downtime impact : €3,000/year

Inventory carrying cost : €500/yearStorage, insurance, tied-up capital and stock write-offs; exclude already counted items.

Avoid double counting: exclude parts and labour already covered by a contract. For downtime, use lost contribution margin or service value per hour, allowing for any catch-up, rather than gross revenue.

Initial values are illustrative. Enter annual amounts for the same asset or installed base throughout. Lost margin is an economic impact, not an additional accounting expense.

MTBF and survival from your Excel data

Import an installed population and its failure history to calculate observed MTBF and survival to first failure.

.xlsx format, maximum 2 MB. Up to 5,000 assets and 10,000 failures.

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Expected Excel format - click to enlarge

Parametres

Example Parametres table from the Excel template, with required headers and sample values

Actifs

Example Actifs table from the Excel template, with required headers and sample values

Pannes

Example Pannes table from the Excel template, with required headers and sample values

MTBF = cumulative operating exposure / total failures. Kaplan-Meier survival uses each asset’s first failure and right-censors assets still failure-free at the end of observation.

Weibull survival

Survival over time, using the shape parameter β and the scale parameter η.

Survival R(t)

77.88 %
Mean
886.23 h
Median
832.55 h

R(t) = exp[−(t/η)β]
Mean = η × Γ(1 + 1/β)
Median = η × (ln 2)1/β

Two-parameter model, without repair.

Weibull survival curve

Weibull survival curve0 %25 %50 %75 %100 %0460.36920.721,381.081,841.452,301.81R(t)Time (h)Mean: 886.23 hMeanMedian: 832.55 hMedianEntered time: 500 h
Survival R(t)Mean : 886.23 hMedian : 832.55 h

Curve readout : 500 h · R(t) = 77.88 %

The median corresponds to 50% survival. The mean is the model’s average lifetime and may differ from the median.

Spare parts requirements - Poisson distribution

Expected consumption of one part number and coverage stock over a specified period, using MTBF or failure rate.

Expected average consumption

10units

Based on the entered MTBF or failure rate

Theoretical coverage stock

15units

For demand over the entire period

Additional units to procure

15units

Target stock minus usable stock, with a minimum of zero

Achieved coverage : 95.126 %

Current stock coverage : 0.005 %

Average demand is an expectation, not a guaranteed quantity. Coverage stock is the smallest number of units meeting the target probability.

Model and exposure

μ = N × m × λ × T
λ = 1 / MTBF
D = q × X, X ~ Poisson(μ)

λ
1.000e-4 h⁻¹
Hours per component over the period T
1,000 h
Total exposure N × m × T
100,000 h
Expected number of failures μ
10

Coverage probability by stock quantity

0 %50 %100 %01427Stock S (units)
Coverage curveTarget stock : 15

Assumptions: independent failures, constant rate, installed population maintained through replacement, fixed consumption per failure. No replenishment or repair returns during the period.

Obsolescence application: end-of-life stock sizing over the remaining operating period under these assumptions. The Poisson model does not predict ageing or end-of-life dates.

Obsolescence analysis

Electronic component lifecycle lookup using its manufacturer part number and manufacturer.

Source: Octopart / Nexar. Status availability depends on the information provided for the component.

Checking connection…

REFERENCE FRAMEWORKS

Practice grounded in engineering frameworks.

CMRP®Certified Maintenance & Reliability Professional
  • IEC 62402
  • ISO 55000
  • IEC 60300-3
  • ISO/IEC 25012
  • IEC 62380
  • EN 50126
  • MIL-HDBK-217F
  • MIL-STD-1388
  • S3000L
  • FIDES

Frameworks, editions and applicability defined for each assignment.

Who am I?

Portrait d’Amine YAHA

Amine YAHA

I am an independent CMRP® certified consultant specialising in reliability, maintenance and support for industrial assets.

My approach combines reliability analysis, support constraints and data analysis to inform your maintenance, inventory and asset renewal decisions.

FIRST DISCUSSION

Discussion of your assets.

Your asset, main challenge and timeframe: the key inputs for an initial discussion.

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