Reliability Strategy

Philips Healthcare, CT/NM BU

ReliabilityReliability StrategyStrategyService Impact on Reliability

… … Getting Reliability to the “Next Level” Getting Reliability to the “Next Level”

Shlomo Eisenbach

CONFIDENTIAL Strategies for Reliability, Shlomo Eisenbach, February 2012 2

CT ReliabilityCT Reliability

• Philips Healthcare, Imaging Systems

• Reliability Values

• Reliability Strategies Service Strategy impact on Reliability

• Philips Healthcare, Imaging Systems

• Reliability Values

• Reliability Strategies Service Strategy impact on Reliability

CONFIDENTIAL Strategies for Reliability, Shlomo Eisenbach, February 2012

Depth and reach of Philips HealthcareWhat we do. Where we are.


What is a CT System?What is a CT System?

An X-Ray tube rotating around the patient and irradiating the patient

X-Ray Detectors reading the amount of X-ray absorbed by the patient. Computers will process this data.

• Rotation speed: 300 RPM• Rotor ~1250 Kg (more than 40 g in fast

rotation)• Tube consuming 120 kW• Ultra fast frame rates: 10,000 samples per

second• 100,000 detectors in a system• Temperature stabilization: +/- .25 degrees• Electronic noise: 1-2 pA• Mechanical tolerance should be below : 20

microns• Reconstruction speed: 40 images per second• Reliability / uptime• Number of images per scan: more then 2000


What is the result of CT?What is the result of CT?“Slices” of the human body


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Why Reliability is Mission Critical in Healthcare Imaging

Systems?


2240


Reliability ValuesReliability Values

Business Value

• Reduce warranty cost• Reduce remediation investment• Service business profitability• Increase Repeating sales• Improve Brand reliability reputation• Increase Market share

Customer Value

• Maximize product availability • Improve reliability perception• Minimal impact of Customer

Life Cycle Cost


Customer Reliability Perception Customer Reliability Perception

Perception based on:


Reliability StrategiesReliability StrategiesChange the Rules for sustainable impact

• Identify Customer/s

• Close the Loop (Gates and feedback)

• Service Policies Impact on Reliability

• Practical Approaches

• Identify Customer/s

• Close the Loop (Gates and feedback)

• Service Policies Impact on Reliability

• Practical Approaches


Identify Customers and Identify Customers and stakeholdersstakeholders

Customer Satisfaction Reduce Unplanned Down time

Customer Satisfaction Reduce Unplanned Down time

Call Rate reduction Call Rate reduction

Cost saving Reduce Total Repair Time Planed FRU usage

Cost saving Reduce Total Repair Time Planed FRU usage

BU Customer Support

Global Sales & Service


Gates & Feedback CyclesGates & Feedback Cycles

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Design Integration Verification ValidationSpec

Process Design Assembly Final Test

Installation Service Event

Suppliers

?

Strategy should start with Gates (customers impact) and short fix cyclesStrategy should start with Gates (customers impact) and short fix cycles

Call Rate Tracking & Analysis

Failure Rate Tracking & Gating


NAEMEA

APAC

0

5

10

15

20

25

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V1.1 - Failure Rate per Site

EMEAAPAC NA

Customer Focus GatesCustomer Focus Gates

Last release (v1.2) measured to be less reliable than previous Customer informal feedback reliability was improved relative to previous version..


Metrics - Close Loop with Customer Metrics - Close Loop with Customer PerceptionPerception

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Service Policies Impact on ReliabilityService Policies Impact on Reliability

• Basic Service Strategies

• 2 ways Prediction

• Service Policies and Impact on Reliability

• Preventive Maintenance

• Specific example

• Basic Service Strategies

• 2 ways Prediction

• Service Policies and Impact on Reliability

• Preventive Maintenance

• Specific example


Basic Service Strategy Basic Service Strategy


Service PoliciesService Policies


Reliability Prediction Based on field DataReliability Prediction Based on field DataAvoid long and costly ALTsAvoid long and costly ALTs

POWER BRUSH BLOCKBeta = 0.95Eta = 2650h • Predicting Reliability out of Failure Rate is a challenge.

• Need full statistical data e.g. - FRU (Field Replaceable Unit) failure age and suspended age)


Reliability Prediction Forward Reliability Prediction Forward From Internal Lab Tests to System Failure Rate Prediction

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0 1.5 3 4.5 6 7.5 9 10.5 12 13.5 15 16.5 18 19.5 21 22.5 24

Repl

acem

ent r

ate

(# u

nits

repl

aced

per

year

)

Time (Years)

FRU Replacement Rate in a System(Replacements per System per Year)

Reliability distribution - Weibull: Beta (shape) = 1.5, Eta (Life) = 10 years

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0.005

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0 5 10 15 20 25Time (Years)

Failure Density f(t), (beta =5, eta =10)

* FRU = Field replaceable Unit (usually non repairable)

* Reliability [R] = Survival of Non Repairable items

* Call Rate [CR] = Known Customer Issues

* FRU = Field replaceable Unit (usually non repairable)

* Reliability [R] = Survival of Non Repairable items

* Call Rate [CR] = Known Customer Issues

0

0.02

0.04

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0 1.5 3 4.5 6 7.5 9 10.5 12 13.5 15 16.5 18 19.5 21 22.5 24

Repl

acem

ent r

ate

(# u

nits

repl

aced

per

year

)

Time (Years)

FRU Replacement Rate in a System(Replacements per System per Year)

Reliability distribution - Weibull: Beta (shape) = 5, Eta (Life) = 10 years

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0.01

0.02

0.03

0.04

0.05

0.06

0 5 10 15 20 25Time (Years)

Failure Density f(t), (beta =5, eta =10)

Install Base Traditional Call Rate measurement is per Calendar.

It blends the different ages and tend to be stable with seasonal fluctuations.

Replacement Rate by age is the relevant metric for reliability view.

Can be predicted out of early reliability measurements.

The Renewal Density function is the theory behind Call Rate by Age

Shlomo Eisenbach

Philips Healthcare

Proactive Replacement

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Service Policy impact Reliability

ExampleService Policy impact Reliability

Example


Project: Proactive HW ReplacementProject: Proactive HW Replacement

Prevent unplanned Corrective Maintenance visits and improve Uptime

Customer SatisfactionReduce Scanner Down timeCall Rate reduction

(> X Call/sys/year)Cost saving

(> X M€/ year)Reduce Total Repair TimePlaned FRU usage

Goal: No unplanned HW parts replacement

“50,000 miles”checkups & treatment

Reactive: Replace by failure Proactive: Replace by “Mileage”


Example: BR64 FansReplacing failed fan: As it happened

Feb-05 Jan-10

Jan-06 Jan-07 Jan-08 Jan-09

533535

Apr-092 Fans

Jan-072 Fans

Jul-072 Fans

23 month 6 month 21 month

6 Fans were replaced at 3 CM visits

3 X Down time events3 X Customer Calls26 CM HoursTotal cost = 2,700€

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Corrective Maintenance

Planed Preventive Maintenance

Feb-05

Replacements after failure (CM)


Feb-05 Jan-10

Jan-06 Jan-07 Jan-08 Jan-09

533535

6 month

Aug-092 Fans

Feb-082 Fans

Aug-062 Fans

Feb-071 Fan

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7 Fans would be replaced ,at 3 PM visits and 1 CM event

1 X Down time events (Vs. 3)

1 X Customer Calls (Vs. 3)

6 CM Hrs + 3 PM Hrs (vs. 26)

Total cost = 1,400€ (Vs. 2,700€)

Example: BR64 Fans: Applying Proactive replacement @ age of 1.5 years

Corrective Maintenance

Planed Preventive Maintenance

3 Proactive replacements (in 5 years = every 18 month)

Replace after failure (CM)

Feb-05


Selecting age to Replace FRU

The following graph show call rate saving and € saving versus FRU age if replaced by age.

• Replacing too late will give the same results as with no aged replacement

• Replacing too soon will cost a lot due too excessive replacement

• PM policy of 18 month will:

a. Reduce calls from 0.54 to 0.22 call/sys/year.

b. Reduce system cost from 540€ to 371€

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Preventive Maintenance PolicyPreventive Maintenance Policy

Vision:

Any CT product will have less than 6 Unplanned Corrective Maintenance events within 5 years after release

Replacementby calendar age

Proactive Replacement (Aged FRUs)

Replacementby usage

Maintenanceby calendar age

Preventive Maintenance(Inspection & Cleaning)

Maintenanceby usage

Age

Usage

Maintenance. Timing by:

Current Project

Current policy

Future Plans

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2Future Plans

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Reliability Strategy

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