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TRANSCRIPT
System Reliability and Challenges
in Electronics Industry
SMTA Chapter Meeting 25th September 2013, India
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Contents
1. System Reliability
2. Importance of Study of System Reliability
3. System Reliability Models
4. Designing System Reliability
5. Electronics Industry Challenges
6. Proposed overcomes
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1. System Reliability
2. Importance of Study of System Reliability
3. System Reliability Models
4. Designing System Reliability
5. Electronics Industry Challenges
6. Proposed overcomes
3
System Reliability
System reliability- what is it?
It is the reliability of an entire system, as opposed to the reliability of its
components.
The system reliability is defined by the reliability of the components as well as the
way the components are arranged reliability-wise.
System may have its components arranged in either Series, Redundant or in Mixed
connection/interlinking.
Some systems can have Redundant systems intentionally added to improve overall
System uptime- i.e. Systems have higher Reliability regardless of its component
failures.
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1. System Reliability
2. Importance of Study of System Reliability
3. System Reliability Models
4. Designing System Reliability
5. Electronics Industry Challenges
6. Proposed overcomes
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Importance of Study of System Reliability
- Systems becoming more complex with more multitasking
- To catch up market attention against your Competitor’s product.
- Cost of Design with high reliable components is very high
- Customer satisfaction and Brand Value are very important.
- Customer always wants LARGER uptime, LOW time to repair and LEAST cost of
repair
- Product and Human Safety Requirements in critical applications
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1. System Reliability
2. Importance of Study of System Reliability
3. System Reliability Models
4. Designing System Reliability
5. Electronics Industry Challenges
6. Proposed overcomes
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System Reliability Models
System reliability models are utilized to describe VISUALLY and MATHEMATICALLY the relationship between
system components and their effect on the resulting system reliability.
A reliability block diagram or structural model provides the visual representation while the mathematical or
“math” model provides the analytical tool to calculate quantitative reliability values.
A. Series Model:
When a group of components or Independent subsystems is such that all must function properly for the
system to succeed, they are said to be in series.
Rs= R1 * R2 * … Rn
CASE: A Communication System consist of the 05 Electronics Ckts each of which must be operational for
system to operate. The subsystem Reliabilities as 0.9, 0.95, 0.99, 0.99 and 0.9.
System Reliability= Rs =?
Rs= 0.9 x 0.95 x 0.99 x 0.99 x 0.9 = 0.75
Note that System Reliability is lower than that of the worst subsystem. This is generally the case of Series
structured System.
1 2 n
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System Reliability Models
B. Redundant Model:
- Mission Reliability of the system containing independent Systems can be improved by using subsystems in the
redundant fashion.
For Example , adding Second Amplifier Circuit on the board parallel to the primary amplifier circuit. Or
addition of second metal detector sensor in the process of food packaging Industry.
Redundant System Mathematical Model:-
System Unreliability= Qs = Q1 * Q2 *……Qn
System Reliability = Rs= (1- Qs)
Below Parameters to be considered when designing the redundant Systems:-
1. Cost of Product
2. Space Required and Weight of the board
3. Testing and Evaluation
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2
n
Active or Standby
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System Reliability Models
C. Mixed Models:
One system configuration that is often encountered is one in which subsystems are in series, but redundancy
(active) is applied to a certain critical subsystem (s). A typical block diagram follows:
This kind of MIXED models are characterized by
Working from Low to high levels of assembly.
R3,4,5 = 1- [(1-R3) (1-R4) (1-R5)]
System Reliability = Rs = R1 x R2 x R3,4,5
3
4
5
1 2
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System Reliability Models
D. K-out-of-N Model:
A system consisting of n components or subsystems, of which only k need to be functioning for system
success, is called a k-out-of-n configuration.
For such a system, k is less than n.
Mathematical Model:
(same as a binomial expansion of (R+Q)^n), R= Reliability, Q= Unreliability
Case: A system consist of 04 sensor circuits which are Identical, operating simultaneously, and failures are
statistically independent. Hence the mathematical Model for this system:-
(R + Q)4 = R4 + 4R3 Q + 6R2 Q2 + 4RQ3 + Q4 = 1 out of which:-
R4 = P(all four will survive)
4R3 Q = P(exactly 3 will survive)
6R2 Q2 = P(exactly 2 will survive)
4RQ3 = P(exactly 1 will survive)
Q4 = P(all will fail)
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System Reliability Models
D. K-out-of-N Model:
We are usually interested in k out of n surviving.
R4 + 4R3 Q = 1 - 6R2 Q2 - 4RQ3 - Q4 = P(at least 3 survive)
R4 + 4R3 Q + 6R2 Q2 = 1 - 4RQ3 - Q4 = P(at least 2 survive)
R4 + 4R3 Q + 6R2 Q2 + 4RQ3 = 1 - Q4 = P(at least 1 survives)
For the system which have subsystems of different reliabilities:-
Consider that we have 03 systems which reliability values of R1, R2 and R3.
Then Rs= (R1+Q1) (R2+Q2) (R3+Q3). Boolian Truth Table is used
Thuss probability of serviving at least two sensor will survive
P(at least 2 sensor surviving) = R1 R2 R3 + R1 R2 Q3 + R1 Q2 R3 + Q1 R2 R3
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Redundancy Allocation Optimization:
Redundant Elements in the Systems can be ‘active’ or ‘standby’.
Selection of the Redundant Elements may be automatic using Switches in ‘standby’ case.
Increasing number of Redundant Elements increases the number of Switching Circuits.
These Switching/ decision devices may fail to switch when required or may operate
inadvertently.
If Such Circuits have high Reliability, then redundancy is most effective.
If these devices are not failure free, then Increasing System Reliability using Redundancy have
to be chosen to Optimized Level.
Since cost, weight, and complexity factors are always involved, the minimum amount of
redundancy that will produce the desired reliability should be used.
Thus efforts should be concentrated on those parts of the system which are the major causes
of system unreliability.
Example below shows how to allocate the redundancy based on System Reliability value.
System Reliability Models
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Redundancy Allocation Optimization:
System Reliability Models
Case and assigned REL values Graphical Model System Reliability
Two circuits A & B have REL values as
0.95 and 0.50 respectively.
SERIES Combination
R1= 0.95 x 0.50
= 0.475
If we duplicate both circuit A and B
Keeping same REL values.
A and B each have one redundant
system
R2= (1-0.50^2) (1-0.05^2)
= 0.748
If we duplicate only Circuit B.
A is in series with redundant
combination of circuit B
R3= 0.95 x (1-0.50^2)
= 0.712
A 0.95
B 0.50
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Redundancy Allocation Optimization:
Conclusions:
- R4 gives a 75% increase in original circuit reliability as compared to the 58% increase of R2
- If complexity is the limiting factor, duplicating SYSTEMS is generally preferred to duplicating ELEMENTS as
shown for R5
System Reliability Models
Case and assigned REL values Graphical Model System Reliability
Triplicate Circuit B with REL value
0.50 and keeping A in series with
redundant combination
R4= 0.95 x (1-0.50^3)
= 0.831
Making a full system Redundant- i.e.
adding a series combination in parallel
with another series combination of A
and B circuits
R5= 1- (1-0.475)^2
= 0.724
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1. System Reliability
2. Importance of Study of System Reliability
3. System Reliability Models
4. Designing System Reliability
5. Electronics Industry Challenges
6. Proposed overcomes
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Designing System Reliability
Objectives of System Reliability Design: It has two objectives as below
1. System Effectiveness: (Mission Reliability): To Measure and enhance System effectiveness
2. Logistic Reliability (Maintenance Reliability + Supply Chain Reliability)
System Effectiveness:
- ‘Worth’ of particular system or equipment- ‘operational effectiveness’
- It is measured when the system is performing its mission in the actual environment for which
it was designed.
- Important is to consider the system effectiveness while design phase, test and evaluation.
- System Effectiveness is measured in terms of three basic parameters- Availability,
Dependability and Capability (ADC)
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Designing System Reliability
System Effectiveness Assessment fundamentally Answers three basic questions:
1. Is the system working at the start of Mission?
2. If the system is working at the start of the mission, will it continue to work during the mission?
3. If the system worked throughout the mission, will it achieve mission success?
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1. System Reliability
2. Importance of Study of System Reliability
3. System Reliability Models
4. Designing System Reliability
5. Electronics Industry Challenges
6. Proposed overcomes
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Major Challenges in System reliability
1. Cost of Overall System Qualification
2. Impact on schedule of Projects
3. No Historical Data available
4. System Qualification with Actual User Conditions
5. Demonstration of System Reliability, Time & Cost for the same
6. Restrictions on the cost of maintenance, parts replacement/repair
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Overcomes
Challenges:
1. Cost of Overall System Qualification
Proposed Overcomes:-
1. Defining Set of Tests as per Product Specs-
Eliminate the Test which are not applicable for the product- Revisit the Product Specs
Some non-operational tests may not be needed on system level to be carried out.
2. Revisit the % Operational Margins of the product.
For Example:- A product operating temp is 40°C. However we may consider margin of 10% as a
company defined procedure. Actual user conditions may not be reaching 3% of operating
Temperature. Hence Product Operating conditions should be revisited.
3. Identify Critical Systems in the products which are prone to failure and have lower %REL
4. COTS module specs and supplier qualification to be considered for the product qualification.
Example: MTBF data, Supplier Test Results, Simulation conditions, Sample Size etc.
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Overcomes
Challenge:
2. Impact on schedule of Projects
Proposed Overcomes:-
1. Perform Accelerated Testing wherever possible to reduce test times.
1. Product Aging is needed, Choosing appropriate method of acceleration is important.
2. Combination of Module/Product Tests to optimize chamber utilization
1. If no violation of Chamber Volume to product volume Ratio, then combine different modules
2. Test specs for different modules should be same
3. Automation of the Tests
1. Develop Software / HW tools to automate Testing i.e. Switching, Changing product function, or
running automatic tests in sequence
2. Automatic Data logging and monitoring can save time
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Overcomes
Proposed Overcomes:-
4. Defining and running the tests in parallel at different locations for two product Samples
1. Its possible if test flow is not defined for assemblies and test results are not dependent on each other.
5. Reducing Non-Operational Test and Increasing Operational Test in Qualification Plan
1. Some of the long term non-operational tests to simulate contamination, rusting or some cosmetic
properties of product which generally does not interrupt Product Functionality.
2. At least system will be ‘up’ even if parts got contaminated to acceptable limits.
6 Product Life Test may be optimized
1. Sometime, as a policy/ company standard, products are tested with safety factors i.e. 1.2, 1.5, 2.0.
Revisit life required by product and apply optimized safety factor
2. Over testing and over design of product can be avoided.
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Overcomes
Challenge:
3. No Historical Data available for the System / Product
Proposed Overcomes:-
1. Check the performance of the similar product- MTBF, failure Rates, CI Values.
2. Assigning the probability value to the system based on model and system reliability value
- Demonstration to required reliability value is must
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Overcomes
Challenge:
4. System Qualification with Actual User Conditions
Proposed Overcomes:-
1. We can’t duplicate exact user conditions in lab, but only simulation can be done.
1. Development of tools, Software and platform for Lab Testing
2. Design / Duplication of Loads to Product- Basically duplicating the I/P and O/P for product in use.
3. Field or Site Visit. Getting Customer user profile.
2. Design and planning of Deployment Tests at user location/site
1. Install a product in field before its release. Planning for Controlled Deployment Tests to exercise
product in actual user conditions. (Samples, Cycles, Recording and Analyzing)
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Overcomes
Challenge:
5. Demonstration of System Reliability, Time & Cost for the same
Proposed Overcomes:-
1. Perform the demonstration test with acceleration
1. Select an appropriate acceleration model. Temp as stress factor is preferable for electronic Components &
assemblies. Arrhenius Model is commonly used for semiconductor and electronics assemblies.
2. Select and define the stress factor (accelerator) limits based on Designers Operating Specs.
2. Enhance the reliability of Product using the accelerated life test like HALT
1. In other words Reduce the probability of failures occurrence by analyzing and improving on HALT results
2. Select the stress parameters for based on actual user / Environmental conditions i.e. Temp, Vibration,
humidity, Pressure and combination of these factors.
3. Find out design limits of assemblies to give confidence to Designer & Manufacturer
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Overcomes
Proposed Overcomes:-
3. ESS test on 100% production Units may be carried out
- This will remove insignificant part of product life like 0.5%, 1% etc.
4. Introduce Stress tests like Burn-In to eliminate weaknesses in Assemblies and avoids defectives
to go to customer.
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Overcomes
Challenge:
Restrictions on the cost of maintenance, parts replacement/repair
Proposed Overcomes:-
1. Preventive Maintenance to be carried out to avoid severe failure in future.
2. Enhance the Reliability of highly used parts or critical circuits. (previous section)
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Questions..??
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