ME-703-D Reliability Engineering - Jun 2025 Question Paper

Under each question, How to answer lists the points an answer should cover, outlined by CampusPrep from the syllabus. Check the details against your textbook.

1. 7 Marks
   aDefine "reliability". Explain importance of reliability engineering in the field of AI and data science.
   How to answer

   • Definition of reliability as probability of performing intended function for specified time under stated conditions
   • Key elements: probability, intended function, time, operating conditions
   • Importance in AI and data science: trustworthy models, data quality, system uptime, safety
   • Examples: reliable ML pipelines, autonomous systems, predictive maintenance
2. 7 Marks
   bDiscuss important steps in reliability analysis procedure.
   How to answer

   • Objective and scope definition and data collection
   • System modeling, failure definition and failure analysis
   • Selection of reliability models and parameter estimation
   • Reliability evaluation, validation and improvement actions
3. 7 Marks
   aExplain failure pattern of complex product.
   How to answer

   • Concept of complex product with multiple failure modes
   • Bathtub curve: infant mortality, useful life, wear-out phases
   • Causes in each phase and failure rate behavior
   • Implications for design, testing and maintenance
4. 7 Marks
   bDefine and explain Hazard rate function.
   How to answer

   • Definition of hazard rate as instantaneous failure rate
   • Formula $h(t) = f(t)/R(t)$ and interpretation
   • Behavior for increasing, constant and decreasing failure rates
   • Role in reliability prediction and maintenance
5. 7 Marks
   aWhat do you mean by 'Set Theory'? Discuss its importance and applications.
   How to answer

   • Definition of set theory: sets, elements, operations
   • Importance in probability and reliability logic
   • Union, intersection, complement with Venn diagrams
   • Applications in fault trees, event analysis and system modeling
6. 7 Marks
   bWhat do you understand by Bay's theorem? Discuss in details.
   How to answer

   • Statement of Bayes' theorem for conditional probability
   • Formula $P(A|B) = P(B|A)P(A)/P(B)$ with terms explained
   • Derivation from definition of conditional probability
   • Applications in reliability updating, diagnosis and testing
7. 7 Marks
   aWhat do you mean probability distribution functions? Discuss density functions for different types of discrete and continuous variables.
   How to answer

   • Definition of probability distribution and distribution functions
   • Discrete variables: PMF examples binomial, Poisson
   • Continuous variables: PDF examples exponential, normal, Weibull
   • CDF, properties and use in reliability modeling
8. 7 Marks
   bCompare Weibull distribution, Normal distribution and lognormal distribution.
   How to answer

   • PDF, hazard shapes and parameters of Weibull, Normal, Lognormal
   • Comparison of symmetry, skewness and tail behavior
   • Applicability: life data, wear-out, repair times, fatigue
   • Selection criteria for reliability data
9. 7 Marks
   aWhat is the role of fatigue strength in geometric modeling of structures? Explain failure rate versus time.
   How to answer

   • Link between fatigue strength, stress and geometric stress concentration
   • Role of geometric modeling in life prediction
   • Bathtub / failure rate vs time curve explanation
   • Design improvement for fatigue reliability
10. 7 Marks
    bExplain relationship between reliability and hazard functions.
    How to answer

    • Definitions of $R(t)$, $f(t)$ and $h(t)$
    • Derivation of $h(t)=f(t)/R(t)$ and $R(t)=\exp(-\int_0^t h(u)du)$
    • Interpretation for constant and time-dependent hazard
    • Graphical relationship and use in reliability evaluation
11. 7 Marks
    aDefine 'optimization' in reliability engineering. Discuss optimization techniques for system reliability with redundancy.
    How to answer

    • Definition of optimization in reliability context
    • Objective: maximize reliability under cost, weight, volume constraints
    • Redundancy optimization: active, standby, mixed redundancy
    • Techniques: Lagrange, dynamic programming, heuristic search
12. 7 Marks
    bDiscuss reliability optimization by non-linear programming.
    How to answer

    • Formulation of reliability optimization as non-linear program
    • Objective function and constraints for component reliabilities
    • Solution methods: Kuhn-Tucker, penalty, gradient methods
    • Example of redundancy allocation solved by NLP
13. 7 Marks
    aWhat do you mean by event tree and fault tree analysis? Discuss giving suitable examples.
    How to answer

    • Definitions of event tree (forward inductive) and fault tree (backward deductive)
    • Symbols: AND, OR gates, basic events, branches
    • Suitable examples with tree construction steps
    • Applications in risk and reliability assessment
14. 7 Marks
    bExplain 'Reliability testing' and 'measurement of reliability'.
    How to answer

    • Definition and objectives of reliability testing
    • Types: accelerated, truncated, sequential tests
    • Measurement: MTBF, failure rate, availability indices
    • Data analysis and estimation procedure
15. 14 Marks
    Write short note on following (any two):

    1. i)Bathtub curve
    2. ii)Laws of probability
    3. iii)Time dependent failure models
    4. iv)Series, parallel and mixed systems
    How to answer

    • Lead-in about short notes on any two topics
    • Key definition, diagram/formula and features for each chosen topic
    • Applications and significance in reliability
    • Comparison or example where relevant