Applied Reliability

Course Description

ETI4186 — Applied Reliability is a 3-credit upper-division (senior-level) course in the Daytona State College Bachelor of Science in Engineering Technology, Industrial Engineering Technology concentration (BSET-IET). The course meets approximately 3 hours per week, accumulating 45 total contact hours over a 15-week semester. The BSET-IET program, launched in Fall 2024 through the Angela & D.S. Patel School of Engineering Technology, is the first BSET-IET program offered in the Florida College System and is delivered in a fully online format suitable for working professionals as well as on-campus students.

The course covers the practical application of reliability concepts and the analysis applicable to the design, development, production, logistic, and operation phases of system components. Reliability engineering is the quantitative discipline of ensuring that products and systems perform their intended function for a specified duration under specified operating conditions. The course emphasizes hands-on application of the principal methods of reliability analysis, including Failure Mode and Effects Analysis (FMEA), Fault Tree Analysis (FTA), statistical analysis of failure data, accelerated life testing, and the use of reliability software tools.

The BSET-IET program operates on a 2+2 model, building on a completed associate degree (typically an A.S. in Engineering Technology or related field) plus the lower-division engineering technology core. ETI4186 sits in the senior-year sequence and pairs with the program's broader industrial engineering technology curriculum, which includes Engineering Quality Assurance (ETI3116 — the immediate prerequisite), Applied Logistics (ETI4205), Operations Management (ETI4640), Project Management and Senior Design (ETI4448 / ETG4950C), Technical Administration (ETI4635), and Occupational Safety (ETI4704). The program is designed to prepare graduates for technical positions in Florida's expanding industrial operations and manufacturing sector, with particular attention to the Volusia and Flagler County manufacturing corridor and the broader Florida advanced-manufacturing economy.

Learning Outcomes

Required Outcomes

Upon successful completion of this course, the student will be able to:

• Define and apply the fundamental reliability terminology and metrics: reliability function R(t), failure function F(t), probability density function f(t), failure rate (hazard rate) h(t), Mean Time Between Failures (MTBF), Mean Time To Failure (MTTF), Mean Time To Repair (MTTR), and availability A(t).
• Apply standard failure distributions to model time-to-failure data, including the exponential, Weibull (two-parameter and three-parameter), normal, lognormal, and gamma distributions; recognize the contexts in which each distribution is appropriate.
• Perform statistical estimation of reliability parameters from failure data, including maximum likelihood estimation (MLE), median rank regression, and confidence interval construction for Weibull shape and scale parameters.
• Analyze reliability of system configurations, including series systems, parallel (redundant) systems, k-out-of-n redundancy, standby redundancy, and complex networks; calculate system reliability from component reliabilities.
• Conduct Failure Mode and Effects Analysis (FMEA) following standard industry methodology (SAE J1739, AIAG-VDA Handbook, or MIL-STD-1629), including severity (S), occurrence (O), and detection (D) ratings, the calculation of Risk Priority Numbers (RPN), and the development of corrective and preventive actions.
• Conduct Fault Tree Analysis (FTA), including the construction of fault trees with AND, OR, and combination gates; the calculation of top-event probability; and the identification of minimal cut sets.
• Apply accelerated life testing concepts, including the Arrhenius model for temperature acceleration, the inverse power law for stress acceleration, and the design of accelerated test plans to estimate field reliability from accelerated test data.
• Apply reliability concepts in design, including reliability allocation, reliability prediction (per MIL-HDBK-217, Telcordia SR-332, or IEC TR 62380), design for reliability (DfR) practices, and reliability-based design tradeoffs.
• Analyze maintainability and availability, including corrective and preventive maintenance, MTTR estimation, inherent vs. operational availability, the role of preventive maintenance scheduling, and reliability-centered maintenance (RCM) introduction.
• Apply reliability data collection and analysis practices, including the use of failure reporting systems (FRACAS — Failure Reporting, Analysis, and Corrective Action System), censored data treatment, and the integration of field-failure data into design improvement cycles.
• Use reliability software tools at the introductory level, including Minitab (Reliability menu), ReliaSoft Weibull++ or equivalent, and Excel-based Weibull analysis; produce probability plots, hazard plots, and reliability function plots.
• Communicate reliability analysis results in professional engineering reports, including appropriate use of probability plots, parameter estimates with confidence intervals, FMEA worksheets, and engineering recommendations grounded in the analysis.

Optional Outcomes

Depending on instructor emphasis and time available, students may also:

• Begin preparation for the ASQ Certified Reliability Engineer (CRE) credential.
• Apply Bayesian reliability analysis for the incorporation of prior knowledge into reliability estimates.
• Conduct warranty analysis using field-returns data, including the Nelson-Aalen estimator and warranty-data Weibull modeling.
• Apply repairable system analysis, including the Power Law Process (Crow-AMSAA) for trend analysis of repair data, and the homogeneous Poisson process model.
• Conduct physics-of-failure analysis, linking failure mechanisms (fatigue, corrosion, wear, electromigration, thermal cycling) to time-to-failure modeling.
• Survey software reliability models, including the Jelinski-Moranda model, the Goel-Okumoto NHPP model, and the Musa-Okumoto logarithmic model.
• Apply reliability concepts to safety-critical systems, including IEC 61508 functional safety, ISO 26262 automotive functional safety, and DO-178C airborne software considerations.

Major Topics

Required Topics

• Reliability Engineering Fundamentals — definitions, history of reliability engineering, the role of reliability in product development, customer expectations, the cost of unreliability.
• Probability and Statistics Review for Reliability — probability density and cumulative distribution functions, expectation and variance, conditional probability, Bayes' theorem, the law of large numbers.
• Reliability Functions and Metrics — reliability function R(t), failure function F(t), probability density f(t), failure rate (hazard rate) h(t), cumulative hazard H(t); MTBF, MTTF, MTTR; bathtub curve.
• Failure Distributions — exponential distribution (constant failure rate), Weibull distribution (two-parameter and three-parameter forms), normal and lognormal distributions, gamma distribution; selection of appropriate distributions for different failure mechanisms.
• Weibull Analysis — Weibull shape parameter (β) interpretation (β < 1 infant mortality, β = 1 constant failure rate, β > 1 wear-out), Weibull characteristic life (η), median rank regression, maximum likelihood estimation, confidence interval construction, probability plotting.
• System Reliability Modeling — series systems (product rule), parallel (active redundancy) systems, k-out-of-n configurations, standby redundancy with switch reliability, complex network reduction.
• Failure Mode and Effects Analysis (FMEA) — process FMEA (PFMEA), design FMEA (DFMEA), system FMEA; severity, occurrence, and detection rating scales; Risk Priority Number (RPN); the AIAG-VDA FMEA Handbook approach; corrective and preventive action development.
• Fault Tree Analysis (FTA) — top events, basic events, intermediate events, AND/OR gates; top-event probability calculation; minimal cut sets; common-cause failures.
• Accelerated Life Testing — Arrhenius model for thermal acceleration, inverse power law for non-thermal stresses, accelerated test plan design, extrapolation from accelerated conditions to field-use conditions, time-compression factor.
• Reliability Allocation and Prediction — top-down reliability allocation methods, prediction handbooks (MIL-HDBK-217 for electronics, Telcordia SR-332, IEC TR 62380), the limits of prediction methods.
• Maintainability and Availability — corrective maintenance, preventive maintenance, inherent vs. operational availability, MTTR estimation, the role of spares provisioning, reliability-centered maintenance (RCM) introduction.
• FRACAS — Failure Reporting, Analysis, and Corrective Action System — structured field-data collection; the role of FRACAS in reliability improvement; integration with quality management systems.
• Reliability Software Tools — Minitab Reliability menu, ReliaSoft Weibull++ (or equivalent), R packages for reliability (survival, weibull, fitdistrplus), Excel-based Weibull analysis.
• Reliability Engineering Reports — professional engineering communication, probability plot interpretation, parameter estimates with confidence intervals, FMEA worksheets, technical recommendations.

Optional Topics

• ASQ Certified Reliability Engineer (CRE) Examination Preparation — the comprehensive body of knowledge tested in the CRE examination.
• Bayesian Reliability Analysis — Bayesian inference for reliability parameters, the use of prior information from historical data or engineering judgment.
• Repairable System Analysis — Power Law Process (Crow-AMSAA), homogeneous Poisson process, trend analysis of repair data.
• Warranty Analysis — Nelson-Aalen estimator, warranty-cost modeling, claims-data analysis.
• Physics-of-Failure — linking specific failure mechanisms (fatigue, corrosion, wear, electromigration) to time-to-failure modeling.
• Software Reliability — Jelinski-Moranda, Goel-Okumoto NHPP, Musa-Okumoto, and other software-reliability models.
• Functional Safety — IEC 61508 safety integrity levels (SIL), ISO 26262 automotive safety integrity levels (ASIL), DO-178C airborne software design assurance levels.

Resources & Tools

• Standard textbooks — common adoptions for BSET-IET reliability courses include Charles E. Ebeling, An Introduction to Reliability and Maintainability Engineering (3rd ed., Waveland Press); Paul A. Tobias and David C. Trindade, Applied Reliability (3rd ed., CRC Press); Elsayed A. Elsayed, Reliability Engineering; Patrick D. T. O'Connor and Andre Kleyner, Practical Reliability Engineering (5th ed., Wiley).
• Reference handbooks — MIL-HDBK-217F Notice 2 (Reliability Prediction of Electronic Equipment, the foundational U.S. military reliability prediction handbook); Telcordia SR-332 (Reliability Prediction Procedure for Electronic Equipment, the telecommunications-industry standard); IEC TR 62380 (Reliability Data Handbook).
• Industry standards — SAE J1739 (Potential Failure Mode and Effects Analysis); AIAG-VDA FMEA Handbook (the current automotive industry standard, replacing AIAG 4th edition and VDA Volume 4); MIL-STD-1629A (Procedures for Performing FMECA); IEC 60812 (FMEA); IEC 61025 (Fault Tree Analysis); ISO 14224 (reliability data collection for process industries).
• Reliability software — Minitab (Reliability/Survival menu — the standard educational reliability software); ReliaSoft Weibull++ and BlockSim (Hottinger Bruel & Kjaer, the industry-leading commercial reliability software); R with the survival, fitdistrplus, weibull, and reliaR packages (free, increasingly used in academic and industrial reliability work); Microsoft Excel with reliability templates and the Solver add-in for Weibull parameter estimation.
• Professional organizations — ASQ (American Society for Quality) Reliability and Risk Division, with the Certified Reliability Engineer (CRE) credential; IEEE Reliability Society; RAMS (Reliability and Maintainability Symposium) annual conference.
• Online educational resources — Reliawiki (ReliaSoft's free reference compendium); the NIST/SEMATECH e-Handbook of Statistical Methods (free, comprehensive); the ASQ Open Access publications.
• Daytona State BSET-IET online learning platform — Canvas LMS with integrated discussion, video lectures, and assignment submission infrastructure supporting the fully-online BSET-IET delivery model.

Career Pathways

ETI4186 is a core senior-level course in the BSET-IET program, preparing graduates for reliability and quality engineering roles in Florida's manufacturing and aerospace sectors:

• Reliability Engineer / Reliability Technician — entry- and mid-level positions in Florida's manufacturing and aerospace industries. Major Florida employers include B. Braun Medical, Boston Whaler, Hudson Technologies, Pentair, ABB, Germfree, Dynamic Engineering Innovations, Everglades Boats, Dougherty Manufacturing, SCCY Firearms, and Sparton (the Volusia/Flagler manufacturing employers actively partnered with Daytona State's FAME program). Florida statewide industrial engineering technologist median wages typically range from $60,000 to $85,000+ annually depending on industry, experience, and certifications.
• Quality Engineer with Reliability Specialization — Florida's medical device industry (B. Braun, Stryker, Boston Scientific operations), pharmaceutical manufacturing, and FDA-regulated industries combine quality engineering and reliability engineering competencies.
• Aerospace Reliability and Safety Engineer — Florida's aerospace sector concentrated on the Space Coast (Kennedy Space Center, Cape Canaveral Space Force Station, SpaceX, Blue Origin, Boeing, Lockheed Martin, Northrop Grumman, L3Harris, the United Launch Alliance) employs significant reliability engineering staff for space vehicle, ground support equipment, and avionics reliability work. Aerospace reliability engineering frequently requires security clearance and supports defense-industry careers.
• Defense and Department of Defense Contractors — Florida's defense corridor (Patrick Space Force Base, MacDill AFB, NSA Pensacola, USSOCOM) and the contractor ecosystem employ reliability engineers for system reliability, maintainability, and availability (RMA) work on Department of Defense systems.
• Power Generation Reliability — Duke Energy Florida, Florida Power & Light (FPL), Tampa Electric Company (TECO), JEA (Jacksonville), Orlando Utilities Commission (OUC), and the Florida cogeneration sector employ reliability engineers for power plant reliability and maintenance optimization.
• Theme Park and Hospitality Engineering Reliability — Walt Disney World, Universal Studios, and SeaWorld maintain dedicated reliability engineering organizations for ride safety, show systems, and large-facility reliability.
• Industrial Manufacturing Reliability — Florida's pulp/paper mills, chemical plants, phosphate processing, sugar processing, and food manufacturing sectors all employ reliability engineers for plant reliability and predictive maintenance programs.
• Graduate Study — ETI4186 provides foundational preparation for graduate study in industrial engineering, reliability engineering, or systems engineering at Florida public universities and elsewhere.

Special Information

Program Context

ETI4186 is offered in the Daytona State College Bachelor of Science in Engineering Technology, Industrial Engineering Technology concentration (BSET-IET), the first BSET-IET program in the Florida College System. The program is administered through the Angela & D.S. Patel School of Engineering Technology within the College of Business, Engineering, and Technology at Daytona State College.

Online Delivery

The BSET-IET program is delivered in a fully online format, suitable for working professionals who continue full-time employment while completing the degree. ETI4186 employs asynchronous online instruction with synchronous discussion sessions, video lectures, software-based laboratory exercises, and online proctored examinations. Students access course materials through the Canvas Learning Management System.

Prerequisites

The course requires ETI3116 — Engineering Quality Assurance as a prerequisite. ETI3116 provides the foundational statistical quality control concepts (control charts, process capability, sampling plans, ANOVA, designed experiments) that ETI4186 extends into reliability engineering. Students should have completed the lower-division Engineering Technology core (typically an A.S. in Engineering Technology), college-level statistics, and the BSET-IET 3xxx-level coursework before enrolling.

Industry Certifications

The course content directly prepares students for several industry-recognized credentials:

• ASQ Certified Reliability Engineer (CRE) — the foundational reliability engineering credential offered by the American Society for Quality. Requires 8 years of work experience or equivalent (education substitutes for experience: BSET counts toward CRE experience requirements). The CRE body of knowledge directly aligns with ETI4186 content.
• ASQ Certified Quality Engineer (CQE) — closely related; many reliability engineers also pursue CQE.
• IISE Certified Industrial Engineer Specializations — emerging credential through the Institute of Industrial and Systems Engineers.
• Six Sigma Black Belt (SSBB) — reliability engineering is closely related; many practitioners hold dual certifications.

2+2 Articulation Model

The BSET-IET program admits students with a completed associate degree (A.S. in Engineering Technology preferred; A.A. or A.A.S. acceptable with appropriate prerequisites). The program is designed to facilitate transfer from any Florida public college's A.S. Engineering Technology program, with seamless articulation of the lower-division engineering technology core.

ABET Accreditation

The BSET-IET program is designed for ABET Engineering Technology Accreditation Commission (ETAC) accreditation, the standard for engineering technology programs in the United States. ABET ETAC accreditation is essential for graduates seeking certain federal, state, and industry positions and supports professional engineering technology recognition.

Florida Industry Context

Florida's manufacturing sector employs more than 380,000 workers across diverse industries: aerospace and defense (Space Coast cluster), medical devices and pharmaceuticals, marine and boatbuilding (Volusia and Flagler coastal manufacturing), food and beverage manufacturing, pulp and paper, phosphate processing, sugar processing, consumer electronics, and chemicals. The Volusia/Flagler manufacturing corridor specifically hosts the FAME (Federation for Advanced Manufacturing Education) partnership employers (ABB, B. Braun, Boston Whaler, Pentair, Sparton, and others) that hire Daytona State Engineering Technology graduates directly.

Time Commitment

A 3-credit upper-division engineering technology course conventionally implies approximately 9-12 hours per week of out-of-class study, including textbook reading, problem sets, reliability software tutorials, FMEA and FTA exercises, and exam preparation. The combination of mathematical content (probability distributions, regression, MLE) and engineering analysis (FMEA, FTA, system reliability) makes this one of the more demanding courses in the BSET-IET sequence.

AI Integration

Generative-AI tools have substantial but careful applications in reliability engineering. AI tools can explain reliability concepts, help with statistical interpretation, suggest FMEA failure modes for systems, and assist with reliability calculations. However, AI tools frequently make errors in probability and statistics calculations, particularly with Weibull parameter estimation, censored data analysis, and complex system reliability calculations. AI also cannot replace the engineering judgment required for FMEA — the identification of relevant failure modes for a specific system requires substantive engineering knowledge of the system being analyzed. The use of AI-generated reliability analyses without independent verification is professionally hazardous and is generally a violation of academic integrity policy. The fundamental skills of reliability engineering — careful probabilistic reasoning, systematic failure mode identification, statistical analysis of failure data, and engineering judgment grounded in physical understanding — are irreducibly the student's responsibility.

Program Contact

For program-specific questions, students should contact the BSET program office at bset@daytonastate.edu or the Angela & D.S. Patel School of Engineering Technology directly.