Reliability, Maintenance & Managing Risk
A week of short courses on Reliability and Risk
July 20-23, 2026
Huntsville, AL
Courses - Pankaj
Reliability Demonstration Test (RDT) – Strategy, Methods & Application
Reliability Demonstration Testing (RDT) provides quantitative evidence that a product or system meets specified reliability requirements at a defined confidence level. This focused training course delivers practical, engineering-oriented guidance on the strategic use and application of RDT across development, qualification, and production phases. The course emphasizes decision-making, risk management, and sensitivity analysis of key input variables, supported by concise theory and worked examples. The key learning objectives include the following.
- Understand the purpose and structure of RDT in engineering programs
- Apply parametric and non-parametric RDT methods
- Develop RDT plans using single and multiple-stress-level
- Recognize when to use cumulative exposure concepts in RDT design
- Use Bayesian methods to incorporate prior knowledge and update confidence
- Apply RDT principles to Production Reliability Acceptance Tests (PRAT)
- Identify key RDT input variables and perform sensitivity analysis
Strategic Root Cause Failure Analysis for Engineering Programs
Root Cause Failure Analysis (RCFA) is essential for identifying underlying causes of failures and preventing recurrence in engineering systems and products. This workshop provides a structured, practical approach to failure investigation using industry-recognized methodologies and analytical tools. The training emphasizes systematic thinking, human factors, evidence-based reasoning, and effective implementation of corrective and preventive actions to improve reliability and organizational learning. The key learning objectives include the following.
• Apply structured root cause analysis processes within engineering programs
• Use the 8D problem-solving framework to manage failure investigations
• Develop and apply cause-and-effect (fishbone) diagrams and the 5 Why’s method
• Construct and interpret Fault Tree Analysis (FTA) models
• Incorporate human factors into failure analysis
• Develop and validate causal theories using data and evidence
• Design effective corrective and preventive actions (CAPA)
• Evaluate the effectiveness and sustainability of implemented solutions
Pankaj Shrivastava
Pankaj Shrivastava is a reliability engineering leader with over 20 years of experience applying reliability, availability, and maintainability (RAM) principles across complex engineered systems. He currently serves as Discipline Manager and Principal Advisor – Reliability at Halliburton, where he leads the application of advanced reliability engineering methods to improve the performance, quality, and lifecycle outcomes of well completion tools. Pankaj specializes in Design for Reliability (DfR), life data analysis, predictive analytics, probabilistic risk assessment, and Six Sigma methodologies. Throughout his career, he has been instrumental in developing reliability strategies, tools, and processes that support new product development and operational excellence in high-reliability industries. Prior to Halliburton, Pankaj held senior technical and leadership roles at General Electric, where he led reliability and analytics initiatives for wind and gas turbine service agreements, and at Accenture Management Consulting, where he led predictive asset maintenance offerings and warranty analytics programs.
He is an active contributor to the global reliability engineering community, serving on the RAMS Management Committee, ASQ-RRD Management Committee and participating in industry standards development through API and AWES committees. Pankaj has authored more than 20 technical papers, holds a licensed patent in risk management systems, and is a frequent invited speaker at international conferences and industry workshops. Pankaj holds a master’s degree in Reliability Engineering and a bachelor’s degree in chemical engineering. He is a Certified Reliability Engineer and ASQ Certified Six Sigma Black Belt, with deep expertise in reliability modeling, analytics, and engineering leadership.