COURSE OVERVIEW:

Industrial operations and maintenance environments are characterized by high stakes, uncertainty, and the constant pressure to balance technical requirements with financial constraints. This course provides a structured mathematical and logical framework for making complex decisions that affect asset performance and organizational stability. It focuses on moving beyond "gut feel" to a quantitative approach that evaluates risks, costs, and benefits to identify the most robust path forward in a dynamic industrial setting.

The scope of this training involves the application of decision science tools such as Decision Trees, Sensitivity Analysis, and Monte Carlo simulations specifically tailored for O&M challenges. Participants will learn how to structure a decision problem, identify all viable alternatives, and assign probabilities to various outcomes. The course emphasizes the importance of data quality and the psychological biases that often cloud professional judgment, providing techniques to mitigate these errors during the decision making process.

Coverage includes the evaluation of "Repair versus Replace" scenarios, the optimization of spare parts stocking levels, and the timing of major plant overhauls. Attendees will explore how to quantify the "Value of Information" when deciding whether to invest in additional condition monitoring or inspections. By the end of this course, participants will be equipped with a rigorous toolkit to justify their recommendations to executive leadership using sound economic and technical logic.

COURSE OBJECTIVES:

After completion of this course, the participants will be able to:

• Apply a structured 6-step decision making process to O&M challenges.
• Construct and analyze Decision Trees for complex maintenance scenarios.
• Quantify uncertainty using probability distributions and expert elicitation.
• Perform Sensitivity Analysis to identify the most critical variables in a decision.
• Evaluate "Repair versus Replace" options using Net Present Value (NPV).
• Use the "Value of Information" (VoI) concept to justify inspection costs.
• Identify and mitigate common cognitive biases in technical decision making.
• Analyze the risks of deferring maintenance using probabilistic modeling.
• Select optimal maintenance strategies by balancing risk, cost, and performance.
• Utilize Multi-Criteria Decision Analysis (MCDA) for equipment selection.
• Communicate the logic of complex decisions to non-technical stakeholders.
• Develop a robust business case for major capital expenditures in maintenance.

TARGET AUDIENCE:

This course is designed for Maintenance Managers, Plant Engineers, Operations Directors, Asset Managers, Reliability Engineers, and Project Managers who are responsible for high-impact operational decisions.

TRAINING COURSE METHODOLOGY:

A highly interactive combination of lectures, discussion sessions, and case studies will be employed to maximize the transfer of information, knowledge, and experience. The course will be intensive, practical, and highly interactive. The sessions will start by raising the most relevant questions and motivating everybody to find the right answers. The attendants will also be encouraged to raise more of their questions and to share in developing the right answers using their analysis and experience. There will also be some indoor experiential activities to enhance the learning experience. Course material will be provided in PowerPoint, with necessary animations, learning videos, and general discussions.

The course participants shall be evaluated before, during, and at the end of the course.

COURSE CERTIFICATE:

National Consultant Centre for Training LLC (NCC) will issue an Attendance Certificate to all participants completing a minimum of 80% of the total attendance time requirement.