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MAST2012

Condition Based Operation and Maintenance

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Assessments and mandatory activities may be changed until September 20th.

Credits 7.5
Level Intermediate course, level II
Course start Spring 2026
Duration 1 semester
Language of instruction Norwegian
Location Trondheim
Examination arrangement Aggregate score

About

About the course

Course content

The course is taught and supervised in Norwegian.

The course focuses on the collection of condition data and the use of such data in decisions regarding the operation and maintenance of technical installations.

The course is divided into the following 4 modules:

  1. Predictive Maintenance (PM) with a focus on:

    • Terminology
    • Establishing goals and strategies for PM
    • Management of PM
  • Collection and Processing of Condition Data with a focus on:

    • Selected methods for collecting condition data
    • Processing of condition data
  • Condition Data Used in Diagnosis and Prognosis with a focus on:

    • Mathematical/statistical models
    • Brief introduction to machine learning
    • Visualization of diagnosis and prognosis
  • Operations and Maintenance Decisions:

    • Use of diagnosis and prognosis derived from condition data in maintenance decisions
  • Learning outcome

    After completing the course, the candidate will have the following fundamental knowledge, skills, and general competence related to condition-based operations and maintenance.

    The candidate has knowledge of:

    • Predictive maintenance
    • Collection of condition data, both digital and analog, on technical installations. The focus is on:
      • Methods for collecting analog and digital condition data
      • Equipment for collecting condition data, with a particular focus on internet-based solutions
    • Use of condition data in:
      • Diagnosing the condition of technical installations
      • Assessing the remaining lifetime of technical installations
      • Operations and maintenance decisions

    The candidate has the following skills:

    • Can select:
      • Method for measuring condition parameters
      • Equipment for measuring condition parameters
    • Can perform:
      • Collection of condition data
      • Processing of condition data
      • Analysis of condition data
      • Use of condition data in operations and maintenance decisions

    General Competence: The candidate has the following competence:

    • Practical understanding and insight into how condition-based maintenance affects:
      • Operational reliability
      • Lifetime
      • Sustainability
      • Health and environment
      • Economy
    • Ability to formulate and discuss technical solutions within predictive operations and maintenance with skilled workers and leading personnel on a professional basis.
    • Ability to critically and reflectively approach condition-based operations and maintenance.

    Learning methods and activities

    In addition to physical teaching, lectures will be streamed and recordings will be made available on NTNU’s digital learning platform.

    Learning methods and activities include, but are not limited to:

    • Interactive lectures using digital tools
    • Digital exercises
    • Exercises in the classroom
    • Laboratory exercises in groups
    • Project work / problem-based learning in groups (graded semester assignment)

    Students will submit a graded semester assignment in groups. It is expected that students themselves will be the driving force in completing the semester assignment.

    Mandatory coursework requirements:

    To be eligible for the exam, the candidate must have submitted and received approval for the following:

    • Digital quizzes - a specified number (individual submission)
    • Reflection notes - a specified number (individual submission)
    • Registered in a semester assignment group (individual registration)
    • Collaboration agreement for the semester assignment group (group submission)
    • A3 poster presenting the semester assignment (group submission)

    The mandatory coursework requirements must be submitted on NTNU’s digital learning platform.

    Compulsory assignments

    • A3 poster of semester assignment
    • Group registration semester assignment
    • Agreement of cooperation semester assignment
    • Digital Quiz
    • Reflection paper

    Further on evaluation

    Mandatory activities from previous semesters can be approved by the department when retaking the course, provided there have not been significant changes in the course structure.

    The assessment in the course (A-F) is based on:

    • Written school exam in Inspera, which counts for 40% of the total grade
    • A group assignment submitted in Inspera, which counts for 60% of the total grade

    Both the school exam and the group assignment must be passed to receive a grade in the course.

    Permitted aids for the exam: G: Specified printed and handwritten aids allowed. All calculators allowed.

    Deferred exam (continuation exam) is arranged in August. For the deferred exam, the written exam may be changed to an oral exam.

    Continuation and voluntary retake/improvement can be carried out for individual partial assessments without retaking both partial assessments in the course (provided the course’s assessment scheme has not changed). It is possible to appeal partial assessments in this course before all partial assessments are completed.

    Course materials

    Will be announced at the start of the course.

    Online resources found in the NTNU library and the National Library are used in the course.

    The book - An introduction to predictive maintenance av R. Keith Mobley (1943-) is reccomended. Found in the digital format at the NTNU library

    Subject areas

    • Operations and Maintenance Management
    • Operation technology

    Contact information

    Examination

    Examination

    Examination arrangement: Aggregate score
    Grade: Letter grades

    Ordinary examination - Spring 2026

    School exam
    Weighting 40/100 Examination aids Code G Duration 3 hours Exam system Inspera Assessment Place and room Not specified yet.
    Semester Assignment
    Weighting 60/100 Examination aids Code A Exam system Inspera Assessment

    Re-sit examination - Summer 2026

    School exam
    Weighting 40/100 Examination aids Code G Duration 3 hours Exam system Inspera Assessment Place and room Not specified yet.