Objectives and Content
This course provides an introduction to analysis and monitoring of industrial processes by means of data analytical methods. The course covers univariate and multivariate statistical process monitoring, exploration and optimization of processes using multivariate design and latent variable analysis of historic data, and prediction of product quality and discharges from feed and process data. The methods are illuminated with real examples from both onshore and offshore process industry,e.g., oil-source correlation, modelling of reservoir characteristics from well logs and application on rigs and refineries.
After completing the course PTEK226 the student will be able to:
- set up and analyse the results from an experimental design.
- explain the assumptions and basic equations in multiple linear regression, and to perform a regression analysis.
- explain and to use methods for response optimisation.
- use latent variables to interpret, classify and predict, and to state the theory behind this.
- do an independent data analysis using chemometric software.
Compulsory Assignments and Attendance
2 computer exercises with report. The exercises is valid for 7 semester.
Forms of Assessment
Written examination (4h).
Examination Support Material
Non- programmable calculator, according to model listed in faculty regulations
The grading scale used is A to F. Grade A is the highest passing grade in the grading scale, grade F is a fail.
KJEM225: 10 credits
For written exams, please note that the start time may change from 09:00 to 15:00 or vice versa until 14 days prior to the exam. The exam location will be published 14 days prior to the exam.
Type of assessment: Semester thesis and one written exam
- Withdrawal deadline