TLOG2011

Digitalization and Simulation of Logistics Systems

Spring

Trondheim

Norwegian

Overview

26 candidates

Average grade

A

4.69

0.52

Pass rate

100%

same

Grade distribution
Average over time
Pass rate over time

About this course

Content

Module 1: Introduction to Logistic Systems, Automation, and Digitalization

  • Overview of Logistic Systems
  • Automation in Logistics Systems
  • Digitalization in Logistics
  • Case Studies

Module 2: Stochastic Simulation and Inventory Management under Uncertainty

  • Introduction to Monte-Carlo spreadsheet simulation
  • Inventory management systems under uncertainty - policies and performance metrics
  • Simulation modeling of inventory management systems
  • Simulation modeling of basic queueing systems

Module 3: Discrete Event Simulation of Logistic Systems

  • Introduction to advanced computer simulation, and digital twin technology
  • Introduction to Discrete Event Simulation (DES) & simulation software
  • Simulation modeling and analysis of the logistics systems

Learning outcomes

This is a specialization course in the 4th semester of the INGLOG study program. The course consists of three modules:

Knowledge:

After completing the course, the candidate will have specific knowledge about:

  • Logistical systems, automation, and digitalization of such systems
  • Inventory management under uncertainty, various policies, and their simulation
  • Safety Stock, Service Level, and Fill Rate
  • Simulation of a real logistical system using DES software.

Ferdigheter:

After taking the course, the candidate will be able to

  • understand various logistical systems, automation, and digitalization technologies in logistics
  • evaluate the automation of a logistical system, or apply a digitalization technology
  • build simulation models for inventory management under uncertainty, and analyze the obtained results
  • build and run a DES model for a simple production or warehouse system by using a software

General competence

After taking the course, the candidate will have a good understanding of

  • innovation and innovative thinking
  • Systems Thinking, and problem-solving

Teaching methods

Lectures, exercises, simulation laboratory, semester project.