Examination arrangement

Course content

The subject is a program specialization subject in 2nd year 2nd semester INGLOG. The subject consists of two main parts. The first part will provide students with basic knowledge of advanced logistics systems used in warehouse and fulfilment centers, production and transport as well as the use of automation, robotics, and digitization in logistics (Logistics 4.0/5.0). The second part of the course provides knowledge of advanced analysis and simulation methods for logistics systems under uncertainty (e.g., stochastic inventory management and statistical quality management). Student will learn how to make simple simulation models in Excel or Python as well as a computer simulation tool for Discrete Event Simulation (FlexSim).

Learning outcome

The course must convey the following specific knowledge to the candidate

• General knowledge of digitization and Industry 4.0/5.0 (Cyber ​​Physical Space, Internet of Things, Artificial Intelligence, Big Data, Machine Learning, Human-Centered approach)
• General knowledge of automation and robotization
• Automation, robotization and digitization in logistics: RFID, AGV, AMR, Drones, AR/VR
• Automated warehouse technology (AS/RS, AutoStore, order-picking systems, WMS)
• Inventory management under uncertainty (continuous review and periodic review)
• Statistical Quality Management
• Simulations modelling of logistic systems, Discrete Event Simulation (DES)

Skills: The candidate must be able to:

• Understand and implement key supply chain and logistics technologies in the digitization era of industrial IoT, autonomous applications and cyber-physical systems and how they can be integrated to generate added value.
• Understand systems in modern automated warehouses, terminals and distribution centers
• Building simulation models for inventory management under uncertainty
• Build and run simulations in FlexSim for simple production or warehouse systems
• Build dashboards for performance measurement/monitoring and improvement

Other important learning objectives: The candidate should be able to

• Gain a broad overview of the smart logistics and its role in building resilient and sustainable supply chain
• Understand the need for verifiable operations ethics and supply chain transparency in the digitalization era with complex systems and supply chains.

Learning methods and activities

Lectures, exercises, simulation laboratory, semester project.

Further on evaluation

The portfolio consists of 4 parts (total 100 points):

1. Assignment set 1 (20 p), submission deadline: End of February
2. Assignment set 2 (20 p), Submission deadline: Mid April
3. Semester report (20 p), submission deadline: End of May
4. Simulation project (40 p), submission deadline: End of May

Parts 1 and 2 are delivered individually on Inspera. Parts 3 and 4 are delivered in groups of a maximum of 2 also on Inspera.

Guidance is provided one quick day a week. Candidates can receive feedback on their performance along the way. Evaluation of the entire map is indicated with a letter grade.

In the event of a voluntary repetition of the survey, all parts must be taken again.

Specific conditions

Recommended previous knowledge

TLOG1015, TLOG2008, TLOG2009

Course materials

Given by the term start.