Maintenance and service logistics

We start with a brief overview of what is needed for managing the availability of advanced technical systems, and we discuss the perspectives of manufacturers and users of such systems. To efficiently and effectively maintain systems, it is necessary to both use smart maintenance policies and spare parts inventory control policies. We therefore use about half of the course to cover spare parts inventory control models and optimization algorithms. The assignment is on this topic and requires students to implement such algorithms (e.g., in Matlab or Python). After that, we use about half of the course to cover the main preventive maintenance policies: age-based policies, minimal repair policies, and inspection-based policies.

After this course, students are able to:

• describe the main elements of the maintenance of technical systems
• paraphrase important concepts related to spare parts inventory models (e.g., different service level measures and the PASTA property)
• construct a spare parts inventory model and optimization procedure for a given situation in practice
• implement optimization procedures for spare parts inventory control (in Python)
• verify whether a given spare parts inventory model has certain important properties (e.g., costs are increasing and convex in the base stock level)
• explain the differences between widely-used maintenance policies such as age-based and inspection-based maintenance
• apply the fundamental concepts in probability and reliability theory to evaluate the expected cost rate of a maintenance policy
• construct and solve a maintenance optimization model for a given situation in practice

You must meet the following requirements

• Registered for a degree programme other than
• HBO-TOP Applied Physics, Pre-Master

• Handouts