Warehouse Operations and Performance Diagnosis
Turn warehouse flows and operating data into an evidence-based performance diagnosis.
An Optimization Perspective
Breno Alves Beirigo
MSc course · 5 EC · 2026–2027
Learn to turn warehouse flows and operational data into defensible decisions about networks, storage, layout, automation, and order picking.
Warehouses connect supply with demand, but every square metre, movement, buffer, and technology choice creates a trade-off. This course combines systems thinking with quantitative models so that you can diagnose performance, compare designs, and justify an improvement plan.
5 EC 140 hours of study
8 teaching weeks Weeks 36–43 of 2026
Five coursework milestones One real warehouse · teams of three
50% + 50% Coursework and final exam
Each module brings together its slides, tutorials, tools, and further reading.
Module 01 · Week 36
Warehouse Operations and Performance Diagnosis
Turn warehouse flows and operating data into an evidence-based performance diagnosis.
Module 02 · Week 37
Distribution Network Design and Facility Location
Distribution network structures, inventory positioning, facility location, and demand allocation under cost and service requirements.
Module 03 · Week 38
Storage Systems, Policies, and Storage Location Assignment
Translate item velocity and handling effort into defensible storage-policy and slotting decisions.
Module 04 · Week 39
Storage Space Requirements, Forward-Reserve Allocation, and Replenishment
Connect inventory rules, replenishment, and lane geometry to the space and service the warehouse needs.
Module 05 · Week 40
Warehouse Sizing, Layout, and Material-Handling System Design
Convert flows, relationships, and area requirements into a feasible, optimized facility layout.
Module 06 · Week 41
Order-Picking System Design and Control
Select a picking architecture and explain how travel, capacity, and automation affect throughput.
Module 07 · Week 42
Robotized and Automated Warehouse Systems
Coordinate routes, batches, zones, and multiple pickers while preserving operational realism.
Module 08 · Week 43
Exam Preparation and Assignment Work
Consolidate the course for the examination and turn your analyses into one defensible warehouse recommendation.
| Course week | Focus |
|---|---|
| 1 (W36) | Warehouse Operations and Performance Diagnosis |
| 2 (W37) | Distribution Network Design and Facility Location |
| 3 (W38) | Storage Systems, Policies, and Storage Location Assignment |
| 4 (W39) | Storage Space Requirements, Forward-Reserve Allocation, and Replenishment |
| 5 (W40) | Warehouse Sizing, Layout, and Material-Handling System Design |
| 6 (W41) | Order-Picking System Design and Control |
| 7 (W42) | Robotized and Automated Warehouse Systems |
| 8 (W43) | Exam Preparation and Assignment Work |
| 9 (W44) | Examination |
The syllabus summarizes the course structure. TimeEdit has the current appointments, times, and rooms.
A warehouse is a coordinated operating system. Its network position, demand, storage policy, layout, equipment, people, and information determine one another.
The central question is “Which design and control decisions produce the required service with a rational use of space, capacity, time, and cost?”
01
Explain the role, functions, flows, planning levels, and technology choices that shape contemporary warehouses.
02
Use operational data, activity profiles, costs, and performance indicators to identify constraints and improvement opportunities.
03
Evaluate distribution-network trade-offs and formulate quantitative warehouse-location decisions.
04
Compare storage policies and systems, estimate space requirements, and optimize storage allocation and facility layouts.
05
Reason about picking systems, routing, batching, zoning, travel time, and the operational consequences of automation.
06
Combine models, evidence, assumptions, and implementation constraints into a clear and critically evaluated improvement proposal.
Step 1
Identify the operational objective, relevant system boundary, data, constraints, and trade-offs before selecting a method.
Step 2
Use activity analysis and quantitative models to make alternatives explicit and test the consequences of assumptions.
Step 3
Translate results into a practical recommendation, critique its limitations, and improve it using feedback and operational knowledge.
Enrolled University of Twente students should use Canvas for announcements, submission routes, grades, and current course communication. TimeEdit remains authoritative for dates, rooms, and appointments.
Course: Warehousing (202400647)
Academic year: 2026–2027
Lecturers: Breno Alves Beirigo and Fabian Akkerman
Program: MSc Industrial Engineering and Management, University of Twente