Preparing for a Digital Twin at Alfa Laval
(2025) MIOM05 20251Production Management
Department of Mechanical Engineering Sciences
- Abstract
- Problem description: Alfa Laval, a global leader in providing solutions for heat transfer, separation, and fluid handling, seeks to improve production scheduling at their component factory in Lund. They aim to digitalise the process by developing a digital twin (DT), a virtual model of the manufacturing system. The DT will simulate production flow to support decision-making and optimise scheduling. Before implementation, Alfa Laval wants to understand how the DT can add value to their operations and identify the key factors and challenges associated with its adoption.
Purpose: The purpose of this thesis is to develop a base model for a digital twin, a digital model, for the small pressline of plates at Alfa Laval’s Global Core... (More) - Problem description: Alfa Laval, a global leader in providing solutions for heat transfer, separation, and fluid handling, seeks to improve production scheduling at their component factory in Lund. They aim to digitalise the process by developing a digital twin (DT), a virtual model of the manufacturing system. The DT will simulate production flow to support decision-making and optimise scheduling. Before implementation, Alfa Laval wants to understand how the DT can add value to their operations and identify the key factors and challenges associated with its adoption.
Purpose: The purpose of this thesis is to develop a base model for a digital twin, a digital model, for the small pressline of plates at Alfa Laval’s Global Core Component Factory in Lund. The main goal is to explore the potential of a simheuristic approach for improving productivity, specifically in terms of increasing throughput and decreasing setup time. The model will primarily support the planners responsible for short-term scheduling. The research will also focus on evaluating key factors and challenges of using the created digital model for production scheduling at Alfa Laval.
Methodology: The study combines exploratory and problem-solving research strategies to optimise production scheduling using an operations research framework. The research follows four key steps: defining the problem through data collection and interviews, formulating a model, developing a simulation model with genetic algorithms and testing the model for accuracy and reliability. A literature review supports the methodology and further analysis ensures robustness.
Conclusions: The thesis resulted in the development of a digital model of Alfa Laval’s small pressline and a new optimisation process. The model offers enhanced visibility, efficiency and decision support in short-term production planning. However, challenges include planning complexity, data accuracy and integration. The model must evolve from a digital representation to a fully integrated DT with real-time data exchange to unlock its full potential. (Less)
Please use this url to cite or link to this publication:
http://lup.lub.lu.se/student-papers/record/9190892
- author
- Andersson Alenbratt, Louise LU and Kritz, Matilda LU
- supervisor
- organization
- course
- MIOM05 20251
- year
- 2025
- type
- H2 - Master's Degree (Two Years)
- subject
- keywords
- Decision Support Systems, Digital Twin, Digital Model, Industry 4.0, Production Planning, Simulation Modelling, Supply Chain
- language
- English
- id
- 9190892
- date added to LUP
- 2025-06-12 18:45:37
- date last changed
- 2025-06-12 18:45:37
@misc{9190892,
abstract = {{Problem description: Alfa Laval, a global leader in providing solutions for heat transfer, separation, and fluid handling, seeks to improve production scheduling at their component factory in Lund. They aim to digitalise the process by developing a digital twin (DT), a virtual model of the manufacturing system. The DT will simulate production flow to support decision-making and optimise scheduling. Before implementation, Alfa Laval wants to understand how the DT can add value to their operations and identify the key factors and challenges associated with its adoption.
Purpose: The purpose of this thesis is to develop a base model for a digital twin, a digital model, for the small pressline of plates at Alfa Laval’s Global Core Component Factory in Lund. The main goal is to explore the potential of a simheuristic approach for improving productivity, specifically in terms of increasing throughput and decreasing setup time. The model will primarily support the planners responsible for short-term scheduling. The research will also focus on evaluating key factors and challenges of using the created digital model for production scheduling at Alfa Laval.
Methodology: The study combines exploratory and problem-solving research strategies to optimise production scheduling using an operations research framework. The research follows four key steps: defining the problem through data collection and interviews, formulating a model, developing a simulation model with genetic algorithms and testing the model for accuracy and reliability. A literature review supports the methodology and further analysis ensures robustness.
Conclusions: The thesis resulted in the development of a digital model of Alfa Laval’s small pressline and a new optimisation process. The model offers enhanced visibility, efficiency and decision support in short-term production planning. However, challenges include planning complexity, data accuracy and integration. The model must evolve from a digital representation to a fully integrated DT with real-time data exchange to unlock its full potential.}},
author = {{Andersson Alenbratt, Louise and Kritz, Matilda}},
language = {{eng}},
note = {{Student Paper}},
title = {{Preparing for a Digital Twin at Alfa Laval}},
year = {{2025}},
}