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Senast publicerade

Analyzing Order-to-Cash Using Process Mining A Case Study in Collaboration with Paulig
(2026) Adolfsson, Jens; Saleh, Dilan
Organizations increasingly rely on digital data to understand and improve their business processes. Process Mining is a data-driven approach that uses event logs from information systems to visualize actual process behavior and identify inefficiencies. This thesis investigates how Process Mining can be applied in practice to analyze the Order-to-Cash process, with a particular focus on the use of pre-defined reference process models and backward-looking analytical techniques. The study is conducted as a case study in collaboration with Paulig, using Infor’s Process Mining solution integrated with the ERP system M3. Through a combination of Process Mining analysis, interviews, workshops and shadowing sessions, the thesis evaluates how well a pre-defined industry-specific process model reflects an organization’s actual Order-to-Cash process and how inefficiencies and bottlenecks can be identified. The reference process model proved to be a strong baseline for understanding the overall process structure, while the analysis revealed bottlenecks related to master data issues that cause unnecessary manual interventions and longer cycle times. The results demonstrate that Process Mining can support improvements in both administrative processes and physical logistics flows by revealing systematic issues that are difficult to detect through traditional qualitative methods alone. The study also highlights the importance of combining Process Mining insights with domain knowledge and stakeholder involvement to correctly interpret results.
Updating Paulings rules using a machine learning approach
(2026) Gustavsson, Pontus
Oxides are an important family of materials that have an extremely wide range of applications in for example semiconductors, pigments and catalysis. It is therefore important to have a solid understanding of these ubiquitous materials. In 1929 Linus Pauling proposed five rules for oxide stability that are widely used. These rules are however not good enough to describe oxide stability as only a fraction of stable oxides fulfil them. In this project a machine learning approach was used to attempt to find better rules based on the composition of oxides. This was done by training a set of autoencoders and analysing the latent spaces of these models by sampling new compositions from the models. Three different autoencoders were trained and based on the results, three new rules of thumb are proposed; Oxides containing only reactive non-metals are in general unstable, metals favour stability and heavier cations favour stability.
A Self–Trained Engine for Atomic Chess
(2025) Andersson, Emil; Hammerlid, Simon; Karlsson, Gustav; Klang, Sebastian; Porota Ndimurukundo, Ken; Söderberg, Elias
This thesis concerns the development of a chess engine to play a variant of chess called atomic chess, utilizing a neural network. The neural network is modeled after DeepMind’s AlphaZero, which is a model that learned standard chess from only the rules, and no real-world games (hence “zero”). We demonstrate an adapted model that improves its playing strength in atomic chess, given enough training time. This is done using a deep convolutional neural network, trained with data generated by a modified Monte Carlo tree search in a process called self-play. These two components feed each other data in a cycle: the neural network guides the tree search, and the results of the tree search are then used to train the network, repeatedly. The result is a trained network that is shown to have improved from the untrained model, which corresponds to an unguided or randomly guided Monte Carlo tree search. An extensive background aimed at computer engineering students is also included, explaining the terms used in the thesis.
Implementation and evaluation of game design patterns for a collaborative game
(2025) Wahlbeck, Leopold; Majberger, Anna; Lisborg, Alexander; Wirthgen, Adrian; Speziale, Marco; Cederberg, Jonatan
This report explores which game design patterns can impact the aspects of meaningful collaboration between players. Using the methodology Research Through Design, we have developed a collaborative game with the aim of identifying and testing patterns that promote player interaction, engagement, and collaborative behaviour. The process involved iterative prototyping, playtesting, and analysing player behaviour through observations and interviews. Challenges addressed include reducing player frustration and ensuring widespread and equal participation. By continuously reflecting over design decisions, we have aimed to deepen the understanding of which game design patterns that may enhance social interaction, collaboration and shared problem-solving in video game environments.
Web Based I/O Simulator for Education in Machine-Oriented Programming
(2025) Nilsson, Andreas; Kjellberg, Alexander; Nordén Elgh, Cecilia; Andersson, Niklas; Ahmed, Omar; Ranhage, Oskar
The Machine-Oriented Programming course at Chalmers University of Technology and the University of Gothenburg introduces students to low-level programming through microcontroller-based laboratory exercises. During the course, physical access to hardware is limited to scheduled lab sessions, which restricts opportunities for practice. To address this issue, a simulator is used to simulate the microcontroller unit (MCU) and the connectable Input/Output (I/O) units that are used in the course. This bachelor’s thesis presents the development of a web-based simulator for the I/O units that interfaces with the existing MCU simulator via WebSockets. This I/O simulator is developed separate from the MCU logic, with the goal of making it platform-independent as well as more usable, maintainable and accessible. It supports various I/O units such as switches, bargraphs, 7-segment displays and keypads. The application was evaluated through user testing with students who have previously taken the course. The overall reception was positive in terms of usability, visual design, and its potential as an educational tool for understanding and experimenting with machine-oriented programming.