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  • About
  • The Global ETD Search service is a free service for researchers to find electronic theses and dissertations. This service is provided by the Networked Digital Library of Theses and Dissertations.
    Our metadata is collected from universities around the world. If you manage a university/consortium/country archive and want to be added, details can be found on the NDLTD website.
1

Improving Software Development Process Through Industry 4.0 Technologies : A focus on Railway Embedded Software

Eriksson, Julia, Busck, Victor January 2023 (has links)
Date: 4th June 2023 Level: Master thesis in Product- and Process Development, advanced level, 30 credits Institution: School of Innovation, Design and Engineering at Mälardalen University Authors: Victor Busck Julia Eriksson Title: Improving Software Development Process Through Industry 4.0 Methodologies - A focus on Railway Embedded Software Supervisor: Yuji Yamamoto - Mälardalens University, Raluca Marinescu - Alstom, Ian Bird-Radolovic - Alstom Keywords: Safety-critical software development; Software development;Industry 4.0; Artificial Intelligence Purpose: The purpose of this study is to investigate what challenges and bottlenecks may occur in the development process of safety-critical software and suggest how Industry 4.0 technologies could be applied to overcome the bottlenecks and improve the process. Research questions: 1. What bottlenecks can the railway domain encounter when developing safety-critical software? 2. How can Industry 4.0 technologies be applied to overcome thebottlenecks and improve the development process of safety-critical software? Methodology: The study is based on a qualitative research methodology following an abductive approach. This led to the theoretical framework being gradually developed in parallel with the empirical data collection. The theoretical collection was based on scientific reports and books. The empirical data collection was based on a questionnaire, of which five in-depth interviews werethen conducted based on responses. Out of the five, three were semi-structured and two unstructured. Conclusion: The study concluded that all phases except design and implementation and software evaluation contained various bottlenecks related to tools, training, processes, resources and communication. However, it can be concluded that the testing phases were the biggest bottleneck at Alstom. To overcome testing challenges and improve the development process, the analysis shows that Industry 4.0 technologies such as AI, NLP and ML could be used to automate testing activities.

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