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Seven student thesis works at bachelors’ and masters’ levels were completed during the AHIL project based on a close collaboration and co-production with industry partners. The student thesis covered different areas such as industrial engineering, informatics, leadership, and production logistics with simulation and machine learning.
This thesis project was carried out with the aim of creating an understanding of how production flow simulation can be used as a sustainable activity to plan production and achieve more efficient planning at Siemens Industrial Turbomachinery AB in Trollhättan. Based on the results that focused on outlining the production flow, a conceptual simulation model was built that visualizes the production, which is a starting point for further development and use of production flow simulations. It was concluded that the data collection aspects and its analysis were of large importance for preparation of building the model. It is of great value to have good insight into the production flow of the company and the conclusion stresses the importance of a detailed study of the production flow and to understand the production data before deciding on whether a simulation model should be built and the scoop of that model.
Master thesis 15 hp in Informatics, University West
Manufacturing industries are today changing faster and faster due to digitalisation and Industry 4.0. Digitalisation has changed the business environment by integrating business and engineering processes, enabling companies to become more dynamic and connected and inherently more complex and dependent on information technology. Furthermore, Industry 4.0 continually changed manufacturing industries since its iteration, with recent advances showcasing the potential of these technologies to assist manufacturers in tackling the challenges associated with the digital transformation. With five qualitative interviews with business professionals in manufacturing industries in addition to a literature review covering 14 articles, this research aimed to identify challenges and opportunities between Industry 4.0 initiatives and IT departments. The research found the increased need for research regarding IT departments roles in Industry 4.0 implementations and how IT departments are defined in organisations today. It found that organisations spread the digital competencies rather than having the IT department as the sole entity for digitalisation. In addition to other areas of interest regarding Industry 4.0 implementation like enabling technologies and the focus on maturity and digital readiness for organisations.
Nyberg, E. (2021). Modelling of production flow at Siemens Energy: Digital Twin with a view towards real time data implementation. Master thesis 30hp, Master Programme in Robotics, University West
The background for this thesis stems from a wish to move the production a step further towards Industry 4.0 at Siemens Energy Trollhättan. They wish to start making this journey by researching the possibilities of simulating their production flows and extending that simulation into a Digital Twin, with alarms helping to optimise their production. In this thesis, the focus will lie on the Digital Twin towards implementation of Real Time Data. Although no clear solution for the task of implementing Real time with a simulation was reached within the timeframe of this degree work, a solid understanding of what needs to be further researched and implemented has to be summed up in the thesis.
Nilsson, K., & Skytt, F. (2021). Hållbar mänsklig utveckling inom industrin: Den fjärde industriella revolutionens nya krav på människan. Kandidatuppsats, 15 hp, Examensarbete i informatik, Högskolan Väst
The purpose of this study is to investigate a well-established industry in the energy sector on how people view competence development, work integrated learning (WIL) and lifelong learning. The purpose is also to investigate how people can grow in an industrial transformation, from a human sustainability perspective towards industry 4.0. The three themes (competence development, WIL and lifelong learning) were posed in statements related to Industry 4.0 and the nine pillars. The nine pillars are Big data, Augmented reality(AR), Cloud services, Simulations, Internet of Things (IoT), 3D-Printing, Autonomous robots, IT-security and Vertical and Horizontal system integration. To answer our research questions, we use quantitative method in the format of surveys. The surveys are sent out to employees of an anonymous industry. Out of the 30 employees, 21 replied to the survey. The main findings of the results in the study show a pattern through three of nine pillars in industry 4.0, IT-security, cloud services and 3D-Printing of all the statements made in the survey. The pattern shows that the industry is currently working with these three. Furthermore, results correlate within all themes in the three pillars (IT-security, cloud services and 3D-Printing) where a majority of the respondents are positive about developing their competence further (competence development), and the combination of theory with practice (WIL) and openness but also motivation for learning (lifelong learning). Another finding was that WIL received only a majority in the three pillars that the industry based on the results of the study suggesting is in use at the present time, unlike the other two themes. Competence development showed a majority of six out of nine pillars and lifelong learning showed a majority of eight out of nine pillars. The conclusion based on the study's questions shows that in order for people to be able to participate in industrial transformation may competence development, WIL and lifelong learning become something of a must in order to achieve human sustainable development. The conclusion also shows that those people in the industry to a greater extent show motivation. The study shows how an industry can respond to rapid industrial development. The conclusion indicates that the people within it seem to be open to take steps forward into the new industrial era. The conclusion also shows that it is not possible to make a clear conclusion because the study was not large enough. This study proposes for the industry on how a transformation towards industry 4.0 can be humanly sustainable.
Hansson, N. (2021). Modelling of production flow at Siemens Energy: Digital twin with plans toward statistical process control. Master thesis 30hp, Master Programme in Robotics, University West
The reason for this thesis’ initialisation was that Siemens Energy Trollhättan wanted to take their manufacturing production a step further into Industry 4.0. This process was to begin with a simulated model of part of their factory being built, which could then later be turned into part of a Digital twin with an alarm functionality that could help optimise production. This thesis will focus on these first steps taken to have a Digital twin of the factory, made together with a theoretical research part regarding how this alarm functionality can be realized. A solution found by the author was sending data from the program Plant Simulation to the computational platform MATLAB, wherein statistical process control is utilised to trigger an alarm when the monitored mean goes beyond acceptable limits. A solution for implementing the requested alarm has been researched and a concept of how this would be extended is outlined in this thesis, though the implementation of the solution itself fell outside of the timeframe of this degree work.
Moskalenko, V. (2022). Discrete event simulation of production flow at Siemens energy - With focus on decision support system for statistical process control considering AI, Master Thesis 30hp, Master Programme in Robotics, University West
Optimisation of the production workflow is a complicated task, since it is nearly impossible for a person to predict bottlenecks and rising cycle times. Discrete event simulations are built with a purpose of monitoring and predicting such problems occurring. But all information from simulations should be analysed by a final user. In order to create a process for prediction and optimization two automated methods were developed in this project. The first method utilizes statistical methods for monitoring separate stations. The second method is using machine learning methods for analysing the whole simulation at once to investigate... machine learning algorithms should be able to tell if there will be issues in the station. Such as growing cycle times, buffer overfilling, bottlenecks. The developed software performs and utilizes statistical and data analytical methods for monitoring and predicting such problems encountered in the workflow as growing cycle times, growing variance, process out of control, bottlenecks.
Gholam, S & Basaran, D. (2022). Ett medarbetarperspektiv på ledarskap: En kvalitativ studie inom tillverkningsindustrin. Kandidatuppsats 15hp i företagsekonomi, Ekonomprogrammet, Högskolan Väst.
Today, organizations are constantly on the move and changes can happen quickly. Extensive, revolutionary changes can occur in the manufacturing industry. Employees in today's organizations are also experiencing constant changes and therefore co-workership is a major component, especially when it comes to Scandinavian working life. For organizations to develop, leadership is another important component. This study is based on an industrial context as the manufacturing industry is undergoing a fourth industrial revolution, which affects the entire organization. The theoretical frame of reference presents previous research on the study's key concepts, and different models that are relevant to the study are presented. Given that the purpose of this study is to study the interaction between employees and management within the chosen organization, but also to analyze what leadership styles are needed in the industry, it is of interest to analyze whether some leadership styles are more appropriate than others to develop the organization. Based on the purpose and the two research questions that have been presented, a qualitative method has been considered to be most suitable for the data collection. The qualitative method techniques that have been applied, have been in the form of semi-structured in-depth interviews and through participation in two focus groups. An interpretive perspective in the form of a hermeneutic approach has been chosen in this study, in order to create a deeper understanding of the interaction between employees and management. By analyzing the empirics in connection with the theory, a conclusion can be drawn that a combination of a team-oriented and a reasonably-oriented leadership style needs to be applied within the studied organization.