Manufacturing process improvement through technical solutions : a case study
Authors
Date
2021Copyright
This publication is copyrighted. You may download, display and print it for Your own personal use. Commercial use is prohibited.
The purpose of this exploratory thesis study is to observe a manufacturing process area in its current state and the opportunities to improve the process area by implementing Artificial Intelligence (AI), Machine Learning (ML) and other technical solutions in industrial manufacturing companies. The theoretical baseline is based on process management, process improvement solutions, AI, and ML. The research is centred around studying industry research and case studies with similar issues and goals as the case company. Data collection was conducted through interviews and observing current processes within the case company. The data was analyzed through compiling all the interview data to understand the current issues and determine the goal of the case company and then determine the best solution based on data and research. The empirical section explored how AI and ML can be implemented, managed, and evaluated for optimization in an industrial manufacturing context. Literature insights were compared with the results from my observations in the discussion section. The answer to the research questions, the limitations of the study, and future research questions are covered in the conclusion.
...


Keywords
Metadata
Show full item recordCollections
- Pro gradu -tutkielmat [23990]
Related items
Showing items with similar title or keywords.
-
Strategic cyber threat intelligence : Building the situational picture with emerging technologies
Voutilainen, Janne; Kari, Martti (Academic Conferences International, 2020)In 2019, e-criminals adopted new tactics to demand enormous ransoms from large organizations by using ransomware, a phenomenon known as “big game hunting.” Big game hunting is an excellent example of a sophisticated and ... -
Towards a Great Design of Conceptual Modelling
Kiyoki, Yasushi; Thalheim, Bernhard; Duží, Marie; Jaakkola, Hannu; Chawakitchareon, Petchporn; Heimbürger, Anneli (IOS Press, 2020)Humankind faces a most crucial mission; we must endeavour, on a global scale, to restore and improve our natural and social environments. This is a big challenge for global information systems development and for their ... -
Adversarial Attack’s Impact on Machine Learning Model in Cyber-Physical Systems
Vähäkainu, Petri; Lehto, Martti; Kariluoto, Antti (Peregrine Technical Solutions, 2020)Deficiency of correctly implemented and robust defence leaves Internet of Things devices vulnerable to cyber threats, such as adversarial attacks. A perpetrator can utilize adversarial examples when attacking Machine ... -
Artificial Intelligence for Cybersecurity : A Systematic Mapping of Literature
Wiafe, Isaac; Koranteng, Felix N.; Obeng, Emmanuel N.; Assyne, Nana; Wiafe, Abigail; Gulliver, Stephen R. (IEEE, 2020)Due to the ever-increasing complexities in cybercrimes, there is the need for cybersecurity methods to be more robust and intelligent. This will make defense mechanisms to be capable of making real-time decisions that can ... -
Sähköä ja alkemiaa : tekoälydiskurssit Yleisradion verkkoartikkeleissa
Slotte Dufva, Tomi; Mertala, Pekka (Media- ja viestintätieteellinen seura MEVI ry, 2021)Tässä artikkelissa tarkastelemme sitä, millaisena ja miten tekoäly esitetään suomalaisessa julkisessa keskustelussa, ja ketkä tekoälystä suurelle yleisölle kertovat. Aineistona olemme käyttäneet Yleisradion verkkosivujen ...