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Manufacturing process improvement through technical solutions : a case study

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Authors
Sillanpää, Kristiina
Date
2021
Discipline
TietojärjestelmätiedeInformation Systems Science
Copyright
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
optimization lead time data management tietojenkäsittely prosessit koneoppiminen tekoäly data processing processes machine learning artificial intelligence
URI

http://urn.fi/URN:NBN:fi:jyu-202106173835

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