AI-enabled automation for SMEs : prerequisites and opportunities for implementation and operation
Year: 2024
Type: dissertation
Abstract: Larger companies have adapted industry 4.0 and it’s benefits while SMEs still face significant barriers such as limited resources and knowledge gaps. By exploring AI implementation, this research aims to provide insight into the suitability and prerequisites for implementation of various AI solutions in automation on manufacturing SMEs, helping them overcome these challenges and remain competitive on the market. To answer the questions a literature review was conducted followed by two case studies at manufacturing SMEs. The case studies involved semi-instructed interviews and observations at site. The information gained was used to analyse and acquire relevant conclusions. The analysis highlights factors affecting AI implementation in manufacturing systems, such as data quality, economic resources, competence development, manager support etcetera are mentioned. Additionally, methods for AI implementation, including ML cloud computing, robotics and Decision support system are discussed. Furthermore, the case studies illustrate exemplify the challenges and aspirations of SMEs in adopting AI, showcasing their varying levels of readiness and approaches towards automation and IT integration. The result show that the lack of competence is a major barrier for SMEs in AI implementation. Both companies recognize the need to digitalize to remain competitive in the market. It is also shown that AI implementation requires the right expertise and support from management to succeed. SMEs also need to start collecting relevant data since it is an identified prerequisite for implementation. This study implies to manufacturing SMEs and how they can implement AI, identifying their needs. It also implies to AI developers that want to create SME-specific tools and helps consultants provide SMEs with accurate advice. The discussion highlights that SMEs are not yet ready for huge AI technology since they lack many of the previously mentioned prerequisites. They should however start with implementing other technology from industry 4.0 since they are highly needed to become more digitalized. The methodology is also discussed and talked about how a triangulation method was used and can help to strengthen the quality of this research.
Authors: Lindqvist, Moa, Andersson Bertilsson, William
Language: English
Subfield: Industrial and Manufacturing Engineering
Field: Engineering
Domain: Physical Sciences
Open Access status: green
OpenAlex ID: W7081548740