Technical Journal, Vol. 18 No. 3, 2024.
Original scientific paper
https://doi.org/10.31803/tg-20240513233046
A Maturity Model to Determine the Degree of Utilization of Machine Learning in Production Planning and Control Processes
Jakob Hartl
; Technische Hochschule Ingolstadt, Esplanade 10, D-85049 Ingolstadt, Germany
Jürgen Bock
orcid.org/0000-0002-1210-1576
; Technische Hochschule Ingolstadt, Esplanade 10, D-85049 Ingolstadt, Germany
*
* Corresponding author.
Abstract
The presented work introduces a maturity model for evaluating Machine Learning implementations, with a primary focus on Production Planning and Control processes, as well as broader organizational and technical aspects in companies. This model emerges as a response to the research gap identified in the analysis of 14 existing maturity models, which served as foundational bases for the development of this novel approach. By examining success factors and obstacles at different maturity levels, categorized according to defined dimensions and overarching design fields, this model can serve as a catalyst for bridging the research gap between models demanded in practice and the scholary exploration of topics related to Machine Learning in corporate processes. Notably, the structured design of this maturity model ensures accessibility for small and medium-sized enterprises (SMEs).
Keywords
machine learning; maturity model; production planning and control; project success; SME; success factors
Hrčak ID:
319184
URI
Publication date:
5.9.2024.
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