Publication
Collaborative exploitation of various AI methods in adaptive assembly assistance systems
Stefan-Alexandru Precup; Alexandru Matei; Snehal Walunj; Arpad Gellert; Christiane Plociennik; Constantin-Bala Zamfirescu
In: Tenth International Conference on Information Technology and Quantitative Management (ITQM 2023). International Conference on Information Technology and Quantitative Management (ITQM-2023), August 12-14, Oxford, United Kingdom, Pages 1170-1177, Procedia Computer Science, Vol. 221, Elsevier B.V, 8/2023.
Abstract
A great challenge in applying AI to specific problems in the industry is to select the proper method when multiple methods are available. In this paper, we intend to address this issue with various AI methods in the context of adaptive assembly assistance systems. The paper is a synthesis that discusses and highlights advantages and disadvantages, applicability, and recommendations for several AI-based methods. For illustration, we present the methods applied to provide choices for the next assembly step in the context of a highly customizable and modular tablet used as a target product. To choose the algorithm that best suits the needs of a specific working environment, we present an approach to consider several criteria weighted based on their importance based on the needs and resources of the use case. The Hidden Markov Model fulfilled our criteria with the highest score and is the selected prediction method for integration into the assembly assistance system.