Evaluation of AI-driven Generative Design and Redesign of a MINI-LINK Mounting Kit
Typ
Examensarbete för masterexamen
Master's Thesis
Master's Thesis
Program
Product development (MPPDE), MSc
Publicerad
2023
Författare
Alanko, Jim
Wallin, Mattias
Modellbyggare
Tidskriftstitel
ISSN
Volymtitel
Utgivare
Sammanfattning
This master’s thesis is a partial fulfillment for the degree of Master of Science in Product
Development and aimed to assess the viability of incorporating AI-driven generative design within
Ericsson’s mechanical design department. In this study, Ericsson’s specific needs and
requirements for generative design were explored and identified through a series of interviews and
a comprehensive user study. Subsequently, the identified needs were transformed into
benchmarking criteria for evaluating the capabilities of different software in performing generative
design or topology optimization. The primary objective of the benchmarking phase was to evaluate
the extent to which various software options aligned with the benchmarking criteria and their
proficiency in executing generative design or topology optimization tasks. Following evaluation
against the benchmarking criteria, PTC Creo Parametric emerged as the highest scoring software
and was consequently employed in the redesign of an existing mounting kit for a MINI-LINK
radio. The outcomes of the redesign phase revealed promising advancements in the form of
improved design that surpassed the performance of the pre-existing solution in terms of weight
reduction, increased stiffness, and a lower total cost. As the complexity of the model, load cases
and constraints increased in the redesign of the mounting kit, limitations with the current version
of Creo were revealed. A potential explanation is the difficulty to combine a generic method as
the contextual complexity and detail imposes specific constrains.
Concluding the thesis report, a revised and improved workflow proposal for product development
process within the mechanical design department was presented, in addition with the insights and
findings obtained throughout the study.
Beskrivning
Ämne/nyckelord
Artificial Intelligence, Benchmarking, Deep Learning, Generative Design, Needs Identification, Redesign, Topology Optimization