Editorial
A Structured Methodology for Synthesizing Parameters and Architecture of Robotic Technological Systems in the Digital Transformation of SME Engineering Production
@ARTICLE{10.4108/dtip.9681, author={Ihor Yakovenko and Yevheniia Basova and Alexander Permyakov and Andrii Pokhil and Victor Sotnychenko and Lu\^{\i}s Freitas}, title={A Structured Methodology for Synthesizing Parameters and Architecture of Robotic Technological Systems in the Digital Transformation of SME Engineering Production}, journal={EAI Endorsed Transactions on Digital Transformation of Industrial Processes}, volume={1}, number={2}, publisher={EAI}, journal_a={DTIP}, year={2025}, month={8}, keywords={Robotic Automation, SME Engineering, Process Synthesis, Digital Transformation, Technological Systems, Workplace Design, Industry 4.0.}, doi={10.4108/dtip.9681} }- Ihor Yakovenko
Yevheniia Basova
Alexander Permyakov
Andrii Pokhil
Victor Sotnychenko
Luís Freitas
Year: 2025
A Structured Methodology for Synthesizing Parameters and Architecture of Robotic Technological Systems in the Digital Transformation of SME Engineering Production
DTIP
EAI
DOI: 10.4108/dtip.9681
Abstract
INTRODUCTION: Robotic automation has become a key driver of digital transformation in the engineering sector, especially for small and medium-sized enterprises (SMEs), which face increasing demands for flexibility, efficiency, and cost optimization. However, most classical automation frameworks do not address the structural and economic limitations specific to SMEs. Despite recent advances in modular automation, a gap remains in methodologies tailored to low-volume, high-mix environments typical of SMEs. OBJECTIVES: This paper aims to develop a structured methodology for synthesizing the parameters and architecture of robotic technological systems adapted to the production realities of SME engineering environments. The goal is to balance automation effectiveness with practical investment constraints. METHODS: The proposed approach integrates a multi-level automation model with production system analysis, considering object-specific constraints, part characteristics, and process parameters. The methodology was validated through an expert- and data-driven case study of a Ukrainian SME engaged in serial plastic part machining. Functional-cost analysis and feasibility modeling were used to evaluate automation options. In addition, investment-efficiency mapping was introduced to support strategic planning of implementation phases. RESULTS: The implementation of the proposed system, based on a six-axis robotic manipulator with digital control and vacuum clamping devices, led to a 50% reduction in auxiliary processing time, improved consistency, and reduced labor intensity. The workplace-level automation enabled flexible part handling without the need for major structural changes or high capital investment. The system demonstrated high adaptability to part variations and required minimal operator intervention. CONCLUSION: The developed methodology provides a scalable and economically viable path to robotic automation for SMEs. It supports gradual implementation and can be further enhanced by integrating artificial intelligence tools for decision-making during system design and optimization. This structured framework contributes to the digital resilience of SME manufacturing and aligns with Industry 4.0 principles.
Copyright © 2025 I. Yakovenko et al., licensed to EAI. This is an open access article distributed under the terms of the CC BY-NCSA 4.0, which permits copying, redistributing, remixing, transformation, and building upon the material in any medium so long as the original work is properly cited.
