MANUFACTURING INNOVATION: COMBINING AUTOMATION AND DIGITAL SOLUTIONS TO GROW EFFICIENCY

EDN: YXCJGM

DOI: https://doi.org/10.65891/2949-1983-2026-22-1-5-8

Authors:

ALLAGULOV Rinat Khasanovich

Abstract.

The article investigates the integration of automation and digitalization as a key vector of production innovations aimed at increasing enterprise efficiency amidst intense market competition. Using structural functional and comparative analysis, the study identifies 7 key components for evaluating these processes: objective, technologies, outcome, business impact, task, scope of application, and coverage extent. The research includes tables that visually demonstrate the similarities and differences between automation and digitalization. The common features have been determined: a unified objective (efficiency enhancement), similar outcomes (cost reduction and quality improvement), and a shared business impact (competitiveness strengthening). The principal differences have been revealed across several dimensions: task (replacing manual labor versus creating smart management systems), scope of application (specific operations versus the entire production cycle), technologies (robots/PLC versus IoT/AI/Big Data), and coverage (narrow specialization versus comprehensive integration). The interconnection of the processes has been shown: automation serves as the technical foundation, while digitalization expands its capabilities through data and analytics, and their integration produces a synergistic effect. The paper provides practical implementation examples and illustrates real-world effects. Additionally, a development forecast within Industry 4.0 is offered, envisioning a transformation into “smart factories” managed via AI and IoT. The conclusion emphasizes that the joint implementation of automation and digitalization is essential for enhancing enterprise competitiveness and enabling adaptation to a rapidly changing market.

Keywords:

production innovations, automation, digitalization, Industry 4.0, IoT, artificial intelligence, production management, production efficiency

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