Operational Decision Support in Manufacturing and Technological Information Processing: A Systematic Literature Review

Abstract

The article is based on a systematic literature review on operational decision support in production and technological information processing. The content analysis aimed to examine how modern information processing systems are integrated into decision-making models in the context of production operations. The literature review follows the PRISMA method, designed to ensure transparent reporting of systematic reviews and meta-analyses. The article covers the following stages: literature search, thematic selection, and quantitative and qualitative analysis of the collected literature. Based on the bibliometric analysis, the literature can be divided into three interrelated thematic areas. The first thematic area concerns operational decision support in production planning, scheduling, capacity allocation, and production control. The second thematic area refers to technological information processing, including the representation of process knowledge through CAD model integration and the interpretation of technical documentation. The third thematic area focuses on tools that have gained increasing importance in recent years in the broadly understood industrial sector: machine learning, digital twins, and Industry 4.0 infrastructure. The literature analysis indicates that a major research gap lies not in the absence of individual decision-support methods, but in the limited integration of operational and technological information within coherent models supporting decision-making under real manufacturing conditions.