DIGITAL TRANSFORMATION IN THE FOOD INDUSTRY: CONCEPTUAL APPROACHES TO DATA-DRIVEN QUALITY AND SAFETY MANAGEMENT

Abstract

This article examines the comprehensive impact of digital transformation on the structure of engineering and technological processes in the food industry and the principles of operational flow management. The relevance of this work stems from the active transition of processing enterprises toward the fourth and fifth industrial revolutions (Food Industry 4.0/5.0), which requires a reevaluation of traditional methods for controlling environmental parameters. The article analyzes modern tools of the Industrial Internet of Things (IIoT), intelligent sensor networks, computer vision systems, and predictive analytics, which are being implemented on production lines to stabilize the conditions of finished products. It is shown that the automation of a modern processing plant transforms the traditional functions of a process engineer, shifting the focus from the routine recording of instrument readings to the analysis of dynamic time series, working with digital log files, and SCADA interfaces.
The methodological basis of the study consists of systemic, technological, and integrative engineering approaches, as well as methods of structural-logical modeling and conceptual synthesis of food system parameters. The scientific novelty of the work lies in the development and justification of an end-to-end conceptual model: “technological foundation – digital tool – data – decision – safety – quality – responsibility.” This model is the first to integrate the physical and chemical principles of raw material processing with higher-level enterprise automation systems (MES/ERP), algorithms for verifying critical control points in the HACCP system, and procedures for digital traceability of batches.
Within the proposed architecture, seven integrated clusters of engineering and technological functions have been structured: technological-process, digital-analytical, quality-safety, traceability-regulatory, engineering-sensor, innovation-design, and system-responsibility. The organizational and technological conditions for building reliable digital control loops have been defined, including requirements for the validation of primary sensor data, the protection of process control system (PCS) information networks, and the evaluation of line efficiency using the OEE metric. The practical significance of the research results lies in the possibility of using them to modernize existing production facilities, automate laboratory control using LIMS systems, and implement computational fluid dynamics (CFD) during the design of new high-efficiency food processing equipment.