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Performance Paradox: High Maintenance Expectations Versus Low Technological Investment in Industrial Enterprises Cover

Performance Paradox: High Maintenance Expectations Versus Low Technological Investment in Industrial Enterprises

Open Access
|Dec 2025

Abstract

This study investigates the current state of maintenance practices, performance evaluation methodologies, and the adoption of digital management systems within industrial organizations in Sibiu County, Romania. The primary objective was to empirically quantify the gap between the perceived strategic importance of maintenance and the practical maturity of its implementation. A quantitative, non-experimental survey design was utilized. Data was collected from a convenience sample of 104 professionals across various industrial sectors, with a significant representation from the automotive industry. The survey instrument assessed organizational demographics, maintenance strategy prevalence (Corrective, Preventive, Predictive), perceived impact on productivity and quality, and the use of specialized management software (CMMS/ERP). Data analysis employed descriptive statistics and cross-tabulations. Results confirmed the high strategic value of maintenance, with over 70% of respondents reporting a strong influence on product quality and productivity. However, the study revealed a significant technological disparity: while Preventive Maintenance (44.2%) was the most common strategy, a substantial portion of organizations (34.6%) reported operating without any specialized CMMS or ERP system for maintenance management. Furthermore, the adoption of advanced Predictive Maintenance was minimal. A critical gap exists between the recognized strategic role of maintenance and the operational maturity of the sector. The lack of integrated digital infrastructure hinders the adoption of advanced, data-driven strategies and limits the ability to accurately measure and benchmark performance through holistic KPIs. Bridging this gap requires strategic investment in both digital systems and specialized personnel training to transition the sector toward truly predictive and efficient maintenance models.

DOI: https://doi.org/10.2478/aucts-2025-0004 | Journal eISSN: 2668-6449 | Journal ISSN: 1583-7149
Language: English
Page range: 27 - 36
Published on: Dec 31, 2025
In partnership with: Paradigm Publishing Services
Publication frequency: 1 issue per year

© 2025 Valentin Grecu, Călin, Deneş, published by Lucian Blaga University of Sibiu
This work is licensed under the Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 License.