# Evaluation of the Barriers to Maintenance 4.0 for the Textile Industry via Pythagorean Fuzzy SWARA
## 1 Introduction  
Maintenance 4.0, as an important part of the digital transformation in the textile industry, plays a critical role in increasing the efficiency and sustainability of production processes. Thanks to the integration of technologies such as the Internet of Things (IoT), big data analytics, and artificial intelligence, machine failures can be predicted in advance, and unplanned downtimes are minimized. This both reduces production costs and increases competitiveness by increasing quality. It also contributes to environmental sustainability, with positive effects on energy consumption and resource use. In a sector such as textiles, which requires intensive machine use, Maintenance 4.0 applications offer a strategic advantage in terms of production continuity and business performance. The concepts of sustainability and digitalization are encountered in the manufacturing industry, as in every field. The optimum use of limited resources has become one of the most fundamental policies of nations, countries, and companies. While businesses develop production and management policies that consider sustainability in terms of environmental and social impacts and sustainability, they are trying to lay the foundations of Industry 4.0 with digitalization [1; 2]. Industry 4.0 has entered our lives with the application of digital technologies such as the Internet of Things (IoT), cyber-physical systems (CPS), artificial intelligence (AI), virtual reality (VR), augmented reality (AR), and big data analysis (BDA) in the manufacturing sector [3; 4; 5]. Ensuring the continuity of production activities without interruptions or delays is of critical importance. The advent of Industry 4.0 technologies has necessitated the adoption of innovative approaches to maintenance operations. Maintenance 4.0 aims to enable failure prediction, optimize resource utilization, and establish continuously improving maintenance systems [6; 7]. Survival in a highly competitive environment is closely linked to the uninterrupted operation of production processes. An effective maintenance policy enables cost-effective production and enhances customer satisfaction without compromising quality or quantity [8]. Maintenance 4.0 applications--where physical systems are synchronized with the virtual world through the integration of computers and technological devices--are a subset of Industry 4.0. These applications involve automated data collection, data analysis, and intelligent decision-making systems [1; 9]. In today's volatile and uncertain market environment, implementing a technically and administratively sound maintenance plan and management strategy is a highly complex process for businesses. Such a long-term strategic plan supports businesses in addressing the economic, environmental, and social dimensions underpinning the principle of sustainability [10; 11; 12]. The periodic maintenance of machines is a critical factor across all industries. It ensures the optimal functioning of machinery and equipment, minimizes the risk of unexpected downtime and emergency repairs, reduces workplace accident risks, extends the lifespan of assets, and ensures compliance with safety and environmental standards. These goals are achieved through regular inspections, preventive and corrective actions, part replacements, and adjustments [13; 14]. A substantial contribution to operational excellence can be achieved through the strategic integration of various maintenance approaches, including corrective, preventive, predictive, autonomous maintenance, and focused improvement initiatives. Corrective maintenance refers to the maintenance activities undertaken when a machine, component, equipment, or system experiences a malfunction. Its primary objective is to restore the affected asset to its normal operational condition. As the machine or system ceases to operate, it necessitates immediate intervention, often leading to increased maintenance and downtime-related costs.