## Appendix A  
Glossary of used terms in alphabetical order:  
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2. _A_: _A  
cators, helping to optimize operational efficiency and align warranty policies with the organization's goals. * Big Data: A set of massive and complex data that cannot be processed by traditional methods and is used to make decisions based on real-time data. * Cloud Computing: Technology that allows remote access to computing services through the cloud, optimizing data storage and processing. * Computer Aided Maintenance Management (CMMS): Software that automates work order management and asset maintenance, improving operational efficiency. * Computer-Assisted Maintenance Management System (CMMS): Software that centralizes maintenance management, optimizing the planning and execution of tasks. In warranty management, CMMSs allow for customizing warranty policies and using historical and real-time data to implement predictive maintenance that minimizes corrective interventions. * Condition-Based Maintenance (CBM): Maintenance strategy based on the actual condition of assets, monitored by sensors and IoT technologies. In the context of warranties, CBM allows maintenance policies to be adjusted according to the condition of the asset, reducing downtime and adapting warranty coverage to its operational status. * Criticality Analysis: Evaluation process that prioritizes the maintenance of the most important assets according to their impact on operations. * CRM (Customer Relationship Management): A system that manages customer relationships, facilitating the personalization of aftersales services. In warranty management, CRM allows the analysis of customer behavior and the adaptation of warranty policies to their needs, improving customer satisfaction and loyalty [71]. * Cybersecurity: Set of practices that protect networks, systems, and data from cyberattacks and threats. * Deep Learning: A subfield of artificial intelligence (AI) and machine learning that uses multi-layered (or \"deep\") artificial neural networks to model and learn complex patterns in large datasets. * Digital Enabler: Refers to any technology, tool, or digital system that facilitates the transformation of processes, products, or services in an organization through automation, connectivity, and data analysis. * Digital Servitization: This is a business model that uses advanced technologies (AI, IoT) to offer additional services around physical products. It is closely related to aftersales and warranty management, personalizing services based on asset use and optimizing maintenance cycles. * Digital Transformation: Process of integrating digital technologies into all areas of a company to improve its efficiency and added value. * Digital Twins: Virtual model of a physical asset that simulates its behavior in real time under different conditions. * Digitization: Process of converting physical information into digital formats, allowing analysis through information technologies. * Dynamics 365: Microsoft's platform for CRM and ERP. * Edge Computing: Processing data close to where they are generated, rather than sending data to the cloud, reducing latency. * e-Warranty: Digital warranty management system that improves the traceability and personalization of coverage policies, adapting them to the customer's usage data. * Enterprise Asset Management (EAM): A comprehensive system for managing enterprise assets that enables assets' performance to be maximized and their useful life to be extended. * Gurobi: Optimization tool. * Industry 4.0: Industrial revolution that involves the integration of IoT, AI, and big data in industrial processes to create smart factories. * Internet of Things (IoT): A network of interconnected devices that collect and share real-time data to improve asset management. * IoT Platform: Software that manages the connectivity and analysis of data generated by connected IoT devices in real time. * ISO 55000: International standard that establishes the requirements for an efficient and sustainable asset management system.