QUALITY COST MANAGEMENT: THEORETICAL FOUNDATIONS, CLASSIFICATION MODELS, AND CONTRIBUTIONS TO STRATEGIC DECISION MAKING

Abstract

Increasing global competitiveness has required organizations not only to offer high-quality products and services but also to strictly control the costs involved in this process. In this context, quality cost management emerges as a strategic tool capable of aligning investments in prevention and evaluation with the reduction of internal and external defects, directly impacting profitability and customer satisfaction. This article aims to systematize the theoretical foundations of quality costs, analyze the main classification models (Prevention, Appraisal, Failures (PAF), Crosby, ABC, Variable Costing), and discuss their application as a tool for managerial decision-making, with an emphasis on the transformations brought about by Industry 4.0. The methodology consists of a systematic review of national and international literature, based on classic authors (Juran, Feigenbaum, Crosby) and recent applied studies. The results indicate that the PAF model is the most widely used, but it has limitations regarding the measurement of intangible costs and the allocation of indirect costs. Integration with Industry 4.0 technologies—such as IoT, computer vision, predictive maintenance, and QMS systems—redefines the nature of prevention and evaluation costs, transforming them into strategic investments with a measurable return in the form of reduced failures. It is concluded that managing quality costs in connected manufacturing requires not only the reconfiguration of costing systems but also the consolidation of a new organizational culture guided by data and real-time decision-making.