A Fuzzy SERVQUAL-Based QFD Framework for Enhancing Calibration Services in a Regional Metrology Laboratory

Abstract

Calibration laboratories operate within technically demanding and highly regulated environments, where service quality is shaped not only by measurement accuracy but also by customers’ service experiences. Traditional service quality assessment approaches often struggle to capture the uncertainty and subjectivity inherent in customer and expert evaluations, particularly in technical services. This study proposes an integrated fuzzy SERVQUAL-based Quality Function Deployment (QFD) framework for improving calibration services in a regional metrology laboratory. A perception-based SERVQUAL instrument is employed to identify and weight customer requirements across the five SERVQUAL dimensions using triangular fuzzy numbers. These fuzzy importance weights are subsequently deployed into a fuzzy House of Quality to prioritize technical improvement actions aligned with ISO/IEC 17025 requirements.

The proposed framework enables the systematic translation of customer perceptions into prioritized technical requirements while explicitly accounting for uncertainty in both customer feedback and expert judgments. By integrating fuzzy logic with SERVQUAL dimensions and QFD, the study provides a transparent and defensible decision-support tool for calibration laboratories seeking to enhance service quality, support risk-based thinking, and guide continuous improvement initiatives. The framework is designed to be replicable and adaptable to other technical service environments governed by quality management standards.