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This study bridges the gap in quality control strategies for high-volume production by balancing the cost and effectiveness of inspection strategies. Using the cost of quality (CoQ) to manage cost and external failures (EF) to gauge effectiveness, this research introduces an innovative inspection strategy chart that serves as a decision-making tool for optimizing inspection processes.

This paper presents a scenario-based framework designed to support strategic decision-making in inspection processes by integrating empirical data analysis with inspection strategy charts. This approach allows for a dynamic assessment and visualization of the relationship between CoQ and EF, facilitating more informed decision-making in quality management. Notably, it contrasts the traditional models with a novel approach that more accurately captures the uncertainty and correlation among key quality indicators, showcasing its potential for more refined decision-making in quality management.

Application of the framework illustrates its effectiveness in offering a nuanced understanding of the cost implications and effectiveness of various quality control strategies. This facilitates enhanced strategic decision-making, optimizing inspection processes and reducing external failures in high-volume production settings.

The study focuses on a single industry case study, limiting the generalizability of findings across different high-volume production contexts. Future research could explore the framework’s applicability in other sectors and refine the model based on additional empirical data.

The research introduces a versatile framework that navigates the unique challenges of high-volume manufacturing environments. Diverging from models optimized for low-volume settings, this approach provides a valuable tool for adapting inspection strategies to complex production demands, marking a significant contribution to quality management and control literature.

This paper proposes an evaluation approach for analyzing excellence management practices at a regional level based on experts’ assessment.

Using the National Quality Foundation’s Management Excellence Model (MEG), 19 management excellence practices were identified and tailored for small- and medium-sized industries (SMIs). Data were collected through a survey with 25 experts who assessed these practices in the context of Brazilian manufacturing SMIs. The analysis utilized Fuzzy TOPSIS Class (FTC), and a sensitivity analysis was also conducted.

The proposed evaluation approach integrates a reference model for management excellence (MEG), an analysis method incorporating uncertainty (FTC), and results that enable decision-makers to make well-informed choices. Of the 19 practices assessed, 15 were classified as “unacceptable,” while four were rated as “regular,” and none as “expected.” Key challenges relate to practices in information security, knowledge, innovation and change management.

The study’s primary limitation is the use of non-probabilistic sampling and its focus on the Brazilian context. However, the extensive knowledge and experience of the experts in manufacturing SMIs and the need for studies addressing specific regional contexts should be noted.

The findings reveal a significant gap between ideal management practices and the actual state of SMIs, especially in emerging markets.

This research introduces a novel approach that combines a reference model tailored for SMIs with a multicriteria decision-making method, offering valuable insights for decision-makers and guiding future research.