Measuring Final Inspectors’ Discrimination Ability of Metal Structures in the Automotive Industry

Purpose – The main objective of this paper is to present an approach for understanding the discrimination ability of the operators responsible for the final inspection at a metal structures’ production line in the automotive industry. Another important goal is to show how this type of analysis can help to improve the way quality inspectors carry out their daily activities.
Design/methodology/approach – The methodology followed consisted in selecting a sample of 30 metal structures (15 conforming and 15 non-conforming), over a time period of two months, and then asking 10 quality inspectors to classify each of the structures. Afterwards the performance of the inspectors was analysed using Receiver Operating Characteristic (ROC) Analysis.
Findings – The results indicate that inspectors are generally working efficiently and also that there is a low risk of rejecting conforming parts and of accepting non-conforming ones. These risks depend on the inspector that judges the structure so the differences between their individual performances were analysed. Improvement actions were then recommended and implemented.
Research implications – The work presented is an exploratory study and reports on the results of the proposed approach that underline the possibility of quantifying the discrimination ability of inspectors in industrial environments.
Practical implications – The quantification of the inspectors’ performances of the company was completed. Afterwards, it was possible to plan and implement improvement actions regarding those performances. All the inspectors, as well as the production line responsible, felt comfortable with the results.
Originality/value – As the approach used has not been addressed by scientific literature, it is considered that the outcomes of the work are valuable for researchers on quality evaluation of inspectors. Additionally, this study may help practitioners implement the proposed method in other environments.

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Quality assessment, Inspection, Automotive industry, ROC Analysis.