An economic evaluation for implementation of Zero Defects and Zero Waste inspection solution in the Wind Energy manufacturing industry

Current research aims to evaluate the return on investment for different automated inspection solutions based on selected features and incorporate this eval-uation methodology in the multistage investment decision process. Hardware, da-taset acquisition, and machining learning training costs are important variables in estimating the cost of automatic painting inspection equipment. This paper proposes a methodology to calculate and analyse the return on investment of an automatic visual inspection solution for painting inspection. The proposed method shows the influence of hardware selection on the inspection equipment cost, inspection cycle time, inspection cost and economic feasibility. The performance of automatic vision systems is influenced by the robustness, accuracy and time efficiency in the defect detection process; this article covers these topics and provides an early use case for painting inspection solutions. The paper remarks on the importance of inspection cost based on the inspection machine, analysing the return on investment based on the technical features selected.