Modelling human errors and quality issues in kitting processes for assembly lines feeding

In this paper a quantitative model is developed to assess errors probability and errors correction costs in kit preparation and delivery processes feeding parts to assembly lines. Error trees and event trees are adopted to keep track of unwanted events and error correction opportunities during the entire logistic process, starting from material picking in the warehouse to kit delivery at workstations and parts assembly. A numerical example is included to show the method application and assess the contribution of each potential error to the overall quality cost in kitting systems. The method is aimed at quantifying the economic consequences of errors in the parts feeding logistic process, and identifying the major error sources. This allows to better compare kitting systems to alternative parts feeding policies and identify corrective measures.