Assembly Time Standard Setting Based on Kernel Estimators

Time standards belong to vital indicators of the production process that facilitate making decisions related to product and process improvement. The presented issues concern the determination of the assembly time standard using kernel estimators. The development of neural networks offers the possibility to identify begin-end points in the assembly process that can provide big data related to the assembly time standard. The problem addressed in this paper is development of a method of big data analysis, on the basis of which the assembly time standard can be determined. In the presented approach adequate formulas are developed together with some examples. The paper presents an application of the theory of kernel estimators as well as results of the proposed approach.