An ANN parametric approach for the estimation of total production operation time

Abstract

Total production time (TPT) is typically an essential component for calculating the total production cost (TPC) in production operations. In job shop facilities, the precise classical calculations of the TPT of a single workpiece or a small batch are too complicated and expensive because of the large variations. The typical solution of this problem is to rely on experts estimations. In this paper, a new estimation method based on an artificial neural network (ANN) is introduced for the assessment of the TPT. This estimator relies on feeding the ANN with a set of workpiece and cutting operation parameters. The TPT outputs from the estimator are compared with collected experts’ estimations, both with reference to the referential accurate operations sheet values. The results of the proposed approach are found to be closer to the referential values by a significant percentage. The developed model is versatile, simple and has shorter execution time.

Keywords

• Cost estimation
• Total production time
• Artificial neural networks
• Turning