Diagnosing Extrusion Process Based on Displacement Signal and Simple Decision Tree Classifier.

Grzegorz Piecuch,Rafał Żyła

doi:10.3390/s22010379

Abstract

The article presents an extensive analysis of the literature related to the diagnosis of the extrusion process and proposes a new, unique method. This method is based on the observation of the punch displacement signal in relation to the die, and then approximation of this signal using a polynomial. It is difficult to find in the literature even an attempt to solve the problem of diagnosing the extrusion process by means of a simple distance measurement. The dominant feature is the use of strain gauges, force sensors or even accelerometers. However, the authors managed to use the displacement signal, and it was considered a key element of the method presented in the article. The aim of the authors was to propose an effective method, simple to implement and not requiring high computing power, with the possibility of acting and making decisions in real time. At the input of the classifier, authors provided the determined polynomial coefficients and the SSE (Sum of Squared Errors) value. Based on the SSE values only, the decision tree algorithm performed anomaly detection with an accuracy of 98.36%. With regard to the duration of the experiment (single extrusion process), the decision was made after 0.44 s, which is on average 26.7% of the extrusion experiment duration. The article describes in detail the method and the results achieved.

Highlights

In line with the idea of industry 4.0, one should strive for increasing digitization, diagnosing processes, predicting failures and reducing the number of defects, etc
The authors present a novelty diagnostic method for extrusion process, with displacement signal as the unique value, while the algorithm based on polynomial approximation complements the proposed method
The structure of the classifier was built on the decision tree model (CART)

Summary

Introduction

In line with the idea of industry 4.0, one should strive for increasing digitization, diagnosing processes, predicting failures and reducing the number of defects, etc. This idea is implemented to a different extent in various industries—one of such industries where more and more emphasis is placed on the use of new technologies in production are the automotive and aviation industries. The quality of the produced details (product or semifinished product) and minimizing errors is a key issue In these industries, we deal mainly with machining processes (milling, turning, grinding), casting, thermal processes, etc. The authors did not find solutions in the literature that use displacement sensor for the extrusion process diagnosis. The main aim of this publication was to utilize a displacement sensor in a new and real application

Methods

Results

Discussion

Conclusion