Feature-based Supervision of Shear Cutting Processes on the Basis of Force Measurements: Evaluation of Feature Engineering and Feature Extraction

Int J Adv Manuf Technol

2021

With the current tendency of mass production towards customer-oriented serial production, blanking processes are facing new challenges. They require an increase in knowledge about faulty process conditions and their influence on the quality of a component as well as an instruction for a target-oriented adaptation of the process. The aim of this study is therefore to identify property deviations based on force-displacement curves and to establish correlations between the quality of the component and features of force-displacement curves. For this purpose, parameter variations are carried out on a high-speed press and features are extracted from these measured time series. Afterwards, the correlation between varying process parameters and features is carried out to obtain a conclusion about the condition of the component. The results of these studies for a regression analysis form the basis for a decision support system to identify deviations of the component as well as faulty process conditions. The paper shows that a reliable correlation between the quality of the component and force-displacement curves is possibly based on the feature engineering approach even under industrial boundary conditions. This also applies to the simultaneous modification and variations within a limited range of several process parameters.

Section: Feature Engineeringmentioning

confidence: 99%

Section: Cutting Edge Radiimentioning

confidence: 99%

Section: Tensile Strengthmentioning

confidence: 99%

See 1 more Smart Citation

Exploitation of force displacement curves in blanking—feature engineering beyond defect detection

Kubik

Hohmann

Int J Adv Manuf Technol

2021

“…Moreover, the wide variety of machine-, tool-, material-and process-parameters and their mutual dependencies render it very difficult to compare the results of different process studies. [3,7,8] Fig. 2: Selection of process parameters that are most likely to influence the cutting surface parameters The influence of these process parameters, lack of an accurate prediction of material separation and rigidity requirements from the process also complicate the design and dimensioning of the stamping tool [9,8].…”

mentioning

confidence: 99%

“…al. [7] showed a comparison of engineered features and feature extraction. Hambli [25] trained a neural network with a large number of FE Simulation to predict the height of the burr.…”

mentioning

confidence: 99%

Towards Data Driven Stamping Process Modelling by Optical Inline Monitoring of Cutting Surface Parameters

Lorenz

Menzl

Donhauser

et al. 2021

Preprint

Stamping is a wide-spread production process, applied when massive amounts of the ever-same cheap parts are needed. For this reason, a highly efficient process is crucial. The cutting process is sensitive to a multitude of parameters. A process that is not correctly adjusted is subject to considerable wear and therefore not efficient. Unfortunately, the precise dependencies are often unknown. A prerequisite for optimal, reproducible and transparent process alignment is the knowledge of how exactly parameters influence the quality of a cutting part, which in turn requires a quantitative description of the quality of a part. A data driven approach allows to meet this challenge and quantify these influences. We developed an optical inline monitoring system, which consists of a image capturing, triangulation and image processing, that is capable of deriving quality metrics from 2D images and triangulation data of the cutting surface, directly inside the machine and without affecting the process. We identify features that can be automatically turned into quality metrics, like fraction of the burnish surface or the cut surface inclination. As an application, we show that the status of tool wear can be inferred by monitoring the burnish surface, with immediate consequences for predictive maintenance. Furthermore, we conclude that connecting machine and process parameters with quality metrics in real time for every single part enables data driven process modelling and ultimately the implementation of intelligent stamping machines.

Methods and Technologies for Mastering Uncertainty

Abele

Springer Tracts in Mechanical Engineering

et al. 2021

Uncertainty affects all phases of the product life cycle of technical systems, from design and production to their usage, even beyond the phase boundaries. Its identification, analysis and representation are discussed in the previous chapter. Based on the gained knowledge, our specific approach on mastering uncertainty can be applied. These approaches follow common strategies that are described in the subsequent chapter, but require individual methods and technologies. In this chapter, first legal and technical aspects for mastering uncertainty are discussed. Then, techniques for product design of technical systems under uncertainty are presented. The propagation of uncertainty is analysed for particular examples of process chains. Finally, semi-active and active technical systems and their relation to uncertainty are discussed.