The paper presents an experimental evaluation of deformation of flat samples during uniaxial tensile testing, including uniform deformation and post-necking phases. The authors recommend a specially designed vision extensometer and simplified image processing method for analytical correction of triaxial test results for extended stress–strain curve estimation. A modified correction model is proposed, based on the application of Gaussian functions, to determine the neck geometry of the tested sample. The vision extensometer can monitor a specimen’s elongation using two fibre-optic gauges inserted into the material. Measurements taken from the vision extensometer are compared with readings from analogue gauges within the range of uniform deformation. The analytical correction model’s ability to correctly assess the extended true stress–strain curve in the post-necking phase was investigated. Image processing forms the basis of an efficient method for identifying the contour of the specimen’s neck. Digital image correlation (DIC) was used to verify the proposed solutions and assess the results obtained for the uniform and post-neck deformation phases. The change in thickness of the sample was experimentally measured throughout the tensile test with a digital gauge sensor and compared with the results of the digital image correlation.

A new method and optical system have been developed to measure the strain distribution in sheet metal bending. The method relies on a simple pattern, i.e., a single line of certain width, or an area having a boundary line, marked on the sheet before deformation. The line traverses a width of the sheet metal at an angle. The sheet metal is deformed and an equivalent two-dimensional image of the line after deformation is obtained. By comparing the two-dimensional equivalent of the line after deformation with that before deformation, the strain on the surface of the deformed region is determined. Experiments using sheet metal flanging and hemming were conducted to verify the effectiveness and determine the limitation of the proposed method.

Purpose: In the development of ideas for Industry 4.0, information about the element production cycle has become more and more important. Knowledge of the subsequent forming processes, determination of the machine on which the process has been carried out and of the type and wear of the tool, leads to smart production management, which plays an increasingly important role in the metal forming industry. To meet the current expectations for these challenges, an advanced technology needs to be introduced for monitoring the manufacturing processes by deploying flexible solutions. This technology must include, but not be limited to, identifying and tracking the product using laser marking. Design/methodology/approach: Laser marking allows a permanent mark in the form of a barcode to be applied to the sheet metal surface. Commonly used marking methods and the condition of the sheet metal surface can affect the marking contrast. This paper presents a concept for recording individual stages of sheet metal forming and determination of the impact of the laser marking technology on the contrast of the applied barcode. To ensure accurate control of the deformation stages, the bulging process of the spherical dome has been used as an example. Findings: Analysis of the influence of laser marking method on the barcode recognition accuracy can contribute to the development of smart management of the production process according to the idea of Industry 4.0. Research limitations/implications: A large plastic deformation has been applied to the sheet metal surface and no limitation in a barcode reading process (using vision scanning technology) was indicated. Also, the geometry deformation (different angle view of the CCD camera) of the barcode image has introduced no additional problems with a barcode reading. Originality/value: The optimal parameters of a laser marking technique for barcode marking, which are critical for the material that is subjected to metal forming operations that deform it, have been studied. The results shows that traceability is an attractive solution for tracking technological data in the production chain for a single-shaped product. Keywords: manufacturing control, laser marking, vision analysis, sheet metal forming, barcode quality. Category of the paper: Technical paper.

Advanced vision method of analysis of the Erichsen cupping test based on laser speckle is presented in this work. This method proved to be useful for expanding the range of information on material formability for two commonly used grades of steel sheets: DC04 and DC01. The authors present a complex methodology and experimental procedure that allows not only to determine the standard Erichsen index but also to follow the material deformation stages immediately preceding the occurrence of the crack. Accurate determination of these characteristics in the sheet metal forming would be an important application, especially for automotive industry. However, the sheet metal forming is a very complex manufacturing process and its success depends on many factors. Therefore, attention is focused in this study on better understanding of the Erichsen index in combination with the material deformation history.

In this article, the authors focused on the widely used aluminium extrusion technology, where the die quality and durability are the essential factors. In this study, detailed solutions in the three-key area have been presented. First is applying marking technology, where a laser technique was proposed as a consistent light source of high power in a selected, narrow spectral range. In the second, an automated and reliable identification method of alphanumeric characters was investigated using an advanced machine vision system and digital image processing adopted to the industrial conditions. Third, a proposed concept of online tool management was introduced as an efficient process for properly planning the production process, cost estimation and risk assessment. In this research, the authors pay attention to the designed vision system’s speed, reliability, and mobility. This leads to the practical, industrial application of the proposed solutions, where the influence of external factors is not negligible.