3.8 Proceedings Paper

Sensitivity analysis of the rotary draw bending process as a database of digital equipping support

Publisher

ELSEVIER SCIENCE BV
DOI: 10.1016/j.promfg.2019.02.100

Keywords

Rotary draw bending; Equipping process; Sensitivity analysis; Cyber physical system; Industry 4.0

Funding

  1. European Union
  2. state of North Rhine Westphalia
  3. EFRE.NRW Investition in Wachstum und Beschaftigung [EFRE-0800261]

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Due to the adaptation to new market requirements with regard to individual products, equipping operations in tube and sheet metal bending are demanded at shorter intervals of time. The equipping process of a rotary draw bending machine can be divided into a static and a dynamic part. The static equipping process consists of all preparatory logistical measures and a subsequent assembly of the tools of the new workpiece. The dynamic equipping process consists of performing iterative bends and, after assessing the component quality, adjusting process parameters until the quality characteristics of the component meet customer requirements. In order to carry out an equipping process with the least possible expenditure of time and a small number of rejected parts, high level of experience is required. The aim is to use a sensitivity analysis to identify the influence of the individual process parameters on the quality characteristics, crack probability on the outer arc and wrinkle formation on the inner arc, by means of practical bending tests in a targeted and systematic manner. Based on the results, recommendations for parameter corrections are stored in cases depending on the error pattern and form the basis of digital equipping support based on the principle of case-based-reasoning. This helps to make the product quality user-independent by guiding the machine operator in his work, and to make the equipping process in the course of Industry 4.0 flexible as well as time and cost-reduced. (C) 2019 The Authors. Published by Elsevier B.V. This is an open access article under the CC BY-NC-ND license (https://creativecommons.org/licenses/by-nc-nd/4.0/) Selection and peer-review under responsibility of the organizing committee of SHEMET 2019.

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