Quality Control of Electro-Discharge Texturing of Rolls Through Six Sigma
This article presents the implementation of the Six Sigma methodology in the electro-discharge texturing process of cold mill work rolls. The final surface quality of sheet metal must meet the specific demands of car body part producers, which require a specific surface texture described by surface microgeometry parameters: the average roughness and the peak density. The requirements for the surface microgeometry of sheet metal are mainly related to improving the formability and adhesion of the paint in the body painting process. These microgeometry parameters can be controlled by the texture of work rolls: this texture is transferred onto the sheet metal surface. The electro-discharge texturing process allows for control of the average roughness and peak density according to individual customer specifications. In this study, a model is proposed to predict the average roughness based on the input parameters of the electro-discharge texturing process: current, voltage, and time. Compared to previous models, this model includes more input parameters. The process suitability was analyzed using control charts, capability indices, and Z scores. The modified weighted product method was used to create a purpose function describing the relationships between the input and output quality parameters. Based on the agreement of the target quality characteristics and the calculated values according to the models obtained, an algorithm to control the texturing process of the work rolls was designed. The proposed model was also validated on results published by other authors and demonstrated good agreement. This study should contribute to the philosophy of continuously improving the surface quality of cold-rolled sheet metal.
Authors
- Emil Evin (ORCID: https://orcid.org/0000-0003-2712-1526)
- Miroslav Tomáš (ORCID: https://orcid.org/0000-0002-8666-5163)
- Vladimír Kokarda
Institutions
- Technical University of Košice (SK)
Publication Details
- Journal
- Processes
- Published
- 2025-02-07
- DOI
- https://doi.org/10.3390/pr13020450
- Citations
- 4
- Primary Topic
- Advanced Machining and Optimization Techniques
- Type
- article
- Field-Weighted Citation Impact
- 2.92
Funders
- Vedecká Grantová Agentúra MŠVVaŠ SR a SAV