{"title":"Model based adaptive process control along intercompany process chain for sheet metal forming of steel","authors":"Nilesh Thakare , Jannik Gerlach , Nikita Fjodorovs , David Bailly , Emad Scharifi","doi":"10.1016/j.jmapro.2025.02.082","DOIUrl":null,"url":null,"abstract":"<div><div>A typical metallic product manufacturing process chain involving several companies faces challenges in promptly responding to the deviations in material properties, thereby impacting its economic efficiency. This can be attributed to the lack of knowledge about the exact condition of each product in a batch, as suppliers can only perform quality inspections randomly. This study introduces a novel approach utilizing simulation models to calculate the mechanical properties of products and design of experiments based process design using the calculated product properties shared by suppliers with their customers over a secure and reliable intercompany data management platform. The proposed approach is implemented in a laboratory scale process chain consisting of cold rolling and deep drawing using DC04 steel to demonstrate adaptive process control via intercompany exchange of yield and tensile strength of the cold strip. The benefits of adaptive process control are demonstrated by 50 % reduction in deviations in the minimum sheet thickness in cross die, thus showcasing the reproducibility of the end product with improved quality and by avoiding scrap generation, thereby allowing a sustainable manufacturing.</div></div>","PeriodicalId":16148,"journal":{"name":"Journal of Manufacturing Processes","volume":"141 ","pages":"Pages 403-415"},"PeriodicalIF":6.1000,"publicationDate":"2025-03-06","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":null,"platform":"Semanticscholar","paperid":null,"PeriodicalName":"Journal of Manufacturing Processes","FirstCategoryId":"5","ListUrlMain":"https://www.sciencedirect.com/science/article/pii/S1526612525002403","RegionNum":1,"RegionCategory":"工程技术","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q1","JCRName":"ENGINEERING, MANUFACTURING","Score":null,"Total":0}
引用次数: 0
Abstract
A typical metallic product manufacturing process chain involving several companies faces challenges in promptly responding to the deviations in material properties, thereby impacting its economic efficiency. This can be attributed to the lack of knowledge about the exact condition of each product in a batch, as suppliers can only perform quality inspections randomly. This study introduces a novel approach utilizing simulation models to calculate the mechanical properties of products and design of experiments based process design using the calculated product properties shared by suppliers with their customers over a secure and reliable intercompany data management platform. The proposed approach is implemented in a laboratory scale process chain consisting of cold rolling and deep drawing using DC04 steel to demonstrate adaptive process control via intercompany exchange of yield and tensile strength of the cold strip. The benefits of adaptive process control are demonstrated by 50 % reduction in deviations in the minimum sheet thickness in cross die, thus showcasing the reproducibility of the end product with improved quality and by avoiding scrap generation, thereby allowing a sustainable manufacturing.
期刊介绍:
The aim of the Journal of Manufacturing Processes (JMP) is to exchange current and future directions of manufacturing processes research, development and implementation, and to publish archival scholarly literature with a view to advancing state-of-the-art manufacturing processes and encouraging innovation for developing new and efficient processes. The journal will also publish from other research communities for rapid communication of innovative new concepts. Special-topic issues on emerging technologies and invited papers will also be published.