Data-driven cyber-physical system framework for connected resistance spot welding weldability certification

被引:18
作者
Ahmed, Fahim [1 ]
Jannat, Noor-E [1 ]
Schmidt, Daniel [2 ]
Kim, Kyoung-Yun [1 ]
机构
[1] Wayne State Univ, Dept Ind & Syst Engn, Detroit, MI 48202 USA
[2] ESTECO, Novi, MI 48375 USA
关键词
Cyber-physical systems; Smart manufacturing; Resistance spot welding; Connected weldability certification; Data analytics; Optimization; PROCESS PARAMETERS OPTIMIZATION; PREDICTION;
D O I
10.1016/j.rcim.2020.102036
中图分类号
TP39 [计算机的应用];
学科分类号
081203 ; 0835 ;
摘要
A cyber-physical system is one of the integral parts of the development endeavor of the smart manufacturing domain and the Industry 4.0 wave. With the advances in data analytics, smart manufacturing is gradually transforming the global manufacturing landscape. In the Resistance Spot Welding (RSW) domain, the focus has been more on the physical systems, compared to the virtual systems. The cyber-physical system facilitates the integrated analysis of the design and manufacturing processes by converging the physical and virtual stages to improve product quality in real-time. However, a cyber-physical system integrated RSW weldability certification is still an unmet need. This research is to realize a real-time data-driven cyber-physical system framework with integrated analytics and parameter optimization capabilities for connected RSW weldability certification. The framework is based on the conceptualization of the layers of the cyber-physical system and can incorporate the design and machine changes. It integrates data from the analytics lifecycle phases, starting from the data collection operation, to the predictive analytics operation, and to the visualization of the design. This integrated framework aims to support decision-makers to understand product design and its manufacturing implications. In addition to data analytics, the proposed framework implements a closed-loop machine parameter optimization considering the target product design. The framework visualizes the target product assembly with predicted response parameters along with displaying the process parameters and material design parameters simultaneously. This layer should help the designers in their decision-making process and the engineers to gain knowledge about the manufacturing processes. A case study on the basis of a real industrial case and data is presented in detail to illustrate the application of the envisioned cyber-physical systems framework.
引用
收藏
页数:12
相关论文
共 39 条
[1]   A Conceptual Framework for Cyber-physical System in Connected RSW Weldability Certification [J].
Ahmed, Fahim ;
Jannat, Noor-E ;
Gavidel, Saeed Z. ;
Rickli, Jeremy ;
Kim, Kyoung-Yun .
29TH INTERNATIONAL CONFERENCE ON FLEXIBLE AUTOMATION AND INTELLIGENT MANUFACTURING (FAIM 2019): BEYOND INDUSTRY 4.0: INDUSTRIAL ADVANCES, ENGINEERING EDUCATION AND INTELLIGENT MANUFACTURING, 2019, 38 :431-438
[2]  
[Anonymous], 2009, ELECT COMMUNICATIONS
[3]   Reducing Asynchrony in Channel Garbage-Collection for Improving Internal Parallelism of Multichannel Solid-State Disks [J].
Chang, Li-Pin ;
Wen, Chen-Yi .
ACM TRANSACTIONS ON EMBEDDED COMPUTING SYSTEMS, 2014, 13
[4]   Cyber-physical integration for moving digital factories forward towards smart manufacturing: a survey [J].
Cheng, Ying ;
Zhang, Yongping ;
Ji, Ping ;
Xu, Wenjun ;
Zhou, Zude ;
Tao, Fei .
INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2018, 97 (1-4) :1209-1221
[5]   Side Channels of Cyber-Physical Systems: Case Study in Additive Manufacturing [J].
Chhetri, Sujit Rokka ;
Al Faruque, Mohammad-Abdullah .
IEEE DESIGN & TEST, 2017, 34 (04) :18-25
[6]   Robust detection and reconstruction of state and sensor attacks for cyber-physical systems using sliding modes [J].
Corradini, Maria Letizia ;
Cristofaro, Andrea .
IET CONTROL THEORY AND APPLICATIONS, 2017, 11 (11) :1756-1766
[7]  
Da Xu L., 2014, IEEE Transactions on industrial informatics, V10, P2233, DOI [DOI 10.1109/TII.2014.2300753, 10.1109/TII.2014.2300753]
[8]   New parametric study of nugget size in resistance spot welding process using finite element method [J].
Eisandeh, Hamid ;
Hamedi, Mohsen ;
Halvaee, Ayob .
MATERIALS & DESIGN, 2010, 31 (01) :149-157
[9]   Artificial neural network-based resistance spot welding quality assessment system [J].
El Ouafi, A. ;
Belanger, R. ;
Methot, J. F. .
REVUE DE METALLURGIE-CAHIERS D INFORMATIONS TECHNIQUES, 2011, 108 (06) :343-355
[10]  
Guturu P., 2011, P INT C ADV COMP COM