Model-based analysis, control and dosing of electroplating electrolytes

被引:0
|
作者
Alexander Leiden
Stefan Kölle
Sebastian Thiede
Klaus Schmid
Martin Metzner
Christoph Herrmann
机构
[1] Technische Universität Braunschweig,Institute of Machine Tools and Production Technology, Chair of Sustainable Manufacturing & Life Cycle Engineering
[2] Fraunhofer-Institute for Manufacturing Engineering and Automation IPA,Division Surface Engineering and Materials Technology, Department Electroplating
[3] Fraunhofer Institute of Surface Engineering and Thin Films IST,undefined
来源
The International Journal of Advanced Manufacturing Technology | 2020年 / 111卷
关键词
Electroplating; Electrolyte control; Electrolyte dosing; Cyber-physical production systems; Simulation;
D O I
暂无
中图分类号
学科分类号
摘要
Controlling and dosing electrolytes is a key challenge in the operation of electroplating process chains. Electrolyte components are continuously degraded and dragged out during the production process. This process is influenced by a variety of internal and external factors such as process parameters, the electrolyte itself, anodes, the substrates and the production environment. The exact analytical measurement of the electrolyte composition requires extensive analytical equipment and typically cannot be completely realized within an industrial plating company. Therefore, this paper presents a model-based approach, integrated in a cyber-physical production system, for controlling and dosing electrolytes. A mathematical resource flow model is the basis for a dynamic agent-based simulation. This model uses available data from the manufacturing execution system and enterprise resource planning system to model the current composition of the electrolyte. The approach is successfully validated for two different electrolyte substances at an industrial acid zinc–nickel barrel plating process chain for automotive parts.
引用
收藏
页码:1751 / 1766
页数:15
相关论文
共 50 条
  • [1] Model-based analysis, control and dosing of electroplating electrolytes
    Leiden, Alexander
    Koelle, Stefan
    Thiede, Sebastian
    Schmid, Klaus
    Metzner, Martin
    Herrmann, Christoph
    INTERNATIONAL JOURNAL OF ADVANCED MANUFACTURING TECHNOLOGY, 2020, 111 (5-6) : 1751 - 1766
  • [2] Model-based simulation to support the extended dosing regimens of atezolizumab
    Chen-Hsi Chou
    Li-Feng Hsu
    European Journal of Clinical Pharmacology, 2021, 77 : 87 - 93
  • [3] Model-based simulation to support the extended dosing regimens of atezolizumab
    Chou, Chen-Hsi
    Hsu, Li-Feng
    EUROPEAN JOURNAL OF CLINICAL PHARMACOLOGY, 2021, 77 (01) : 87 - 93
  • [4] Considerations for model-based traffic control
    Burger, M.
    van den Berg, M.
    Hegyi, A.
    De Schutter, B.
    Hellendoorn, J.
    TRANSPORTATION RESEARCH PART C-EMERGING TECHNOLOGIES, 2013, 35 : 1 - 19
  • [5] Model-Based Approaches to Active Perception and Control
    Pezzulo, Giovanni
    Donnarumma, Francesco
    Iodice, Pierpaolo
    Maisto, Domenico
    Stoianov, Ivilin
    ENTROPY, 2017, 19 (06)
  • [6] Fuzzy model-based predictive temperature control
    Kozák, S
    Vassileva, S
    Kozáková, A
    ESS'98 - SIMULATION TECHNOLOGY: SCIENCE AND ART, 1998, : 313 - 317
  • [7] A redundant dynamic model of parallel robots for model-based control
    Zubizarreta, Asier
    Cabanes, Itziar
    Marcos, Marga
    Pinto, Charles
    ROBOTICA, 2013, 31 : 203 - 216
  • [8] MODEL-BASED AND MODEL-FREE CONTROL OF AUTOCORRELATED PROCESSES
    RUNGER, GC
    WILLEMAIN, TR
    JOURNAL OF QUALITY TECHNOLOGY, 1995, 27 (04) : 283 - 292
  • [9] Model-based analysis and simulation of airflow control systems of ventilation units in building environments
    Wu, Zhuang
    Melnik, Roderick V. N.
    Borup, Finn
    BUILDING AND ENVIRONMENT, 2007, 42 (01) : 203 - 217
  • [10] Model-based needle control in prostate percutaneous procedures
    Maghsoudi, Arash
    Jahed, Mehran
    PROCEEDINGS OF THE INSTITUTION OF MECHANICAL ENGINEERS PART H-JOURNAL OF ENGINEERING IN MEDICINE, 2013, 227 (H1) : 58 - 71