Model-based analysis, control and dosing of electroplating electrolytes

Leiden, Alexander; Kölle, Stefan; Thiede, Sebastian; Schmid, K.; Metzner, Martin; Herrmann, Christoph

doi:10.1007/s00170-020-06190-0

Cited by 10 publications

(10 citation statements)

References 18 publications

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“…Validation describes the comparison of the simulation results with the physical system to ensure a sufficient correspondence [84,85]. The model for electrolyte and its flows was already validated in a previous study [68]. The obtained results are also in the same range as other publications [86].…”

Section: Validationmentioning

confidence: 82%

“…This mechanism is crucial for the rinsing cascade as the carryover and the revers rinse flow are the only flows which influence the concentrations in the fluids. More details of the model for the fluids and its verification can be found in Leiden et al [68].…”

Section: Process Chainmentioning

confidence: 99%

“…Different process parameters are used for different product types. The drag-out volume is calculated with a classification approach [68] and the basis for the resource flow model.…”

Section: Description Of Case Studymentioning

confidence: 99%

See 2 more Smart Citations

Synergetic Modelling of Energy and Resource Efficiency as well as Occupational Safety and Health Risks of Plating Process Chains

Leiden

Thiede

Herrmann

2021

Int. J. of Precis. Eng. and Manuf.-Green Tech.

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To meet the sustainable development goals of the United Nations, the energy and resource efficiency of industrial processes have to increase, and workplaces have to become decent for the involved workers. Plating process chains are typically associated with high energy and resource demand and the use of hazardous chemicals. For the analysis and improvement of the energy and resource efficiency as well as for modelling the occupational safety and health risks, a variety of separate approaches are available. Combined approaches are not available yet. An agent-based simulation is used as the basis for integrated energy and resource as well as occupational safety and health risk assessment. In particular, an energy and resource flow model provides the life cycle inventory data for an environmental assessment. The integration of a mechanistic inhalation exposure model through a surrogate model approach enables a combined synergetic consideration of environmental and occupational safety and health effects. A simulation case study shows the impact of chrome acid changes in chrome electroplating processes as well as the effect of different rinsing cascade settings and rinsing control strategies.

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Section: Validationmentioning

confidence: 82%

Section: Process Chainmentioning

confidence: 99%

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Synergetic Modelling of Energy and Resource Efficiency as well as Occupational Safety and Health Risks of Plating Process Chains

Leiden

Thiede

Herrmann

2021

Int. J. of Precis. Eng. and Manuf.-Green Tech.

Self Cite

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“…To achieve a coating with the desired properties, process optimization is necessary. However, this can be a time-consuming process [3]. One typical approach in industry for electroplating process optimization is to do Hull Cell experiments.…”

Section: Introductionmentioning

confidence: 99%

Machine Learning Approach for Process Optimization of Black Nickel Electroplating

SUN,

Tan,

Zhao

et al. 2024

Preprint

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Optimization of electroplating processes is crucial yet time-consuming. In an electroplating process like black nickel plating, achieving a consistent coating becomes challenging without boric acid, which serves as a pH buffer and widens the operational process window. Despite its benefits, the use of boric acid conflicts with the growing emphasis on sustainable and eco-friendly manufacturing. This complication intensifies the intricacy of process optimization. To tackle this challenge, this study employs machine learning techniques to gain insights into optimizing a boric acid-free black nickel plating process. Specifically, three machine learning models were developed to predict coating defects, coating colour, and coating mass. Drawing from the predictions of these models, an optimization algorithm is proposed to select process parameters ensuring a flawless coating with the desired colour and mass, which is validated by experimental result. The machine learning models were able to give accurate predictions for black nickel electroplating process which behaves in a non-linear manner. This research illustrates how machine learning can enhance the manufacturing industry, particularly in the surface finishing sector, by providing an effective approach to optimize processes in non-linear scenarios, thereby improving product quality and work productivity.

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“…In this case, chemical processes are being employed mainly for plating, corrosion protection and surface finishing and involve chemical cleaning, deoxidizing, metal plating, anodizing and chemical conversion coatings. These chemical processes, however, are responsible for the majority of the environmental impact of the Special Processes in total, because hazardous substances are being used, process baths are typically large and therefore the effluent loads are high and difficult to manage [1], [2] [3].…”

Section: Introductionmentioning

confidence: 99%

Continuing education in green chemical processes for aerospace manufacturing: The case of drag-out

Aptoglou,

Papachristodoulou,

Gounaris

et al. 2023

J. Phys.: Conf. Ser.

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In the new era of job market in the EU zone and abroad, novel Occupational Profiles dictate the development and the update of Learning Outcome-based Curricula. This stands for all disciplines and specialties and for various Qualification Levels (QL), from after-school education up to the highest QL. The pertaining Curricula should allude to specific knowledge, skills, and behaviours, that are being mandated from the respective Occupational Profiles. For intermediate QL, namely in between secondary school and University, there is an utmost need for new, updated, attractive Curricula covering current and new market needs. Such Curricula should be supported from Course Units that are technologically updated, thus providing the trainees the skills and knowledge to cover the current and novel Learning Outcomes and Performance Criteria for the specified QL. We herein present a newly developed Course Unit, part of the Green Special Processes course that can be offered in the context of a continuing Vocational Education Training (cVET) Program targeting a QL equivalent to the European QL 5. This Course Unit covers the case of drag-out, which has significant environmental and economic impacts on the engineering of wet chemical processes entailing multiple process baths and requiring rinsing. Such processes are widely used also in Aircraft manufacturing and the related environmental impacts have become very important. Part of the basic theory, as well as part of the practical training are presented herein.

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Model-based analysis, control and dosing of electroplating electrolytes

Cited by 10 publications

References 18 publications

Synergetic Modelling of Energy and Resource Efficiency as well as Occupational Safety and Health Risks of Plating Process Chains

Synergetic Modelling of Energy and Resource Efficiency as well as Occupational Safety and Health Risks of Plating Process Chains

Machine Learning Approach for Process Optimization of Black Nickel Electroplating

Continuing education in green chemical processes for aerospace manufacturing: The case of drag-out

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