Response surface modeling and optimization of single axis automatic application of automotive polyurethane coatings on plastic components

Arunkumar, N.; Venkatesh, P. H. J.; Srinivas, Kadivendi; Kaushik, Sanjiv

doi:10.1007/s00170-012-3970-1

Cited by 10 publications

(4 citation statements)

References 4 publications

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“…Solvent‐borne coatings not only pollute the environment but also threaten human health because of the relatively high volatile organic components (VOCs) present in them. Waterborne polyurethanes (WPUs) are taking an important role in polyurethane industry because of the fact that they are eco‐friendly and can be formulated into coatings containing little or no co‐solvent . WPU makes an effective substitute for solvent‐based analogues.…”

Section: Introductionmentioning

confidence: 99%

Preparation and characterization of waterborne polyurethane containing PET waste/PPG as soft segment

Fang

Lei

Zhou

et al. 2015

J of Applied Polymer Sci

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Soft drinks poly(ethylene terephthalate) (PET) bottles were depolymerized by glycolysis using a 1 : 3 molar ratio of PET repeating unit to glycols like neopentyl glycol (NPG) and dipropylene glycol (DPG). Further, a series of waterborne polyurethanes (WPUs) was synthesized using pure polypropylene glycol (PPG), and glycolyzed oligoesters/PPG blends in different molar ratios as soft segment. Thermal property of WPU was tested by differential scanning calorimetry (DSC) and thermogravimetric analysis (TGA). Moreover, viscosity and particle size of WPU were also investigated. The results show that introduction of a certain amount of glycolyzed oligoester to soft segment makes the degree of hard‐soft domain microphase separation smaller, and can also improve thermal stability of WPU. Furthermore, WPUs synthesised from glycolyzed oligoesters and PPG blends possess larger particle size, better particle size distribution, relative lower and more stable viscosity. © 2015 Wiley Periodicals, Inc. J. Appl. Polym. Sci. 2015, 132, 42757.

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Section: Introductionmentioning

confidence: 99%

Preparation and characterization of waterborne polyurethane containing PET waste/PPG as soft segment

Fang

Lei

Zhou

et al. 2015

J of Applied Polymer Sci

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“…21 Based on the quadratic model, experiments were planned to carry out 13 trials plus a star configuration for time (35, 50, and 65) and temperature (900, 975, and 1050) with their duplicates at the central point. Experimental error was determined using 13 runs at the central point.…”

Section: Development Of Regression Model Equationmentioning

confidence: 99%

Process optimization of doping conditions for (100) P-type monocrystalline silicon solar cell using response surface methodology

2013

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The effect of time and temperature on the sheet resistance (R S ) and carrier concentration (N A ) of (100) P-type monocrystalline Si was investigated. Phosphorus-doped n þ -emitters were fabricated through solid-source doping in a quartz tube furnace. The process variable values for 13 runs were proposed by response surface methodology (RSM). The optimized values for time and temperature predicted by RSM were 56 min and 1045°C, respectively, for a sheet resistance of 41.7 Ω∕□ and a carrier concentration of 3.7E18 cm −3 . Optimization-based fabrication was found to be in close agreement with the optimized values. Parameter optimization using RSM could be valuable in achieving predetermined dopant variables in optoelectronic devices as well as in reducing the surface recombinations and series resistance of highly efficient Si solar cells. , and Mat Jafri: Process optimization of doping conditions for (100) P-type monocrystalline. , and Mat Jafri: Process optimization of doping conditions for (100) P-type monocrystalline. , and Mat Jafri: Process optimization of doping conditions for (100) P-type monocrystalline. , and Mat Jafri: Process optimization of doping conditions for (100) P-type monocrystalline. , and Mat Jafri: Process optimization of doping conditions for (100) P-type monocrystalline. , and Mat Jafri: Process optimization of doping conditions for (100) P-type monocrystalline.

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“…[11][12][13] Validation of spray painting techniques was done using a mathematical model and simulation in Robot Studio for obtaining minimum cycle time using the response surface method. 14,15 Researchers 16,17 identified that precise control of dynamic motion of industrial robots had a significant impact on the overall spray painting process. Thus, a feed-forward closedloop motion precision control was proposed.…”

Section: Introductionmentioning

confidence: 99%

Fuzzy logic expert system with multi-objective optimization of carbon nanotube infused nanopaint surface characteristics analysis using IRB 1410 robot

Jakkula

Sethuramalingam

2022

Proceedings of the Institution of Mechanical Engineers, Part C:

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In this investigative study, the Taguchi design (L9) of experiments with TOPSIS multi-objective optimization is used for the robot nanopainting. The optimization objective is to maximize the film glue individually and minimize the surface blemishes and film thickness by varying the IRB 1410 robot painting parameters, such as the robot speed, pressure, and distance. The multi-wall carbon nanotube is infused into the paint materials using the ultrasonication process, and the mechanical properties are analysed with a comparison to regular paint materials. The virtual robot cycle time analysis is carried out for three different robot pathway patterns, namely linear, zig-zag, and circular. It is then compared with real-time experimental robot nanopaint on cold rolled close annealing steel materials. The obtained results show that surface roughness and thickness are minimized by 54% and 33.4%, respectively, using the robot nano spray coating when compared with regular spray coating. The film adhesive of robot Nano spray coating is maximized by 2.8% more than normal spray coating. A fuzzy logic expert system model is used to evaluate the surface finish characteristics of the nanopaint surface with low prediction error and with 89.2% confidence level. Heat transfer analysis of the robot nano-coated substrate is compared with that of the robot normal-coated substrate.

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Response surface modeling and optimization of single axis automatic application of automotive polyurethane coatings on plastic components

Cited by 10 publications

References 4 publications

Preparation and characterization of waterborne polyurethane containing PET waste/PPG as soft segment

Preparation and characterization of waterborne polyurethane containing PET waste/PPG as soft segment

Process optimization of doping conditions for (100) P-type monocrystalline silicon solar cell using response surface methodology

Fuzzy logic expert system with multi-objective optimization of carbon nanotube infused nanopaint surface characteristics analysis using IRB 1410 robot

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