Selection of Suitable Control Parameters for Proper High-Resolution Deposition Performance of E-Jet Microfabrication Process

2021 ◽  
pp. 193-214
Author(s):  
Raju Das ◽  
Shibendu Shekhar Roy
Keyword(s):  
High Resolution ◽  
Applied Voltage ◽  
Optimization Method ◽  
Control Factor ◽  
Successful Implementation ◽  
Control Parameters ◽  
Utility Concept ◽  
Grey Relational Grade ◽  
Microfabrication Technology ◽  
Grey Relational

E-jet is a high-resolution microfabrication technology. Its operation depends on several process control parameters like applied voltage, flow rate of the material, stand-off height, type of ink material. High-resolution deposition along with high ejection frequency is the performance parameter of E-jet. In the present study, an attempt is made to design the process parameters in such a way that it could simultaneously satisfy both the performance characteristics of the E-jet process. A Taguchi robust design-based utility concept is applied to optimize the multi-response E-jet process through a case study. The optimization result is compared with another multi-objective optimization method called Grey relational grade analysis. The comparative analysis showed that both the methodologies identified the same process parameter combination for improved E-jet performance. Analysis of variance found applied voltage is the most influential control factor in the investigated region. The anticipated improvement in performance shows the successful implementation of the aforesaid methodology.

Parameter Design of High-Resolution E-Jet Micro-Fabrication Process by Taguchi Utility Approach

2018 ◽  
Vol 8 (3) ◽  
pp. 44-58 ◽  
Author(s):  
Raju Das ◽  
Shibendu Shekhar Roy
Keyword(s):  
High Resolution ◽  
Flexible Electronics ◽  
Applied Voltage ◽  
Control Factor ◽  
Successful Implementation ◽  
Utility Analysis ◽  
Micro Fabrication ◽  
Utility Concept ◽  
Single Response

This article describes how an electrohydrodynamic inkjet, or E-jet, is a high-resolution micro-fabrication technology for flexible electronics application. Its operation depends on several process control parameters like applied voltage, flow rate of the material, stand-off height, type of ink material. High-resolution deposition along with ejection frequency is the performance parameter of E-jet. In this article, an attempt is made to design the process parameters in such way, that it could simultaneously satisfy both the performance characteristics of the E-jet process. A Taguchi robust design based utility concept is applied to optimize the multi-response E-jet process through a case study. Utility analysis converts multi-response scenario into a single response by calculating overall utility value, which is optimized by signal to noise (S/N) analysis. Analysis of variance ANOVA found applied voltage is the most influential control factor in the investigated region. The anticipated improvement in fabrication operation shows the successful implementation of the aforesaid methodology.

A Multi-Criteria Decision-Making Approach for Process Improvement of E-Jet: An Experimental Investigation

2020 ◽  
Vol 19 (03) ◽  
pp. 463-497
Author(s):  
Raju Das ◽  
Amit Kumar Ball ◽  
Shibendu Shekhar Roy ◽  
Naresh Chandra Murmu
Keyword(s):  
Flow Rate ◽  
Printed Electronics ◽  
Droplet Diameter ◽  
Relative Weight ◽  
Principal Component ◽  
Evaluation Procedure ◽  
Control Parameters ◽  
Order Preference ◽  
Grey Relational Grade ◽  
Microfabrication Technology

E-jet is a novel microfabrication technology of producing high-resolution patterns for various application areas like printed electronics, biotechnology, etc. Judicious selection of the operating scenario can improve the quality of the fabrication performance of E-jet. The objective of this study is to experimentally evaluate different operating scenarios of the E-jet microfabrication process while considering the deposited droplet diameter and droplet ejection frequency as performance characteristics simultaneously. Experimentations were carried out on the developed E-jet setup according to the design of experiment technique considering nozzle stand-off height, applied voltage, and ink flow rate as process control parameters. The effect of each control parameter on the process response is investigated. The relative weight values of each performance characteristic or response variable are determined by principal component analysis, which makes the weight evaluation procedure more rigorous and eliminates the dependence on the practitioner’s judgment. A hybrid grey relational grade analysis and technique for order preference by similarity to ideal solution methodology is employed to evaluate the optimal operating scenario of E-jet. Both methodologies indicated a similar desirable operating condition for E-jet. Moreover, the variance study called analysis of variance is employed to discover the pattern in which the control parameters affect the fabrication process. The variance study suggests that the ink flow rate is the most dominant parameter in the experimental domain.

scholarly journals Efficient Design of Energy Disaggregation Model with BERT-NILM Trained by AdaX Optimization Method for Smart Grid

Energies ◽  
2021 ◽  
Vol 14 (15) ◽  
pp. 4649
Author(s):  
İsmail Hakkı ÇAVDAR ◽  
Vahit FERYAD
Keyword(s):  
Smart Grids ◽  
Energy Demand ◽  
Optimization Technique ◽  
Cost Effective ◽  
Optimization Method ◽  
Long Term Memory ◽  
Successful Implementation ◽  
Efficient Design ◽  
Energy Disaggregation ◽  
Load Monitoring

One of the basic conditions for the successful implementation of energy demand-side management (EDM) in smart grids is the monitoring of different loads with an electrical load monitoring system. Energy and sustainability concerns present a multitude of issues that can be addressed using approaches of data mining and machine learning. However, resolving such problems due to the lack of publicly available datasets is cumbersome. In this study, we first designed an efficient energy disaggregation (ED) model and evaluated it on the basis of publicly available benchmark data from the Residential Energy Disaggregation Dataset (REDD), and then we aimed to advance ED research in smart grids using the Turkey Electrical Appliances Dataset (TEAD) containing household electricity usage data. In addition, the TEAD was evaluated using the proposed ED model tested with benchmark REDD data. The Internet of things (IoT) architecture with sensors and Node-Red software installations were established to collect data in the research. In the context of smart metering, a nonintrusive load monitoring (NILM) model was designed to classify household appliances according to TEAD data. A highly accurate supervised ED is introduced, which was designed to raise awareness to customers and generate feedback by demand without the need for smart sensors. It is also cost-effective, maintainable, and easy to install, it does not require much space, and it can be trained to monitor multiple devices. We propose an efficient BERT-NILM tuned by new adaptive gradient descent with exponential long-term memory (Adax), using a deep learning (DL) architecture based on bidirectional encoder representations from transformers (BERT). In this paper, an improved training function was designed specifically for tuning of NILM neural networks. We adapted the Adax optimization technique to the ED field and learned the sequence-to-sequence patterns. With the updated training function, BERT-NILM outperformed state-of-the-art adaptive moment estimation (Adam) optimization across various metrics on REDD datasets; lastly, we evaluated the TEAD dataset using BERT-NILM training.

scholarly journals Grey Relational Grade Based Quantitative Analysis of the Factors Influencing the Load Characteristics of A Power Grid

2018 ◽  
Vol 53 ◽  
pp. 01012 ◽  
Author(s):  
Wei Pan ◽  
Caijia Lei ◽  
Wei Jia ◽  
Hui Gao ◽  
Binghua Fang
Keyword(s):  
Quantitative Analysis ◽  
Influencing Factors ◽  
Power Grid ◽  
Grey System Theory ◽  
Grey System ◽  
Factors Affecting ◽  
Grey Relational Grade ◽  
Load Characteristics ◽  
Grey Relational ◽  
Main Factor

Regarding analysis of load characteristics of a power grid, there are multiple factors that influence the variation of load characteristics. Among these factors, the influence of different ones on the change of load characteristic is somewhat different, thus the degree of influence of various factors needs to be quantified to distinguish the main and minor factors of load characteristics. Based on this, the grey relational analysis in the grey system theory is employed as the basis of mathematical model in this paper. Firstly, the main factors affecting the load characteristics of a power grid are analysed. Then, the principle of quantitative analysis of the influencing factors by using grey relational grade is introduced. Lastly, the load of Guangzhou power grid is selected as the research object, thereby the main factor of temperature affecting the load characteristics is quantitatively analysed, such that the correlation between temperature and load is established. In this paper, by investigating the influencing factors and the degree of influence of load characteristics, the law of load characteristics changes can be effectively revealed, which is of great significance for power system planning and dispatching operation.

Stochastic Bayesian optimization for predicting borderline knock

2021 ◽  
pp. 146808742110652
Author(s):  
Jian Tang ◽  
Anuj Pal ◽  
Wen Dai ◽  
Chad Archer ◽  
James Yi ◽  
...  
Keyword(s):  
Fuel Economy ◽  
Learning Algorithm ◽  
Feedforward Control ◽  
Model Development ◽  
Kriging Model ◽  
Optimization Method ◽  
Surrogate Models ◽  
Bayesian Optimization ◽  
Control Parameters ◽  
Operation Conditions

Engine knock is an undesirable combustion that could damage the engine mechanically. On the other hand, it is often desired to operate the engine close to its borderline knock limit to optimize combustion efficiency. Traditionally, borderline knock limit is detected by sweeping tests of related control parameters for the worst knock, which is expensive and time consuming, and also, the detected borderline knock limit is often used as a feedforward control without considering its stochastic characteristics without compensating current engine operational condition and type of fuel used. In this paper, stochastic Bayesian optimization method is used to obtain a tradeoff between stochastic knock intensity and fuel economy. The log-nominal distribution of knock intensity signal is converted to Gaussian one using a proposed map to satisfy the assumption for Kriging model development. Both deterministic and stochastic Kriging surrogate models are developed based on test data using the Bayesian iterative optimization process. This study focuses on optimizing two competing objectives, knock intensity and indicated specific fuel consumption using two control parameters: spark and intake valve timings. Test results at two different operation conditions show that the proposed learning algorithm not only reduces required time and cost for predicting knock borderline but also provides control parameters, based on trained surrogate models and the corresponding Pareto front, with the best fuel economy possible.

A novel PID control parameters tuning approach for robot manipulators mounted on oscillatory bases

Robotica ◽  
2007 ◽  
Vol 25 (4) ◽  
pp. 467-477 ◽  
Author(s):  
J. Lin ◽  
Z.-Z. Huang
Keyword(s):  
Pid Control ◽  
Pid Controller ◽  
Low Cost ◽  
Equations Of Motion ◽  
Grey Theory ◽  
Control Parameters ◽  
State Variables ◽  
Relational Analysis ◽  
Parameters Tuning ◽  
Grey Relational

SUMMARYThis research focuses on the issue of dynamic modeling and controlling a robotic manipulator attached to a compliant base. Such a system is known under the name macro–micro system, characterized by the number of control actuators being less than the number of state variables. The equations of motion for a two-link planar elbow arm mounted on an oscillatory base has been presented in this investigation. In order to study the sensitivity of tuning the PID parameters to achieve the desired performance, the Grey relational analysis has first been proposed. Therefore, the aim of this work is to apply Grey theory to optimize parameters for partial states feedback of a PID controller for such a structure. The experimental results of the proposed methodology also show that it is technically and economically feasible to develop a low-cost, reliable, automatic, less time-consuming controller for robotics mounted on oscillatory bases.

scholarly journals Multi Performance Optimizationof Shoulder Milling Process Parameters of AA6063 T6 Aluminium Alloy by Taguchi Based GRA

2019 ◽  
Vol 8 (10S) ◽  
pp. 420-425
Keyword(s):  
Process Parameters ◽  
Grey Relational Analysis ◽  
Removal Rate ◽  
Analysis Data ◽  
Milling Process ◽  
Depth Of Cut ◽  
Analysis Method ◽  
Relational Analysis ◽  
Grey Relational Grade ◽  
Grey Relational

In this paper, a grey relational analysis method based on Taguchi is proposed to improve the multi-performance characteristics of VMC shoulder milling process parameters in the processing of AA6063 T6. Taking into account four process parameters such as coolant, depth of cut,speed and feed, there are three level of each process parameter in addition to two levels of coolant. 18 experiments were used by L18 orthogonal array using the taguchi method. Multi-performance features like surface roughness and material removal rate are used. Grey Relational Analysis method is used to obtain the Grey Relational Grade, and the multiperformance characteristics of the process are pointed out. Then, the Taguchi response table method and ANOVA are used to analysis data. In order to ensure the validity of the test results, a confirmation test was conducted. The study also shows that this method can effectively improve the multi-function characteristics of shoulder milling process.In his work microstructure and mechanical properties of AA6063 T6before and after shoulder milling have been investigated.

Application of the Grey-Taguchi Method to the Optimization of Metal Injection Molding (MIM) Process

2010 ◽  
Vol 443 ◽  
pp. 63-68 ◽  
Author(s):  
Khairur Rijal Jamaludin ◽  
Norhamidi Muhamad ◽  
Mohd Nizam Ab. Rahman ◽  
Sufizar Ahmad ◽  
Mohd Halim Irwan Ibrahim ◽  
...  
Keyword(s):  
Injection Molding ◽  
Taguchi Method ◽  
Mold Temperature ◽  
Parameter Design ◽  
Metal Injection Molding ◽  
Quality Performance ◽  
Surface Appearance ◽  
Grey Relational Grade ◽  
Grey Relational ◽  
Grey Taguchi

The Grey-Taguchi method was adopted in this study to optimize the injection molding parameters for the MIM green compacts with multiple quality performance. A Grey relational grade obtained from the Grey relational analysis is used as the quality performance in the Taguchi method. Then, the optimum injection molding parameters are determined using the parameter design proposed by the Taguchi method. The result concluded that the mold temperature (D) is very significant, by the fact that the ANOVA shows its contribution to excellent surface appearance as well as strong and dense green compacts is 38.82%.

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