scholarly journals Prediction and Optimization of Production Quantities in Innoson Manufacturing Extraction Plastic Product

2019 ◽  
pp. 1-11
Author(s):  
Ezeliora, Chukwuemeka Daniel ◽  
Okoye, Peter Chukwuma ◽  
U. Mbabuike, Ikenna
Keyword(s):  
Factorial Design ◽  
Design Space ◽  
Design Method ◽  
Signal To Noise Ratio ◽  
Optimal Solution ◽  
Coefficient Of Determination ◽  
Anambra State ◽  
Plastic Pipes ◽  
Surface Plot ◽  
Production Quantity

In this research, it focused on the prediction and optimization of the production quantity in Innoson Plastic Manufacturing Company, Nnewi, Anambra State, Nigeria. The research method used is the application of factorial design methods to model, to evaluate the best optimal solutions for the production quantity of extrusion plastic pipes in the aforementioned company. The analysis shows that the parameters used to model the production quantity are significant and the model produced is also significant with its coefficient of determination to be 0.9968 and the adjusted R-Squared is 0.9823. Adequate Precision measures the signal to noise ratio. A ratio greater than 4 is desirable. The ratio of 29.271 indicates an adequate signal. This model can be used to navigate the design space. The Model F-value of 68.99 implies the model is significant. There is only a 1.44% chance that an F-value this large could occur due to noise. Values of "Prob > F" less than 0.0500 indicate model terms are significant. The 3D surface plot shows the effect of the variables in production system. It describes the variations of the input and output parameters in production of plastic extrusion products. The factorial design method applied shows the optimal solution which revealed that the best quantity of the product that is necessary to produce in any given month is 14414.112 units of a 25mm diameter plastic pipes with the optimal desirability of 100%. The tool also shows that the pigment is almost not important in the optimization of the product production quantity due to its insignificant quantity. However, the results further revealed that the industry should be conscious of highly influence input variable during production.

scholarly journals METHOD TO DEFINE MEASUREMENT UNCERTAINTY FOR DESIGN SPACE EXPLORATION IN ADDITIVE MANUFACTURING

2021 ◽  
Vol 1 ◽  
pp. 2067-2076
Author(s):  
Valentine Cazaubon ◽  
Audrey Abi Akle ◽  
Xavier Fischer
Keyword(s):  
Additive Manufacturing ◽  
Design Space Exploration ◽  
Design Space ◽  
Design Method ◽  
Optimal Solution ◽  
Feed Speed ◽  
Parameters Selection ◽  
Wire Feed Speed ◽  
Geometrical Defects ◽  
The Given

AbstractAdditive manufacturing is a process used for quick prototyping in industries. Geometrical defects are observed on printed parts. The aim of the paper is to propose a design method to implement measurements uncertainties into a Design Space for Additive Manufacturing parameters selection. To do so, two tests have been realized. The first test consists in determining the instrument’s uncertainty by measuring a standard length several times by an operator. The second test aim to determine the uncertainty within operators mesurement of geometric outputs (clad’s height, clad’s width, dilution’s height, dilution’s width and contact angle). Based on the results of our tests, uncertainties have been applied in our Design Space populated with 31 real printed clads. The uncertainties display with error bars on scatterplots allow to capitalize the knowledge for his/her exploration of the Design Space for future prints. The given information provides to ease the engineer to select the optimal solution (laser power, tool speed and wire feed speed) for his/her given Additive Manufacturing problematic among candidate points

A Natural Language to Component Term Methodology: Towards a Form Based Concept Generation Tool

2009 ◽  
Author(s):  
Matt R. Bohm ◽  
Robert B. Stone
Keyword(s):  
Artificial Intelligence ◽  
Natural Language ◽  
Design Space ◽  
Design Method ◽  
Optimal Solution ◽  
Solution Space ◽  
Design Solution ◽  
Concept Generation ◽  
Language Interpretation ◽  
Interpretation Algorithm

Over the last few decades design researchers have put forward theories and proposed methodologies that increase the chance that a design team will reliably arrive at the optimal solution to a given design problem. Studies, however, bear out that theories and methodologies alone will not guarantee an optimal or even good design solution. Instead, a breadth of knowledge across multiple engineering domains and the time and tools to thoroughly evaluate the design space are as important as any prescriptive design method. This work presents one of the underlying engineering technologies needed to leverage artificial intelligence approaches to thoroughly search the design space and synthesize concept solutions. Artificial intelligence methods are employed to generate a natural language to formal component terms thesaurus as part of a novel form-initiated concept generation approach. With this fundamental natural language interpretation algorithm, designers may now suggest an initial solution to a problem, expressed in everyday terms, and then rely on a machine to abstract the underlying functionality and conduct a thorough search of the solution space.

scholarly journals Configuration Study of Electric Helicopters for Urban Air Mobility

Aerospace ◽  
2021 ◽  
Vol 8 (2) ◽  
pp. 54
Author(s):  
Julia A. Cole ◽  
Lauren Rajauski ◽  
Andrew Loughran ◽  
Alexander Karpowicz ◽  
Stefanie Salinger
Keyword(s):  
Conceptual Design ◽  
Urban Areas ◽  
Design Space ◽  
Design Method ◽  
Urban Air ◽  
Main Rotor ◽  
Potential Benefits ◽  
Compound Helicopter ◽  
Configuration Changes

There is currently interest in the design of small electric vertical take-off and landing aircraft to alleviate ground traffic and congestion in major urban areas. To support progress in this area, a conceptual design method for single-main-rotor and lift-augmented compound electric helicopters has been developed. The design method was used to investigate the feasible design space for electric helicopters based on varying mission profiles and technology assumptions. Within the feasible design space, it was found that a crossover boundary exists as a function of cruise distance and hover time where the most efficient configuration changes from a single-main-rotor helicopter to a lift-augmented compound helicopter. In general, for longer cruise distances and shorter hover times, the lift-augmented compound helicopter is the more efficient configuration. An additional study was conducted to investigate the potential benefits of decoupling the main rotor from the tail rotor. This study showed that decoupling the main rotor and tail rotor has the potential to reduce the total mission energy required in all cases, allowing for increases in mission distances and hover times on the order of 5% for a given battery size.

scholarly journals Full Factorial Design for Gold Recovery from Industrial Solutions

Toxics ◽  
2021 ◽  
Vol 9 (5) ◽  
pp. 111
Author(s):  
Maria Mihăilescu ◽  
Adina Negrea ◽  
Mihaela Ciopec ◽  
Petru Negrea ◽  
Narcis Duțeanu ◽  
...  
Keyword(s):  
Factorial Design ◽  
Adsorption Capacity ◽  
Contact Time ◽  
Adsorption Process ◽  
Design Method ◽  
Precious Metals ◽  
Gold Recovery ◽  
Maximum Adsorption Capacity ◽  
Gold Concentration ◽  
Commercial Resin

Gold is one of the precious metals with multiple uses, whose deposits are much smaller than the global production needs. Therefore, extracting maximum gold quantities from industrial diluted solutions is a must. Am-L-GA is a new material, obtained by an Amberlite XAD7-type commercial resin, functionalized through saturation with L-glutamic acid, whose adsorption capacity has been proved to be higher than those of other materials utilized for gold adsorption. In this context, this article presents the results of a factorial design experiment for optimizing the gold recovery from residual solutions resulting from the electronics industry using Am-L-GA. Firstly, the material was characterized using atomic force microscopy (AFM), to emphasize the material’s characteristics, essential for the adsorption quality. Then, the study showed that among the parameters taken into account in the analysis (pH, temperature, initial gold concentration, and contact time), the initial gold concentration in the solution plays a determinant role in the removal process and the contact time has a slightly positive effect, whereas the pH and temperature do not influence the adsorption capacity. The maximum adsorption capacity of 29.27 mg/L was obtained by optimizing the adsorption process, with the control factors having the following values: contact time ~106 min, initial Au(III) concentration of ~164 mg/L, pH = 4, and temperature of 25 °C. It is highlighted that the factorial design method is an excellent instrument to determine the effects of different factors influencing the adsorption process. The method can be applied for any adsorption process if it is necessary to reduce the number of experiments, to diminish the resources or time consumption, or for expanding the investigation domain above the experimental limits.

Median Morphological Filter Design Based on the PSO Algorithm

2011 ◽  
Vol 128-129 ◽  
pp. 181-184
Author(s):  
You Lian Zhu ◽  
Cheng Huang
Keyword(s):  
Filter Design ◽  
Design Method ◽  
Signal To Noise Ratio ◽  
Pso Algorithm ◽  
Morphological Operations ◽  
Morphological Filter ◽  
Signal To Noise ◽  
Noise Ratio ◽  
The Cost ◽  
Filter Design Method

Design of morphological filter greatly depends on morphological operations and structuring elements selection. A filter design method used median closing morphological operation is proposed to enhance the image denoising ability and the PSO algorithm is introduced for structural elements selecting. The method takes the peak value signal-to-noise ratio (PSNR) as the cost function and may adaptively build unit structuring elements with zero square matrix. Experimental results show the proposed method can effectively remove impulse noise from a noisy image, especially from a low signal-to-noise ratio (SNR) image; the noise reduction performance has obvious advantages than the other.

Optimal Parameter Design of Solder Residue in Flip Chip Process by Using Taguchi Method

2010 ◽  
Vol 443 ◽  
pp. 543-548
Author(s):  
Jian Long Kuo ◽  
Kai Lun Chao ◽  
Chun Cheng Kuo
Keyword(s):  
Taguchi Method ◽  
Product Quality ◽  
Manufacturing Process ◽  
Flip Chip ◽  
Optimal Parameter ◽  
Experimental Testing ◽  
Signal To Noise Ratio ◽  
Optimal Solution ◽  
Passive Component

Because the solder residue was found in the manufacturing process which greatly affected the product quality, the purpose of this paper was to make the product quality improved and to find an optimal solution for process parameters in the flip chip process. The experimental testing was based on SMT manufacturing process. The amount and size of solder left on passive component in the process of manufacturing were considered as the quality traits. Since too many solders left on the passive component side during flux cleaning process, it was possible that the balling would be flowed into the chip, which caused the bump short in the chip and affected the quality of the product. In this paper, orthogonal array by using Taguchi method is adopted as the effective experimental method with the least experimental runs. Also, based on the quality evaluation of signal-to-noise ratio, the ANOVA is used to evaluate the effects of quality target according to the experimental results. The results reveal that the optimization in the process is confirmed. Therefore, this study can effectively improve the solder residue in semiconductor manufacturing process.

scholarly journals The effect of service constraint on EPQ model with random defective rate

2006 ◽  
Vol 2006 ◽  
pp. 1-5 ◽  
Author(s):  
Yung-Fu Huang
Keyword(s):  
Annual Cost ◽  
Differential Calculus ◽  
Cost Minimization ◽  
Algebraic Approach ◽  
Optimal Solution ◽  
Service Level ◽  
Economic Production Quantity ◽  
Economic Production ◽  
Epq Model ◽  
Production Quantity

Chiu studied the effect of service-level constraint on the economic production quantity (EPQ) model with random defective rate. In this note, we will offer a simple algebraic approach to replace his differential calculus skill to find the optimal solution under the expected annual cost minimization.

scholarly journals Acid treatments of montmorillonite-rich clay for Fe removal using a factorial design method

2013 ◽  
Vol 16 (5) ◽  
pp. 1122-1127 ◽  
Author(s):  
Lindiane Bieseki ◽  
Francine Bertell ◽  
Helen Treichel ◽  
Fabio G. Penha ◽  
Sibele B. C. Pergher
Keyword(s):  
Factorial Design ◽  
Design Method ◽  
Acid Treatments

Design Optimization of a 3D Parameterized Vane Cascade With Non-Axisymmetric Endwall Based on a Modified EGO Algorithm and Data Mining Techniques

2017 ◽  
Author(s):  
Chenxi Li ◽  
Zhendong Guo ◽  
Liming Song ◽  
Jun Li ◽  
Zhenping Feng
Keyword(s):  
Data Mining ◽  
Global Optimization ◽  
Design Space ◽  
Pressure Coefficient ◽  
Differential Evolution Algorithm ◽  
Optimal Solution ◽  
Efficient Global Optimization ◽  
Data Mining Techniques ◽  
Parallel Axis ◽  
Better Than

The design of turbomachinery cascades is a typical high dimensional and computationally expensive problem, a metamodel-based global optimization and data mining method is proposed to solve it. A modified Efficient Global Optimization (EGO) algorithm named Multi-Point Search based Efficient Global Optimization (MSEGO) is proposed, which is characterized by adding multiple samples at per iteration. By testing on typical mathematical functions, MSEGO outperforms EGO in accuracy and convergence rate. MSEGO is used for the optimization of a turbine vane with non-axisymmetric endwall contouring (NEC), the total pressure coefficient of the optimal vane is increased by 0.499%. Under the same settings, another two optimization processes are conducted by using the EGO and an Adaptive Range Differential Evolution algorithm (ARDE), respectively. The optimal solution of MSEGO is far better than EGO. While achieving similar optimal solutions, the cost of MSEGO is only 3% of ARDE. Further, data mining techniques are used to extract information of design space and analyze the influence of variables on design performance. Through the analysis of variance (ANOVA), the variables of section profile are found to have most significant effects on cascade loss performance. However, the NEC seems not so important through the ANOVA analysis. This is due to the fact the performance difference between different NEC designs is very small in our prescribed space. However, the designs with NEC are always much better than the reference design as shown by parallel axis, i.e., the NEC would significantly influence the cascade performance. Further, it indicates that the ensemble learning by combing results of ANOVA and parallel axis is very useful to gain full knowledge from the design space.

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