Development of the Optimized Manufacturing Process Model by "TAGUCHI METHOD"

2008 ◽  
Vol 33-37 ◽  
pp. 1413-1418
Author(s):  
Hidetoshi Sakamoto ◽  
Kimihide Tsukamoto ◽  
Yoshifumi Ohbuchi ◽  
Hisahiro Inoue
Keyword(s):  
Taguchi Method ◽  
Manufacturing Process ◽  
Process Model ◽  
Knowledge Engineering ◽  
Processing Condition ◽  
Optimum Conditions ◽  
Knowledge Database ◽  
The Past ◽  
Manufacturing Condition ◽  
Engineering Technique

Authors tried to construct multimedia base support system of the manufacturing process with use of the knowledge base and the inference engine on the www server. This knowledge database systematized the knowledge which was obtained from the document and the skilled engineer as much as possible by using a knowledge engineering technique. However, it is difficult for beginner to find the best processing condition under the condition of the material, the machine and the tool on grinding operation by using the conventional database. Especially, when they encountered the manufacturing condition which is not built into the conventional data base, the past optimum conditions cannot be obtained from the expert system. The best method of obtaining the optimum conditions as the solution of this problem is to execute some experiments for this new case. This research proposed the system, which presented a minimum combination of the multi factor experiments for the best manufacturing condition search by using the Taguchi method. We were able to obtain the best condition to use the proposed robust engineering by only 18 times.

Toward Metamodels for Composable and Reusable Additive Manufacturing Process Models

2014 ◽  
Vol 136 (6) ◽  
Author(s):  
Paul Witherell ◽  
Shaw Feng ◽  
Timothy W. Simpson ◽  
David B. Saint John ◽  
Pan Michaleris ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Metal Powder ◽  
Manufacturing Process ◽  
Process Model ◽  
Model Development ◽  
Process Models ◽  
Powder Bed Fusion ◽  
Powder Bed ◽  
Future Work ◽  
Am Processes

In this paper, we advocate for a more harmonized approach to model development for additive manufacturing (AM) processes, through classification and metamodeling that will support AM process model composability, reusability, and integration. We review several types of AM process models and use the direct metal powder bed fusion AM process to provide illustrative examples of the proposed classification and metamodel approach. We describe how a coordinated approach can be used to extend modeling capabilities by promoting model composability. As part of future work, a framework is envisioned to realize a more coherent strategy for model development and deployment.

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 Evaluating Optimum Conditions for Fatigue Life of NR-based Rubber Compounds Using the Taguchi Method

2019 ◽  
Vol 64 (9) ◽  
pp. 755-761
Author(s):  
Fereshteh MOTIEE ◽  
◽  
Zohreh Ghazi GHAZI TABATABAEI ◽  
Keyword(s):  
Fatigue Life ◽  
Taguchi Method ◽  
Optimum Conditions ◽  
Rubber Compounds

scholarly journals Peningkatan Mutu Proses Pembuatan Cat Solvent dengan Metode Taguchi di PT JI

2018 ◽  
Vol 17 (1) ◽  
pp. 46
Author(s):  
Hery Hamdi Azwir ◽  
Mahfud Mufadhol
Keyword(s):  
Taguchi Method ◽  
Manufacturing Process ◽  
Process Capability ◽  
Powder Coating ◽  
Optimal Level ◽  
Average Percentage ◽  
Control Factors ◽  
Additional Process ◽  
Increase Productivity ◽  
First Time

In a manufacturing process, quality is not only seen from the final product, but also manufacturing process.  PT JI located in Cikarang is a company that produces paints and powder coating. Currently, the company has problems with 24.16% products that need rework or additional process. To increase productivity, PT JI applies the A3 project that is Right First Time (RFT). RFT is how to create a product with a one-time process and produce a product that has good quality on the first test. The average percentage of total RFT products in September 2016-January 2017 was 75.84%. This result is still below the company target of 80%. This study found the source of problems analyzed the manufacturing process using control chart, process capability, fishbone, and pareto. Taguchi method and ANOVA are applied to improve the design process. The application of the Taguchi Method shows that the factors which influence the value of viscosity quality are number of White Spirit, Number of Genekyd, Total Tio2 (kaolin), and mixing temperature, where each factor has an optimal level of 26.01%, 56.07%, 18.78% and 45oC. Then, it is found that all control factors have significant effect on viscosity value from ANOVA analysis. The application of this Taguchi method increases the process capability to Cp = 1.68 and Cpk = 1.43 from Cp = 0.29 and Cpk = 0.18, as well as an increase in RFT percentage of 5.78% or to 81.62% over the last two months.

Some Aspects of S.S.T. Operations in Non-optimum Conditions

1966 ◽  
Vol 19 (3) ◽  
pp. 324-330
Author(s):  
P. S. Cole
Keyword(s):  
Short Review ◽  
Relative Cost ◽  
Optimum Conditions ◽  
The Past ◽  
Cost Penalty

Over the past few years, numerous papers have been written concerning various aspects of S.S.T. operations, the majority dealing with one or two facets. This short review considers those aspects which are of major importance when the S.S.T. is operated in non-optimum conditions and an attempt is made to indicate the relative cost penalty caused by the phenomena discussed, the performance in smooth standard conditions being taken as the datum. Little of the information presented is new and most of the points mentioned are considered in greater detail in the references. (Crown copyright, reproduced with the permission of H.M.S.O.)

Determination of the Optimum Conditions for the Leaching of Lead from Zinc Plant Residues in NaCl–H2SO4–Ca(OH)2 Media by the Taguchi Method

2012 ◽  
Vol 51 (10) ◽  
pp. 3887-3894 ◽  
Author(s):  
Bahram Behnajady ◽  
Javad Moghaddam ◽  
Mohammad A. Behnajady ◽  
Fereshteh Rashchi
Keyword(s):  
Taguchi Method ◽  
Plant Residues ◽  
Optimum Conditions ◽  
Zinc Plant

Learning Algorithm Based Modeling and Process Parameters Recommendation System for Binder Jetting Additive Manufacturing Process

2015 ◽  
Author(s):  
Han Chen ◽  
Yaoyao F. Zhao
Keyword(s):  
Additive Manufacturing ◽  
Product Quality ◽  
Process Parameters ◽  
Manufacturing Process ◽  
Process Model ◽  
Recommendation System ◽  
Powder Materials ◽  
Quality Properties ◽  
Binder Jetting ◽  
Printing Time

Binder Jetting (BJ) process is an additive manufacturing process in which powder materials are selectively joined by binder materials. Products can be manufactured layer by layer directly from 3D model data. It is not always easy for manufacturing engineers to choose proper BJ process parameters to meet the end-product quality and fabrication time requirements. This is because the quality properties of the products fabricated by BJ process are significantly affected by the process parameters. And the relationships between process parameters and quality properties are very complicated. In this paper, a process model is developed by Backward Propagation (BP) Neural Network (NN) algorithm based on 16 groups of orthogonal experiment designed by Taguchi Method to express the relationships between 4 key process parameters and 2 key quality properties. Based on the modeling results, an intelligent parameters recommendation system is developed to predict end-product quality properties and printing time, and to recommend process parameters selection based on the process requirements. It can be used as a guideline for selecting the proper printing parameters in BJ to achieve the desired properties and help to reduce the printing time.

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