Tolerance Allocation Using Design of Experiments

2015 ◽  
Vol 760 ◽  
pp. 45-50
Author(s):  
Felicia Veronica Banciu ◽  
Ion Grozav ◽  
Cristian Gheorge Turc
Keyword(s):  
Design Of Experiments ◽  
Practical Problem ◽  
Quality Characteristics ◽  
Tolerance Allocation ◽  
Quality Characteristic ◽  
Design Activity ◽  
Tolerance Design ◽  
Mathematical Function ◽  
Optimal Parameters ◽  
High Quality

Tolerance design plays a very important in any manufacturing process because this activity directly influences products cost and quality. In design activity the designer solve the quality problems selecting tight tolerances for components but this generates cost increasing. The practical problem is to assure the high quality characteristics using the maximum tolerances for components that influence them. The paper’s aim is to find optimal parameters setting which assure the desire value of quality characteristics using the DoE (Design of Experiments), and to find a mathematical model and a respective quality characteristic function of the parameters that it was influenced. Using the mathematical function, by imposing the desired tolerance for quality characteristic, it will be allocated the optimal tolerance for components. This tolerance allocation will be verified using Monte-Carlo method.

scholarly journals Optimal Tolerance Design and Optimization for a Pharmaceutical Quality Characteristic

2013 ◽  
Vol 2013 ◽  
pp. 1-17 ◽  
Author(s):  
Seong Hoon Jeong ◽  
Pauline Kongsuwan ◽  
Nguyen Khoa Viet Truong ◽  
Sangmun Shin
Keyword(s):  
Quality Improvement ◽  
Closed Form Solution ◽  
Pharmaceutical Products ◽  
Quality Characteristics ◽  
Form Solution ◽  
Quality Characteristic ◽  
Design System ◽  
Tolerance Design ◽  
Numerical Example ◽  
Pharmaceutical Quality

A number of pharmaceutical quality characteristics are destructive or too costly to inspect. However, most quality improvement tools developed in the pharmaceutical research community typically assume that quality characteristics are nondestructive. This paper proposes a new design system for quality improvement by incorporating the concept of surrogate variables with the concepts of robust design (RD) and tolerance design (TD). The proposed robust-tolerance design paradigm determines the optimal factor setting and specification limits simultaneously, thereby improving quality of pharmaceutical products. In addition, the proposed methodology can provide the optimal tolerance as a mathematical closed-form solution. Finally, a numerical example and its associated sensitivity analysis for a pharmaceutical case are conducted for verification purposes. Based on the numerical example results, the proposed approach could provide robust factor settings with significant tradeoffs between quality and cost.

scholarly journals T1K+: A Database for Benchmarking Color Texture Classification and Retrieval Methods

Sensors ◽  
2021 ◽  
Vol 21 (3) ◽  
pp. 1010
Author(s):  
Claudio Cusano ◽  
Paolo Napoletano ◽  
Raimondo Schettini
Keyword(s):  
Design Of Experiments ◽  
Texture Classification ◽  
Construction Materials ◽  
Heterogeneous Database ◽  
High Quality ◽  
Visual Descriptors ◽  
Classification Tasks ◽  
Color Texture

In this paper we present T1K+, a very large, heterogeneous database of high-quality texture images acquired under variable conditions. T1K+ contains 1129 classes of textures ranging from natural subjects to food, textile samples, construction materials, etc. T1K+ allows the design of experiments especially aimed at understanding the specific issues related to texture classification and retrieval. To help the exploration of the database, all the 1129 classes are hierarchically organized in 5 thematic categories and 266 sub-categories. To complete our study, we present an evaluation of hand-crafted and learned visual descriptors in supervised texture classification tasks.

Quality characteristic decoupling planning of different meta-action units for computer numerical control machine tool

2019 ◽  
Vol 234 (14) ◽  
pp. 2760-2770 ◽  
Author(s):  
Yan Ran ◽  
Teng Zhang ◽  
Zongyi Mu ◽  
Genbao Zhang ◽  
Hongwei Wang ◽  
...  
Keyword(s):  
Machine Tool ◽  
Optimization Method ◽  
Computer Numerical Control ◽  
Quality Characteristics ◽  
Numerical Control ◽  
Quality Characteristic ◽  
Control Machine Tool ◽  
Action Unit ◽  
Action Units ◽  
Control Machine

Since computer numerical control machine tool is composed of multiple meta-action units to achieve one specific function, including the meta-action units' own quality, it still needs to control the coupling relationships among different meta-action units' quality characteristics to guarantee the whole machine's quality. In this article, a method of quality characteristic decoupling planning based on meta-action unit for computer numerical control machine tool was proposed. Firstly, the coupling constraint models based on meta-action unit were established. Secondly, the comprehensive coupling strengths of meta-action units were calculated and introduced into the design structure matrices. Thirdly, multidisciplinary design optimization method was adopted to obtain the optimized control sequence of different meta-action units' quality characteristics. What is more, automatic pallet changer rotary motion of computer numerical control machine tool was taken as an example to illustrate the rightness and effectiveness of this method.

Modeling Present Worth of Product Quality Loss of STB Characteristic Based on Service Life Distribution

2013 ◽  
Vol 397-400 ◽  
pp. 846-851 ◽  
Author(s):  
Yan Ming Zhao ◽  
De Shun Liu ◽  
Ze Jun Wen ◽  
Ting Liu
Keyword(s):  
Service Life ◽  
Product Quality ◽  
Cylindrical Surface ◽  
Quality Characteristics ◽  
Quality Characteristic ◽  
Quality Loss ◽  
Life Distribution ◽  
New Model ◽  
Product Service ◽  
Present Worth

The product smaller-the-better (STB) quality characteristics are continually changing and out of specification limits because of the constant stress, wear and others after the product is put into use, which will cause loss because of the product rejected and scrapped. On the basis of the quality viewpoint that product quality loss is present worth of a loss caused as a result of its quality characteristics because its quality characteristic is out of specification and lead to product scrap after the product is put into service, the paper establishes the present worth model of quality loss of STB characteristic based on service life distribution, and proposes the calculation method on the probability density function (PDF) of the product service life based on the technical specifications of STB quality characteristic. It takes the concentricity between the inner cylindrical surface and the outer cylindrical surface of the link bushing as an example to analysis the various factors that impact on the present worth of concentricity quality loss in the new model, and contrast with Taguchi quality loss model. The results show that the new model describes an actual loss that a product imparts to society after the product is put into service, and can reflect the quality loss of STB characteristic in the product service process, and is more realistic than Taguchi quality loss model of STB. The new model extends tolerance design of STB characteristic from the manufacturing stage to the service stage.

scholarly journals Quality characteristics of spatial furniture

2009 ◽  
pp. 135-145 ◽  
Author(s):  
Dusan Skakic ◽  
Igor Dzincic
Keyword(s):  
Quality Control ◽  
Quality Characteristics ◽  
High Quality ◽  
Production Economy ◽  
Production Practice ◽  
Basic Quality ◽  
Quality Of Products ◽  
Quality Production

The quality of products represents one of the key aims of any modern organized production. In the production practice, it is essential to establish the optimal relationship between quality, production economy and delivery deadlines. Furniture quality is evaluated by three levels and they are: basic quality, high quality and especially high quality. The results presented in this paper are based on the sample measurements of chairs and tables during 2007 and 2008 at the Institute for Furniture Quality Control.

Optimizing parameters for continuous electrospinning of polyacrylonitrile nanofibrous yarn using the Taguchi method

2017 ◽  
Vol 48 (3) ◽  
pp. 559-579 ◽  
Author(s):  
Chang-Mou Wu ◽  
Ching-Hsiang Hsu ◽  
Ching-Iuan Su ◽  
Chun-Liang Liu ◽  
Jiunn-Yih Lee
Keyword(s):  
Principal Component Analysis ◽  
Taguchi Method ◽  
Flow Rate ◽  
Draw Ratio ◽  
Principal Component ◽  
Quality Characteristics ◽  
Optimal Parameters ◽  
Signal To Noise ◽  
Multiple Quality Characteristics ◽  
Nanofibrous Yarn

In this study, the Taguchi method, analysis of variance, and principal component analysis were used to design the optimal parameters with respect to different quality characteristics for the continuous electrospinning of polyacrylonitrile nanofibrous yarn. The experiment was designed using a Taguchi L9(34) orthogonal array. The Taguchi method is a unique statistical method for efficiently evaluating optimal parameters and the effects of different factors on quality characteristics. The experimental results obtained by this method are more accurate and reliable than one-factor-at-a-time experiments. The control factors discussed in this work include the draw ratio, nozzle size, flow rate, and draw temperature. The quality characteristics taken into consideration are fiber diameter, fiber uniformity, and fiber arrangement. The parameters to optimize the different quality characteristics were obtained from the main effect plot of the signal-to-noise ratios, after which analysis of variance and confidence intervals were applied to confirm that the results were acceptable. Multiple quality characteristics were analyzed by principal component analysis from the normalized signal-to-noise ratios and the principal component score. Combining the experimental and analysis results, the optimum parameters for multiple quality characteristics were found to be a draw ratio of 2.0, a nozzle number of 22 G, a flow rate of 7 ml/h, and a draw temperature 120℃.

Design of experiments in the service industry: results from a global survey and directions for further research

2020 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Jiju Antony ◽  
Elisabeth Viles ◽  
Alexandre Fonseca Torres ◽  
Marcelo Machado Fernandes ◽  
Elizabeth A. Cudney
Keyword(s):  
Design Of Experiments ◽  
Continuous Improvement ◽  
Process Improvement ◽  
Six Sigma ◽  
Service Sector ◽  
Success Factors ◽  
Service Industry ◽  
Quality Characteristics ◽  
Content Type ◽  
Critical Success

PurposeThe purpose of this study is to critically evaluate the current status of Design of experiments (DoE) in the service industry or non-manufacturing processes in the manufacturing sector. This involves the identification of critical success factors and challenges in the use of DoE in the context of the service industry as well as the key skills needed for its successful applications.Design/methodology/approachIn order to identify the critical success factors and challenges, an online survey instrument was developed and distributed across Six Sigma Black Belts (SSBB), Six Sigma Master Black Belts (SSMBB), process improvement champions, continuous improvement professionals, DoE experts and specialists as well as academics who are involved in DoE research and applications.FindingsA total of 109 participants from over 20 countries responded to the study. One of the first findings of the study is that over 40% of the process improvement professionals in the service sector do not have any hands-on experience with the application of DoE. Further, this study highlights the following critical factors for successful DoE applications: dedicating adequate resources in terms of time, budget and people for the experiment; getting a clear understanding of the problem at hand; securing a reliable and validated measurement system for measuring the response or quality characteristics of interest; and identifying input independent variables, which influence the quality characteristics during the brainstorming stage. Some respondents also mention the importance of having training or education in DoE as a critical success factor. At the same time, the lack of adequate planning to experimentation, mathematical knowledge and statistical reasoning remains as challenge to be solved.Research limitations/implicationsAs data were collected at an individual level, inter-reliability, which measures the consistency of judgements on a particular survey item, could not be gauged. Moreover, due to low sample size across some continents, an intercontinental comparative study on the extent of the application of DoE across various continents could not be performed.Originality/valueTo the best of the authors’ knowledge, this is the first global survey carried out to understand the status of DoE in the service industry. The results of the global study can be used to encourage quality, continuous improvement and process improvement professionals in the service sector to drive wider acceptance of one of the most powerful tools in the Six Sigma toolkit for problem-solving scenarios. Moreover, senior managers in the service industry can take away some of the key benefits, challenges and success factors in the implementation of DoE.

scholarly journals Multivariate Control Chart Based on Kernel PCA for Monitoring Mixed Variable and Attribute Quality Characteristics

Symmetry ◽  
2020 ◽  
Vol 12 (11) ◽  
pp. 1838
Author(s):  
Muhammad Ahsan ◽  
Muhammad Mashuri ◽  
Wibawati ◽  
Hidayatul Khusna ◽  
Muhammad Hisyam Lee
Keyword(s):  
Control Chart ◽  
Control Charts ◽  
Synthetic Data ◽  
Principal Component ◽  
Quality Characteristics ◽  
Kernel Functions ◽  
Quality Characteristic ◽  
Kernel Pca ◽  
Asymmetric Pattern ◽  
Attribute Quality

The need for a control chart that can visualize and recognize the symmetric or asymmetric pattern of the monitoring process with more than one type of quality characteristic is a necessity in the era of Industry 4.0. In the past, the control charts were only developed to monitor one kind of quality characteristic. Several control charts were created to deal with this problem. However, there are some problems and drawbacks to the conventional mixed charts. In this study, another approach is used to monitor mixed quality characteristics by applying the Kernel Principal Component Analyisis (KPCA) method. Using the Hotelling’s T2 statistic, the kernel PCA mix chart is proposed to simultaneously monitor the variable and attribute quality characteristics. Due to its ability to estimate the asymmetric pattern of the mixed process, the kernel density estimation (KDE) used in the proposed chart has successfully estimated the control limits that produce ARL0 at about 370 for α=0.00273. Through several experiments based on the proportion of the attribute characteristics and kernel functions, the proposed chart demonstrates better performance in detecting outlier and shift in the process. When it is applied to monitor the synthetic data, the proposed chart can detect the shift accurately. Additionally, the proposed chart outperforms the performance of the conventional mixed chart based on PCA mix by producing lower false alarm with more accurate detection of out of control processes.

Applying Life Cycle Six Sigma in Tolerance Design Methodology

2012 ◽  
Vol 443-444 ◽  
pp. 881-887
Author(s):  
Jian Jun Wu ◽  
Yi Zhen Wang
Keyword(s):  
Life Cycle ◽  
Six Sigma ◽  
Life Cycle Cost ◽  
Product Life Cycle ◽  
Quality Characteristic ◽  
Quality Level ◽  
Manufacturing Cost ◽  
Tolerance Design ◽  
Product Life ◽  
Sigma Level

Setting of tolerances to meet a required specification of quality characteristic and keep low manufacturing cost is one of common problems in the process quality control. But generally traditional tolerance design only focus on cost of manufacturing, few consider product Life Cycle Cost. In these situations, to obtain a satisfactory six sigma quality level as well as keep lower life cycle total cost should be considered. This paper expands tolerance optimization based on the manufacturing cost to the product life cycle cost, which can improve product quality to the six sigma level and keep lower LCC simultaneously.

Optimal designing of SkSP-2 skip-lot sampling plan for normally distributed quality characteristics

2017 ◽  
Vol 40 (7) ◽  
pp. 2240-2248 ◽  
Author(s):  
Saminathan Balamurali ◽  
Jambulingam Subramani
Keyword(s):  
Sampling Plan ◽  
Quality Characteristic ◽  
Optimal Parameters ◽  
Optimal Plan ◽  
Sample Number ◽  
Sampling Plans ◽  
Sampling Schemes ◽  
The Cost ◽  
Optimal Designing ◽  
Average Sample

Skip-lot sampling plans have been widely used in industries to reduce the inspection efforts on products that have an excellent quality history. These skip-lot sampling schemes are economically advantageous and useful to minimize the cost of the inspection of the final lots. Also, the skip-lot concept is sound and useful in the design of sampling plans. In this paper, we propose a designing methodology to determine the optimal parameters of a skip-lot sampling plan of type SkSP-2 when the quality characteristic under study follows a normal distribution. The optimal plan parameters are determined to minimize the average sample number subject to satisfying the producer’s and consumer’s risks simultaneously at the acceptable and limiting quality levels, respectively. An optimization problem is formulated in order to construct tables for determining the optimal parameters of the proposed sampling plan for both known and unknown standard deviation cases and the results are compared with the variables single sampling plans.

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