東華大學圖書館 |

Language: English

Help

回圖書館首頁

手機版館藏查詢

Back

Switch To: Labeled | MARC Mode | ISBD

Industrial design of experiments = a...

Shina, Sammy.

Linked to FindBook

Google Book

Amazon

博客來

Industrial design of experiments = a case study approach for design and process optimization /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Industrial design of experiments/ by Sammy Shina.
Reminder of title:	a case study approach for design and process optimization /
Author:	Shina, Sammy.
Published:	Cham :Springer International Publishing : : 2022.,
Description:	xxxi, 368 p. :ill. (some col.), digital ;24 cm.
[NT 15003449]:	Presentations, Statistical Distributions, Quality Tools and Relationship to DoE -- Samples and Populations: Statistical Tests for Significance of Mean and Variability -- Regression, Treatments, DoE Design and Modelling Tools -- Two-Level Factorial Design and Analysis Techniques -- Three-Level Factorial Design and Analysis Techniques -- DoE Error Handling, Significance and Goal Setting -- DoE Reduction Using Confounding and Professional Experience -- Multiple Level Factorial Design and DoE Sequencing Techniques -- Variability Reduction Techniques and Combining with Mean Analysis -- Strategies for Multiple Outcome Analysis and Summary of DoE Case Studies and Techniques.
Contained By:	Springer Nature eBook
Subject:	Engineering - Experiments. -
Online resource:	https://doi.org/10.1007/978-3-030-86267-1
ISBN:	9783030862671

Industrial design of experiments = a case study approach for design and process optimization /
Shina, Sammy.

Industrial design of experimentsa case study approach for design and process optimization /[electronic resource] :by Sammy Shina. - Cham :Springer International Publishing :2022. - xxxi, 368 p. :ill. (some col.), digital ;24 cm.

Presentations, Statistical Distributions, Quality Tools and Relationship to DoE -- Samples and Populations: Statistical Tests for Significance of Mean and Variability -- Regression, Treatments, DoE Design and Modelling Tools -- Two-Level Factorial Design and Analysis Techniques -- Three-Level Factorial Design and Analysis Techniques -- DoE Error Handling, Significance and Goal Setting -- DoE Reduction Using Confounding and Professional Experience -- Multiple Level Factorial Design and DoE Sequencing Techniques -- Variability Reduction Techniques and Combining with Mean Analysis -- Strategies for Multiple Outcome Analysis and Summary of DoE Case Studies and Techniques.

This textbook provides the tools, techniques, and industry examples needed for the successful implementation of design of experiments (DoE) in engineering and manufacturing applications. It contains a high-level engineering analysis of key issues in the design, development, and successful analysis of industrial DoE, focusing on the design aspect of the experiment and then on interpreting the results. Statistical analysis is shown without formula derivation, and readers are directed as to the meaning of each term in the statistical analysis. Industrial Design of Experiments: A Case Study Approach for Design and Process Optimization is designed for graduate-level DoE, engineering design, and general statistical courses, as well as professional education and certification classes. Practicing engineers and managers working in multidisciplinary product development will find it to be an invaluable reference that provides all the information needed to accomplish a successful DoE. Presents classical versus Taguchi DoE methodologies as well as techniques developed by the author for successful DoE; Offers a step-wise approach to DoE optimization and interpretation of results; Includes industrial case studies, worked examples and detailed solutions to problems.

ISBN: 9783030862671

Standard No.: 10.1007/978-3-030-86267-1doiSubjects--Topical Terms:

531641
Engineering
--Experiments.

LC Class. No.: TA160 / .S55 2022

Dewey Class. No.: 620.00724

Industrial design of experiments = a case study approach for design and process optimization /
LDR:02962nmm a2200325 a 4500 001 2297273
003 DE-He213
005 20220103143040.0
006 m d
007 cr nn 008maaau
008 230324s2022 sz s 0 eng d
020 $a 9783030862671 $q (electronic bk.)
020 $a 9783030862664 $q (paper)
024 7 $a 10.1007/978-3-030-86267-1 $2 doi
035 $a 978-3-030-86267-1
040 $a GP $c GP
041 0 $a eng
050 4 $a TA160 $b .S55 2022
072 7 $a TBD $2 bicssc
072 7 $a TEC016020 $2 bisacsh
072 7 $a TBD $2 thema
082 0 4 $a 620.00724 $2 23
090 $a TA160 $b .S556 2022
100 1 $a Shina, Sammy. $3 3592670
245 1 0 $a Industrial design of experiments $h [electronic resource] : $b a case study approach for design and process optimization / $c by Sammy Shina.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2022.
300 $a xxxi, 368 p. : $b ill. (some col.), digital ; $c 24 cm.
505 0 $a Presentations, Statistical Distributions, Quality Tools and Relationship to DoE -- Samples and Populations: Statistical Tests for Significance of Mean and Variability -- Regression, Treatments, DoE Design and Modelling Tools -- Two-Level Factorial Design and Analysis Techniques -- Three-Level Factorial Design and Analysis Techniques -- DoE Error Handling, Significance and Goal Setting -- DoE Reduction Using Confounding and Professional Experience -- Multiple Level Factorial Design and DoE Sequencing Techniques -- Variability Reduction Techniques and Combining with Mean Analysis -- Strategies for Multiple Outcome Analysis and Summary of DoE Case Studies and Techniques.
520 $a This textbook provides the tools, techniques, and industry examples needed for the successful implementation of design of experiments (DoE) in engineering and manufacturing applications. It contains a high-level engineering analysis of key issues in the design, development, and successful analysis of industrial DoE, focusing on the design aspect of the experiment and then on interpreting the results. Statistical analysis is shown without formula derivation, and readers are directed as to the meaning of each term in the statistical analysis. Industrial Design of Experiments: A Case Study Approach for Design and Process Optimization is designed for graduate-level DoE, engineering design, and general statistical courses, as well as professional education and certification classes. Practicing engineers and managers working in multidisciplinary product development will find it to be an invaluable reference that provides all the information needed to accomplish a successful DoE. Presents classical versus Taguchi DoE methodologies as well as techniques developed by the author for successful DoE; Offers a step-wise approach to DoE optimization and interpretation of results; Includes industrial case studies, worked examples and detailed solutions to problems.
650 0 $a Engineering $x Experiments. $3 531641
650 0 $a Manufacturing processes $x Experiments. $3 3592671
650 0 $a Experimental design. $3 524737
650 1 4 $a Engineering Design. $3 891033
650 2 4 $a Statistical Theory and Methods. $3 891074
650 2 4 $a Industrial Design. $3 890946
650 2 4 $a Industrial and Production Engineering. $3 891024
650 2 4 $a Business and Management, general. $3 2162672
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
856 4 0 $u https://doi.org/10.1007/978-3-030-86267-1
950 $a Engineering (SpringerNature-11647)