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

Production planning and control in s...

Chen, Tin-Chih Toly.

Linked to FindBook

Google Book

Amazon

博客來

Production planning and control in semiconductor manufacturing = big data analytics and Industry 4.0 applications /

Record Type:	Electronic resources : Monograph/item
Title/Author:	Production planning and control in semiconductor manufacturing/ by Tin-Chih Toly Chen.
Reminder of title:	big data analytics and Industry 4.0 applications /
Author:	Chen, Tin-Chih Toly.
Published:	Cham :Springer International Publishing : : 2023.,
Description:	vi, 100 p. :ill., digital ;24 cm.
[NT 15003449]:	Chapter 1. Big Data Analytics for Semiconductor Manufacturing -- Chapter 2. Industry 4.0 for Semiconductor Manufacturing -- Chapter 3. Cycle Time Prediction and Output Projection -- Chapter 4. Defect Pattern Analysis, Yield Learning Modeling and Yield Prediction -- Chapter 5. Job Sequencing and Scheduling.
Contained By:	Springer Nature eBook
Subject:	Semiconductor industry - Production control. -
Online resource:	https://doi.org/10.1007/978-3-031-14065-5
ISBN:	9783031140655

Production planning and control in semiconductor manufacturing = big data analytics and Industry 4.0 applications /
Chen, Tin-Chih Toly.

Production planning and control in semiconductor manufacturingbig data analytics and Industry 4.0 applications /[electronic resource] :by Tin-Chih Toly Chen. - Cham :Springer International Publishing :2023. - vi, 100 p. :ill., digital ;24 cm. - SpringerBriefs in applied sciences and technology,2191-5318. - SpringerBriefs in applied sciences and technology..

Chapter 1. Big Data Analytics for Semiconductor Manufacturing -- Chapter 2. Industry 4.0 for Semiconductor Manufacturing -- Chapter 3. Cycle Time Prediction and Output Projection -- Chapter 4. Defect Pattern Analysis, Yield Learning Modeling and Yield Prediction -- Chapter 5. Job Sequencing and Scheduling.

This book systematically analyzes the applicability of big data analytics and Industry 4.0 from the perspective of semiconductor manufacturing management. It reports in real examples and presents case studies as supporting evidence. In recent years, technologies of big data analytics and Industry 4.0 have been frequently applied to the management of semiconductor manufacturing. However, related research results are mostly scattered in various journal issues or conference proceedings, and there is an urgent need for a systematic integration of these results. In addition, many related discussions have placed too much emphasis on the theoretical framework of information systems rather than on the needs of semiconductor manufacturing management. This book addresses these issues.

ISBN: 9783031140655

Standard No.: 10.1007/978-3-031-14065-5doiSubjects--Topical Terms:

3626012
Semiconductor industry
--Production control.

LC Class. No.: HD9696.S42

Dewey Class. No.: 338.4762138152

Production planning and control in semiconductor manufacturing = big data analytics and Industry 4.0 applications /
LDR:02203nmm a2200337 a 4500 001 2314535
003 DE-He213
005 20220919123520.0
006 m d
007 cr nn 008maaau
008 230902s2023 sz s 0 eng d
020 $a 9783031140655 $q (electronic bk.)
020 $a 9783031140648 $q (paper)
024 7 $a 10.1007/978-3-031-14065-5 $2 doi
035 $a 978-3-031-14065-5
040 $a GP $c GP
041 0 $a eng
050 4 $a HD9696.S42
072 7 $a TGP $2 bicssc
072 7 $a TEC009060 $2 bisacsh
072 7 $a TGP $2 thema
082 0 4 $a 338.4762138152 $2 23
090 $a HD9696.S42 $b C518 2023
100 1 $a Chen, Tin-Chih Toly. $3 3443006
245 1 0 $a Production planning and control in semiconductor manufacturing $h [electronic resource] : $b big data analytics and Industry 4.0 applications / $c by Tin-Chih Toly Chen.
260 $a Cham : $b Springer International Publishing : $b Imprint: Springer, $c 2023.
300 $a vi, 100 p. : $b ill., digital ; $c 24 cm.
490 1 $a SpringerBriefs in applied sciences and technology, $x 2191-5318
505 0 $a Chapter 1. Big Data Analytics for Semiconductor Manufacturing -- Chapter 2. Industry 4.0 for Semiconductor Manufacturing -- Chapter 3. Cycle Time Prediction and Output Projection -- Chapter 4. Defect Pattern Analysis, Yield Learning Modeling and Yield Prediction -- Chapter 5. Job Sequencing and Scheduling.
520 $a This book systematically analyzes the applicability of big data analytics and Industry 4.0 from the perspective of semiconductor manufacturing management. It reports in real examples and presents case studies as supporting evidence. In recent years, technologies of big data analytics and Industry 4.0 have been frequently applied to the management of semiconductor manufacturing. However, related research results are mostly scattered in various journal issues or conference proceedings, and there is an urgent need for a systematic integration of these results. In addition, many related discussions have placed too much emphasis on the theoretical framework of information systems rather than on the needs of semiconductor manufacturing management. This book addresses these issues.
650 0 $a Semiconductor industry $x Production control. $3 3626012
650 0 $a Product coding $v Case studies. $3 3626013
650 1 4 $a Industrial and Production Engineering. $3 891024
650 2 4 $a Internet of Things. $3 3538511
650 2 4 $a Production. $3 2203137
650 2 4 $a Cyber-Physical Systems. $3 3591993
650 2 4 $a Semiconductors. $3 516162
710 2 $a SpringerLink (Online service) $3 836513
773 0 $t Springer Nature eBook
830 0 $a SpringerBriefs in applied sciences and technology. $3 1565541
856 4 0 $u https://doi.org/10.1007/978-3-031-14065-5
950 $a Engineering (SpringerNature-11647)