Data Analysis Tools and Methodologies for Quick Yield Learning in a High Volume Manufacturing Environment

2000 ◽  
Author(s):  
L. Andrade ◽  
T. Taylor
Keyword(s):  
Data Analysis ◽  
Random Access ◽  
Final Analysis ◽  
High Volume ◽  
Analysis Tool ◽  
Analysis Tools ◽  
Minimal Cycle ◽  
Yield Learning ◽  
Efficient Data ◽  
Using Data

Abstract High volume products in manufacturing require fast yield learning, root cause identification, and verification that process or tool problems are fixed. Yield losses of 1% correspond to very large dollar losses. Therefore, it is important to have sophisticated data analysis tools that handle large volumes of data to drive higher yields. This paper will present our methodology for defining yields, assessing wafer yield signatures, and using data analysis tools to determine tools or processes which drive yield loss. A SAS based data analysis tool will be shown which can identify tool or process related problems causing abnormalities in parametrics and impacting yield. Case studies illustrating the usefulness of the tool are shown for a Synchronous Dynamic Random Access Memory (SDRAM) product from our wafer fab. In the final analysis, it is clear that an efficient data analysis approach utilizes resources most effectively and pinpoints yield problems with minimal cycle time.

Tampa Electronics: An Instructional Case in Computer-Assisted Fraud Examination

2010 ◽  
Vol 25 (3) ◽  
pp. 547-552 ◽  
Author(s):  
Uday S. Murthy
Keyword(s):  
Data Analysis ◽  
Computer Assisted ◽  
Analysis Tool ◽  
Case Scenario ◽  
Analysis Techniques ◽  
Microsoft Access ◽  
Open Source Data ◽  
Using Data ◽  
Basic Features ◽  
Travel Expense

ABSTRACT: This case is designed to impart practical skills in data analysis techniques aimed at fraud examination. Instructors could employ any one of widely available tools such as ACL, IDEA, Microsoft Access, or Picalo, which is an open-source data analysis tool. Couched in the context of a manufacturer of electronic components in the southeastern United States, the case involves the identification of potentially fraudulent travel expense reimbursements. In the case scenario, traveling salespersons submit expense reimbursement claims, which are subject to a number of business rules. Using data analysis techniques, students are required to identify potentially fraudulent travel expense reimbursements. The data analysis techniques covered in the case include basic features such as identifying duplicates and gaps to more advanced features like joining tables, finding unmatched records, filtering data based on various criteria, and classifying and summarizing data. The degree of structure provided to students is within the control of the instructor, with less structure making for a more realistic and challenging assignment. Spreadsheet files containing the travel expense data are designed to facilitate easy changing of numbers between semesters.

scholarly journals Forecasting air pollution load in Delhi using data analysis tools

2018 ◽  
Vol 132 ◽  
pp. 1077-1085 ◽  
Author(s):  
Nidhi Sharma ◽  
Shweta Taneja ◽  
Vaishali Sagar ◽  
Arshita Bhatt
Keyword(s):  
Air Pollution ◽  
Data Analysis ◽  
Pollution Load ◽  
Analysis Tools ◽  
Using Data

scholarly journals Development of International Agricultural Trade Using Data Mining Algorithms-Based Trade Equality

2021 ◽  
Vol 2021 ◽  
pp. 1-9
Author(s):  
Liu Yan
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Agricultural Trade ◽  
Machine Learning Techniques ◽  
Trade Data ◽  
Data Mining Algorithms ◽  
Efficient Data ◽  
Using Data ◽  
Analysis System ◽  
Data Analysis System

The development of international agriculture trade during the COVID-19 pandemic has encountered significant challenges. The processing of international agricultural trade data using machine learning techniques needs to be improved to perform effective analysis of agricultural trade. An essential issue for international agricultural trade is the accurate yield estimation for the numerous crops involved in international trade. Data mining techniques are the necessary approach for accomplishing practical and effective solutions for this problem. This paper combined the bidirectional encoder representations from transformers (BERT) model to conduct data mining and developed a trade data analysis system with efficient data analysis capabilities. Our results indicate that our model does reasonably well and obtains adequate information in deciding international agricultural trade. It can also be instrumental for policy and decision-making regarding international agricultural trade.

scholarly journals LevelFilesSet: An efficient Data Structure for Scalable Web Tiled Map Management Systems

2019 ◽  
Vol 2 ◽  
pp. 1-10
Author(s):  
Menelaos Kotsollaris ◽  
William Liu ◽  
Emmanuel Stefanakis ◽  
Yun Zhang
Keyword(s):  
Data Structure ◽  
Data Structures ◽  
File System ◽  
Hybrid Approach ◽  
Random Access ◽  
Management Systems ◽  
Efficient Data ◽  
Using Data ◽  
System Configurations ◽  
Map Management

<p><strong>Abstract.</strong> Modern map visualizations are built using data structures for storing tile images, while their main concerns are to maximize efficiency and usability. The core functionality of a web tiled map management system is to provide tile images to the end user; several tiles combined construe the web map. To achieve this, several data structures are showcased and analyzed. Specifically, this paper focuses on the SimpleFormat, which stores the tiles directly on the file system; the ImageBlock, which divides each tile folder (a folder where the tile images are stored) into subfolders that contain multiple tiles prior to storing the tiles on the file system; the LevelFilesSet, a data structure that creates dedicated Random-Access files, wherein the tile dataset is first stored and then parsed in files to retrieve the tile images; and, finally, the LevelFilesBlock, a hybrid data structure which combines ImageBlock and LevelFilesSet data structures. This work signifies the first time this hybrid approach has been implemented and applied in a web tiled map context. The JDBC API was used for integrating with the PostgreSQL database. This database was then used to conduct cross-testing amongst the data structures. Subsequently, several benchmark tests on local and cloud environments are developed anew and assessed under different system configurations to compare the data structures and provide a thorough analysis of their efficiency. These benchmarks showcased the efficiency of LevelFilesSet, which retrieved tiles up to 3.3 times faster than the other data structures. Peripheral features and principles of implementing scalable web tiled map management systems among different software architectures and system configurations are analyzed and discussed.</p>

AKTUALISASI PEDIDIKAN KARAKTER DALAM PENGEMBANGAN REVOLUSI MENTAL BERBASIS ADIWIYATA DAN MULTIKULTURAL

2018 ◽  
Vol 2 (2) ◽  
Author(s):  
Suhardi Suhardi
Keyword(s):  
Data Analysis ◽  
Character Education ◽  
Achievement Motivation ◽  
Case Study Research ◽  
Individual Development ◽  
Human Beings ◽  
Soft Skill ◽  
Design Data ◽  
Strategic Role ◽  
Using Data

Mental revolution of education requires efforts to print educated human beings by having the motivation to meet the standards of achievement excellence, such as ethos of progress, ethics, achievement motivation, discipline, optimistic, productive, innovative and active views. This can be implemented with character education. Character education is one of the soft skill tools that can be integrated in learning in each subject. Learning activities using an active learning approach have a strategic role in instilling national character values so that students are able to behave and act on values that have become their personality. The purpose of this study was to find and analyze about: 1) Implementation of Character Education to Build Adiwiyata-Based Mental Revolution and Multiculturalism; 2) Implementation of Character Education to Build Mental Revolution in Organizational Culture. This study uses a qualitative approach with phenomenological naturatistics (phenomenology approach), with a descriptive type of case study research design. Data were analyzed using data analysis techniques: data reduction, data analysis and conclusions. The results of the study are: The application of character education to develop a mental revolution can be started from the character of building the environment. Environmental character is very important for individual development. The implementation of character education in building a mental revolution can emphasize the internalization of multicultural values and Adiwiyata which in the end will form a loving environmental awareness and foster a spirit of tolerance.

Peranan Ketua Pengurus dan Manajer Dalam Penyusunan dan Penerapan Laporan Keuangan Berbasis SAK ETAP Pada Koperasi di Kota Palembang

2019 ◽  
Vol 14 (2) ◽  
pp. 119
Author(s):  
Riza Syahputera ◽  
Martha Rianty
Keyword(s):  
Data Analysis ◽  
Sampling Technique ◽  
Financial Statements ◽  
Significant Positive Effect ◽  
Analysis Technique ◽  
Regression Test ◽  
Using Data ◽  
The City ◽  
Positive Effect

AbstractThis study aims to determine the effect of the role of the Chairperson and Cooperative Manager in the preparation and application of Financial Statements based on SAK ETAP in cooperatives in the city of Palembang. This research is a quantitative study using data obtained from questionnaires and measured using a Likert scale. The sampling technique used is purposive sampling. The sample used in this study was the Chairperson of the cooperative and the manager of the cooperative in the city of Palembang. The cooperatives studied were 203 cooperatives. The data analysis technique used is multiple linear regression test. The results showed that the role of cooperative leaders and managers had a significant positive effect on the preparation and application of SAK ETAP-based financial statements.Keywords : chairman, manager, SAK ETAP, cooperative

K-MEANS CLUSTERING ALGORITHM FOR SERVICE DATA ANALYSIS BASED ON CUSTOMERS COMBINATION

2018 ◽  
Vol 3 (1) ◽  
pp. 001
Author(s):  
Zulhendra Zulhendra ◽  
Gunadi Widi Nurcahyo ◽  
Julius Santony
Keyword(s):  
Data Mining ◽  
Data Analysis ◽  
Clustering Algorithm ◽  
Customer Complaints ◽  
Using Data ◽  
Clustering Data ◽  
Service Data ◽  
Selection Of

In this study using Data Mining, namely K-Means Clustering. Data Mining can be used in searching for a large enough data analysis that aims to enable Indocomputer to know and classify service data based on customer complaints using Weka Software. In this study using the algorithm K-Means Clustering to predict or classify complaints about hardware damage on Payakumbuh Indocomputer. And can find out the data of Laptop brands most do service on Indocomputer Payakumbuh as one of the recommendations to consumers for the selection of Laptops.

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