Training Services
Syntricity Training Services are designed to accelerate your implementation and enable your users and administrators to manage your Enterprise Yield Management system more effectively.
In order for your users and administrators to reap the full benefits of dataConductorEP and address complex issues arising from your product data, we recommend advanced feature training to ensure success and application expertise. Syntricity offers comprehensive training led by seasoned experts in semiconductor manufacturing practices, statistics, and data analysis. Our training courses covers all aspects of the dataConductor product, as well advanced topics for Product Engineering professionals, regardless of the Analysis and Yield Management tools currently in use at their companies.
At Syntricity, we make educating your users and administrators easy:
Instructor-Led Training
Whether you visit us in San Diego, CA, or we visit you at your offices, our instructors will teach your users and administrators in a live classroom setting. In addition to our standard training offerings, we offer the option of using course materials customized to your data, or even creating customized courses to suit your particular training needs. In an instructor-led setting, most classes provide hands-on excercises, and lots of Q&A.
Online Training
To make learning applications convenient and accessible for all users and administrators, Syntricity also offers online training. Our online training is the perfect opportunity to increase your skills and knowledge in an interactive and collaborative environment.
To learn more about how our training can help you, contact us at training@syntricity.com.
Introduction to dataConductor
Gain a basic understanding of the dataConductor interface. Learn how to navigate throughout the user interface. Understand basics of querying the warehouse for data of interest. Learn about Power Tools, AMP, SYM, and SQL Access.
Topics covered: Searching for data, simple power tools analysis, binder creation, data insertion, scheduling jobs, macros.
This course is a prerequisite for all other dataConductor courses.
dataConductor Administration
The core of a successful deployment of dataConductor is the resourcing of the dataConductor Administrator role. Learn about the warehouse structure and rules. Understand the importance of managing the data. Learn the various aspects of administering dataConductor. Identify your role in facilitating data analysis for your engineers.
Topics covered: Basic dataConductor User Interface overview, warehouse structure and rules, data uniqueness and ramifications, the role of the dataConductor maskset, data lifecycle management process and policy development, dataConductor administration, customizing the application for your engineers, maintaining the application.
Prerequisites: None
dataConductor Statistics
Gain a deeper understanding of the statistical techniques implemented within dataConductor.
Topics covered: Summary statistics, such as mean, standard deviation, skewness, kurtosis, and percentiles; confidence intervals for means and variance; graphical methods, such as histograms, boxplots, and normal probability plots; inference, including p-values, t-tests, paired t-tests and one-way ANOVA.
Prerequisites: None
Process Capability
In this introduction to Process Capability indices, you will learn about the appropriate use of Cp and Cpk, and how to interpret them. This course is designed for all Semiconductor Product Engineers, regardless of the analysis tools used to get the job done.
Topics covered: Key assumptions and issues underlying the interpretation of Cp and Cpk, including stability, measurement error, sampling error, distributional assumptions, and process centering; Z-scores, margin, gauge metrics, interpreting Cp and Cpk in terms of yield, graphical methods, case studies, and an introduction to Cnpk.
Prerequisites: None
Introduction to Control Charts
Would you like to know more about the use of Control Charts? Think you already know when and how to use them? Learn about Control Charts and their appropriate use, and the limits of their use.
Topics covered: Control chart background and history, control chart statistics, why control chart ‘rules' don't make a lot of sense for the typical ‘after the fact' analysis, and control chart calculations (where the lines come from). We cover several examples and cases, including Multiple views of a dataset, showing boxplots and control charts for a simple dataset; A WAT parameter with a distinct pattern across wafers; A WAT parameter with no variation per wafer; Looping on a package part X number of times – a quick repeatability study; Gauge R&R data – using control charts to check measurement error; Checking spec limits with control charts; Control charts for a series of related test parameters; An example of how control chart rules are (primarily) based on plot order.
Prerequisites: None
Gauge R&R I
Learn about Gauge R&R Studies in Part 1 of this two-part course.
Topics covered: Terms, tools, and techniques that form the basis for gauge studies; the gauge r&r measurement error model, properties of variance, and analysis of variance; a sample gauge r&r study.
Prerequisites: None
Gauge R&R II
In Part 2 of this two-part course, learn about gauge metrics, and more about Gauge R&R studies.
Topics covered: Introduction to gauge metrics; a detailed discussion of a gauge r& r study; data collection and analysis suggestions; guidelines and suggestions for using gauge metrics.
Prerequisites: Gauge R&R I
Introduction to SYM and AMP
Learn allow about our Advanced Monitoring for Production (AMP) and Supplier Yield Management (SYM) products.
Topics covered: How SYM can help you manage your suppliers; Exporting results; Continuing your SYM analysis in AMP and RaCR; Supplier Yield Management Summary and Drilldown reports; Tour of the AMP reports; Material Selection; Continuing your AMP analysis in SYM and RaCR; Correlating to WAT data; Filtering Data
Prerequisites: None
Implementing MES in dataConductor
In this course you will learn about integrating MES feeds into dataConductor, and the benefits that flow from having your MES data together with your production test data.
Topics covered: Benefits of MES integration; Cross-operation correlation; MCM/SiP traceability; Traditional YMS implementations vs. dataConductor MES; Implementing MES; The MES Information Model; Genealogy.
Prerequisites: None
Introduction to RaCR
Learn how to use our next-generation Analysis application RaCR (Rapid Characterization and Root Cause Analysis).
Topics covered: Typical workflows; Understanding and using templates; Exporting results; The Gauge R&R application in RaCR.
Prerequisites: None
Automated Reporting and Publishing
In almost every organization, periodic reports are published and distributed. These reports could be anything from high level quarterly reports down to daily or weekly lot-level reports. Other reports often used in manufacturing are process monitoring and excursion reports, supply chain monitoring reports and QA reports. In this course, you will learn how to use macros in dataConductor to automate analysis tasks, how to create reports to publish the results, and how to put the two together to establish the desired automated reporting and publishing.
Topics covered: Creating, editing, and combining macros; sharing macros; creating binders; sharing binders; exporting and managing binders; running and scheduling macros.
Prerequisites: None
Understanding the SAF and STDF Data Formats
Grow your knowledge of the correct implementation of the SAF and STDF data formats in this course.
Topics covered: SAF capabilities; the structure of a SAF file; SAF examples; Review of STDF definition; Adding conditions to your STDF files; Mapping STDF into dataConductor.
Prerequisites: None
Introduction to SQL Access
Learn about how SQL Access can be used to create custom queries of data from the dataConductor warehouse.
Topics covered: Overview of SQL Access capabilities; Review of the dataConductor warehouse structure; Configuring JMP and Excel to access the dataConductor warehouse; Review od SQL Access Schema
Prerequisites: None