welcome [tc18.tableau.com] · let’s talk about where we started datacom transmission &...
TRANSCRIPT
Welcome
Data Innovation at the Speed of LITE: How Lumentum is driving a zero defect culture from engineer to executive
Stephanie Vierus
Data Scientist
Lumentum
# T C 1 8
Overview
Lumentum Lumentum (NASDAQ: LITE) is a market-leading manufacturer of innovative optical and photonic products enabling optical networking and commercial laser customers worldwide.
SpeakerStephanie has over 18 years of engineering experience and has spent the past six years dedicated to supply chain data analytics. Previously, Stephanie wrote software for mathematical algorithms in high performance computing, and firmware for flagship supercomputers.
What are we going to talk about?
AgendaOur first year of transformation – First Pass Yield
Utilizing data to drive a zero defect culture
Continuing the journey
Questions and Answers
Data Innovation @ Speed of LITEOur first year
Let’s talk about where we started
Datacom Transmission & Transport
Commercial Lasers 3D Sensing
October 2017Report Mechanisms
Manual and taking months to generate static reports Inconsistent without a standard measurement methodologyHidden in emails, share points, and desktops
Data Landscape Diverse product sets spanning multiple markets Various test platformsGlobal with 8 manufacturing locationsDisparate databases, 30 and counting
DemandsCustomers requesting real time data analytics!
Introducing a new way: First Pass Yield1. Standard definition and certified views updated at least daily
2. Consistency and linkage for single source of truth CEO to Engineer
3. Focused and appropriate details for each user role
Executive Business Unit Engineering & QualityStandard measure for all segments Multiple product lines Details to drive action
Pre-Tableau Tableau
Frequency Once a month (manual) Twice daily (automated)
Source Static report generate, outside of process Connected to test systems, embedded in process
Definition Subset of population Entire population
Data Grain Aggregated values, with limited attributes Unit serial number for a given test run, with all attributes available
Access Share Point, Emails, Meetings Tableau Online
Effort Preparing reports Acting on data
Next Steps Follow up with engineer Drill into data, alert engineers, extend VIZs
Result
Impact of Change
Engage a Company
Enable Users
• Tableau self based training
• Host Tableau Day
• Boot Up Sessions to groups
• Data Dictionaries
Tableau Site
• Architecture of flow
• Embed User Guides into VIZ
• Enable easy navigation for site
• Control certified VIZs & data sources
Monitor / Support
• Monitor Track user visits
• Ongoing expansion of content
• Partner with Kaizen Promotion Office
Data Innovation @ Speed of LITEDriving a zero defect culture
Building a data culture
Data analytics is a team sport
All three parties must be present in order to create successful insights
As a team, we strive to bring insight into
• manufacturing processes
• customer experiences
• business questions
• ad hoc analysis
• data exploration
Data Steward
•Owns & collects data
•Ensures correctness
•Provided access
•Optimizes bottlenecks
Subject Matter Expert
•Understands process
•Puts data into context
•Understands the product
• Feels pain points
Tool Expert
•Helps Visualize Data
• Standardizes metrics
•Drives Action from data
•Builds tools to enable organization
What had to be built for the data to flow?
Tableau Online
Licenses
Collaborate with data stewards
and subject matter experts
Subject matter experts identify
what they need
Data Stewards provide
access the data
sources
Data blending,
calculations, and viz
generations
Collaborate with the subject matter
experts/ gain insights
Automate dashboards
Dig deeper
A perfect pair: data analytics and Kaizen
• Just providing data to a new set of users is only half the battle
• Pairing the power of analysis and Kaizen tools to utilize the data generates results
1. Identify yield issue with new
dashboard
2. Setup Kaizen team, use PDCA
methodology
3. Monitor Results –zero defect is
possible
In one year what type of success can there be?
• 80%+ Data Coverage off revenue generating products
• Double digit yield improvement
• Data to the people!
• Reached 100% of executives & 30% of engineers
• Allowed key customers & CMs to access to their VIZs
• Removed report generation tasks
• Single source of truth
• CEO, engineers, customers all talking about data
• Quality metrics integrated into employee bonuses
• Continuous improvement with better goal setting
Business Unit Yield Improvement
Datacom 24%
Transmission & Transport 18% - 23%
Commercial Lasers 20%
3D Sensing 26%
Better Goal Setting : Bad Tester Detection
Data Innovation @ Speed of LITEContinuing the journey
Next Generation Tools
• Wafer Modeling• Bullseye
• Outer Ring
• Block
• Data Driven Alerts• Parametric
• Yield Loss
• Test escapes
• Idle equipment
• Statistical Controls• SPC
• Bad Tester
• Tool Interaction affects
What’s Next
• Scale
• Tackle the harder problems
• More advance analytics
• Empower and grow data culture across the company
Questions & Answers
Thank You!!
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What’s Next
• Scale
• Tackle the harder problems
• More advance analytics
• Empower and grow data culture across the company
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var pd = require('pretty-data').pd;
var xml_pp = pd.xml(data);
var xml_min = pd.xmlmin(data [,true]);
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var css_min = pd.cssmin(data [, true]);
var sql_pp = pd.sql(data);
var sql_min = pd.sqlmin(data);
Sample Code
var pd = require('pretty-data').pd;
var xml_pp = pd.xml(data);
var xml_min = pd.xmlmin(data [,true]);
var json_pp = pd.json(data);
var json_min = pd.jsonmin(data);
var css_pp = pd.css(data);
var css_min = pd.cssmin(data [, true]);
var sql_pp = pd.sql(data);
var sql_min = pd.sqlmin(data);
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