presentazione standard di powerpoint · 2018. 9. 26. · datascientist • highly qualified and...
TRANSCRIPT
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17 Giugno 2016 - #FUTUREFACTORYTVbeanTech
MANUFACTURING ANALYTICSDAL DATO AL VALORE PER IL BUSINESS
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VISION
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IT INFRASTRUCTURE
SOFTWARE APPLICATIONS
BUSINESS ANALYTICS
CRM
AREAS
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2001Foundation Year
>300Clients
>15Countries
4,5MTurnover
45People
33Average Age
INFOGRAPHICS
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OUR TEAM
PRODUCT MANAGER• Knowledge of the offering, of
possible applications and of R&D investments
• Ability to deal with different businesses
PROJECT MANAGER• Expertise in consulting and in
applied technologies • Responsible of the project
INFRASTRUCTURE ARCHITECT• Responsible for software and hardware
choices and for infrastructure dimensions
SOFTWARE ARCHITECT• Responsible for software development
and maintenance
DATA SCIENTIST• Highly qualified and specialized
profile• Cooperates with Full Professors and
Researchers in innovative projects
DATA ANALYST• Advanced technical and consulting
skills • Developing and testing ETL
processes and data models
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OUR APPROACH
VALU
E AD
DED
DEGREE OF INTELLIGENCE
1. DESCRIPTIVE
2. DIAGNOSTIC
3. PREDICTIVE
4. PRESCRIPTIVE
What happened?Where did it happen?
Where is the problem?Why did this happen?
Where are we trending?
What optimization?How can I automate a decision?
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INFORMATION IS THE OIL OF THE 21° CENTURY, AND ANALYTICS IS THE COMBUSTION ENGINE.
Peter SondergaardSVP, Head of Research, Gartner Inc.
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DATA, INTELLIGENCE, ACTION
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OUR MAIN PARTNER
Part of DANIELI GROUP, it is a leading automationand software company, focused on providing valueadded automation, MES and BI software solutions
3Q Concept
1.137Level 1
Automation Systems
650Level 2
Automation Systems
35Level 3
Automation Systems
http://www.danieli.com/en/worlwide/business-units/danieli-automation.htm
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THE PARTNERSHIP
Different Know Hows
One Solution
• 10 years Partnership• 40+ Successful Projects• 20+ Covered Countries
Q3Intelligence
https://www.youtube.com/watch?v=0pHZngyANAQ
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LIVE DEMO
MONITORINGOur monitoring solutions offer a customizable and device-independent environment bycomparing the actual status with set targets, allowing to keep the plant performancesalways under control.
The design reflects a “top-down” approach. It starts with the monitoring of business KPIsand tracks production down to single product details.
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LIVE DEMO - MONITORING
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LIVE DEMO - MONITORING
Detail KPI Section
Product Details
Plant KPIs
Period Selection
Extra Contents
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LIVE DEMO - MONITORING
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LIVE DEMO - MONITORING
Multi-Device
Responsive Design
Multimedia Integration
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LIVE DEMO
ANALYTICSOur Analytics solutions for the Process Control System allows to access the historicalinformation to support strategic decisions, increasing efficiency & productivity.
This lets you make proactive actions through comparisons and correlations, between differentplant areas’ performances and quality results, in order to continuously drive the processtowards the desired goals.
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PLANT DATA MODEL
PROCESSVARIABLES
CUSTOMER REQUIREMENTS
CONSUMPTION
STOCKYARD
QUALITY INSPECTION
PLANNING & SCHEDULING
FINAL PRODUCTS
SHIPPING
CHEMICAL ANALYSIS
PRODUCTION TIMES
KPI LIBRARY
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LIVE YOUR DATA
• The #1 data analysis tool on the planet
• Available on every device
• Flexible ad-hoc analysis
• Drill to and through
• Rich visualization
• Lot of data sources
• Used also for sharing
Connect & Analyze:Excel: The mostly used data analysis tool
Share & Consume:Power BI: Your data, every time, everywhere
• Get data from cloud and on-premises sources
• Live dashboards
• Native apps for iOS, Android and Windows
• Share and collaborate with colleagues through O365 groups
• Natural language query
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LIVE DEMO - ANALYTICS
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LIVE DEMO - ANALYTICS
Business Monitoring Unified Data
Models
Analysis Templates Interactivity &
Customization
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LIVE DEMO - ANALYTICS
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LIVE DEMO - ANALYTICS
Self BI
Your Data, Everywhere
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LIVE DEMO
PREDICTIVEWith the state-of-the-art statistical tools, users can do advanced mining of plant data,including multivariate regressions as well as clustering and classification analyses.
Thanks with our consulting services, basing also on complex machine learning algorithms, weprovide valuable insights into plant operations and performances.
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TECHNOLOGIES: OUR CHOICES
• Machine learning is a scientific discipline that explores the construction and study of algorithms that can learn from data
• In industrial contexts, machine learning methods may be referred to as predictive analytics or predictive modelling
• Azure ML is a fully-managed cloud service that enables to efficiently embed predictive analytics into applications, helping organizations benefit from massive data sets
• It is where data science, predictive analytics, cloud resources, and your data meet
• Azure ML supports R and Python custom code
• R is an environment for advanced statistical computing and graphics
• R is widely used in both academic and industrycommunities
• R relies on an active community of developers and algorithm experts, getting available:
• Standard statistical techniques
• Machine learning and in general more complex analysis packages/tools
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PREDICTIVE SLA COMPLIANCE
• Predict quality conformity of final products (in terms of mechanical properties) using production process variables as classifiers
• Use the prediction model to support operational activities:
• Offline: product type and process analysis• Online: fine tuning of the manufacturing process piece by piece
• Analysis of historical production data collected by Q3Intelligence
• Integration of Microsoft Azure Machine Learning resources (services and algorithms) for setting up an advanced and cloud-based analytics framework
• Ready-to-use prediction service
• To reduce the amount of products to be tested
• To reduce the percentage of out-of-spec final products thanks to a better knowledge of the machine/operation under analysis (e.g: adjusting the set-up according to results)
• To fine tune process variables in real-time and make products that are in line with specifications
WHAT?
HOW?
WHY?
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EXPERIMENT SETUP
Training Prediction
Plant Production Data
Data Loading
Application
Predictive Experiment
Machine Learning Experiment
Data Preparation
Regression Prediction
Direct Classification
Prediction
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EXPERIMENT KPIs
2Years of Data
11,5kProducts
5Production Areas
138
>2B
1Multidisciplinary
TeamSamples
Process Variables
97,5%Predictions in Range
10’
<1’’ Response Time
Training Time
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LIVE DEMO - PREDICTIVE
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LIVE DEMO - PREDICTIVE
Azure ML
Tools
ML Experiment
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LIVE DEMO - PREDICTIVE
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LIVE DEMO - PREDICTIVE
• What-If Analysis• Estimate Final Product Quality
during Production• Identify Process Variables most
influent on Product Quality
Iterative Prediction
Statistical Analysis
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Grazie per l’attenzione!
MANUFACTURING ANALYTICSDAL DATO AL VALORE PER IL BUSINESS