IoT e Industria 4.0. evoluzione e intelligenza aumentata

(in lingua inglese)

- Key Challenges
- The nex wave of digital reinvented manufactoring use cases
- Execution: Traditional technologies - 3.0 to support operations
- Execution: Advanced Technologies - 4.0 to support operations
- Logical steps to realize the benefit
- IBM Watson IoT for Manufactoring drive cost saving and operational effiency across the factory value chain

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Atti di convegni o presentazioni contenenti case history
SAVE Milano aprile 2018 Industria 4.0, evoluzione tecnologica e nuove agevolazioni

da Alessia De Giosa
SAVE Milano 2018Segui aziendaSegui


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Estratto del testo
Gli atti dei convegni e pi di 9.000 contenuti su Milano 2018 IBM Corporation IoT e Industria 4.0: Evoluzione tecnologica e Intelligenza Aumentata Andrea Boccotti
IoT and Industry 4.0 Solution Leader
m +39-348-13 18 566 2018 IBM Corporation 2 Manufacturing companies are facing many of the same strategic and operational chal enges We need to maximize asset
uptime and stability We need to decrease
maintenance and field
service costs We need to drive
customer experience
by providing a flawless
customer service We have assets
deployed al over the
place and need an
orchestrated repair
process We need to
improve pro-
activeness in all
parts of the
organization We need to shift
workload from field
service to remote
service We want to
through a data-
driven approach We should plan our
service on condition
repairs instead of time-
based maintenance We need to find new
sources of revenue by
moving to new
models 2018 IBM Corporation 3 Key Chal enges Incompatible
Standards Fundamental Shifts in
Business Models Unprecedented
Data Volumes New Privacy
Landscape Entirely New
Security Threats ' Sensors generating new
kinds of data, as well as
volumes 1000's of times
higher than pre-IoT systems. ' Big data and machine
learning required to
complement traditional
reporting and analytics. ' One-time purchases being
transformed into 'pay as you
grow' long term revenue streams. ' Traditional manufacturing and
place-based businesses must
become IT-centric organizations. ' Proliferation in competing platforms and incompatible standards raises costs and complexity, security risks,
and time-to-market for IoT innovators. ' Col ecting physical world data on people and objects. ' Market is slow grasping implications - stiffer
regulations are likely. ' Devices no longer
contained and protected in
data centers. ' Automobiles, plants and
medical devices are under
growing attack. New Competences
Required ' Companies are transforming in a software companies, and right skil s need to be acquired ' Advanced Data Analysis in becoming day by day more important, data scientist and data architects skil s required New Organization
Required ' Chief data office has to be created ' Dev-Ops : R&D + production and Post Sales to support
product update, post sales management ' Customer Success management : Marketing, Sales and Post Sales
Support 2018 IBM Corporation 4 Connected Sales & Marketing Connected Operations Connected Products Customer Insights and Opportunities Flexible Bil ing and Pricing Models New Value Added Services Connected Product Usage Analysis Connected Product Quality Analysis Connected Software Management Asset and Materials Tracking Connected Operations Intel igence Unified Key Performance Indicators Real-Time Asset Health Monitoring Operation Management Improvement 4 The Next Wave of Digital Reinvented Manufacturing Use Cases 2018 IBM Corporation 5 Connected Customers Connected Services & Support Connected Information & Operation Technology Monitoring and Diagnostics Remote Services Automated Service Execution Condition-based Predictive
Maintenance Connected Service Parts Planning Warranty Cost Management Usage and Performance Dashboard Customer Self-Service Product Personalization Flexible Product and Asset Connectivity Identify and Security Management Scalable IoT Operation Management Seamless IoT Data Integration Automated Analytics and Actions Rapid IoT Application Development 5 The Next Wave of Digital Reinvented Manufacturing Use Cases 2018 IBM Corporation 6 EXECUTION: TRADITIONAL TECHNOLOGIES- 3.0 - TO SUPPORT OPERATIONS ' Data give 3.0 maturity
indication, as precondition
to start 4.0 projects ' From design solution
(CAD), automation,
warehouse and PDM
companies are ready to
move to industry 4.0 ' More advanced solutions
are still not fully adopted Quali tecnologie avete adottato/state adottando a supporto dei processi di sviluppo prodotto, gestione delle operations e gestione della supply chain' 16% 21% 22% 34% 40% 42% 45% 50% 61% 73% 10% 11% 13% 19% 16% 7% 13% 14% 4% 4% 20% 19% 19% 18% 21% 16% 15% 12% 7% 4% 46% 47% 33% 26% 21% 25% 19% 21% 17% 10% 8% 2% 13% 4% 2% 10% 8% 3% 10% 9% 0% 20% 40% 60% 80% 100% Computerized Maintenance Management System (CMMS) Safety Management (SM), Governance Risk and Compliance (GRC) Sistemi di Product Lifecycle Management (PLM) Advanced Planning & Scheduling (APS), schedulatore Piattaforme web di collaborazione con fornitori, clienti Sistemi di Product Data Management (PDM) Manufacturing Execution System (MES), sistemi di controllo avanzamento produzione Warehouse e Management System (WMS) Automazione industriale Strumenti di supporto alla progettazione (CAD 2D/3D, software per FEM e CFD) Adottata da tempo Adottata da poco In corso di valutazione Non adottata Non applicabile nella nostra azienda Fonte: Industria 4.0 in Italia: Vision & Execution Panel 135 Aziende 2018 IBM Corporation 7 EXECUTION: ADVANCED TECHONLOGIES- 4.0 ' TO SUPPORT OPERATIONS ' Relevant presence of
Advanced Automation, but
still prevail on not
applicable or not adoption ' Industrial Analytics and
Industrial IoT produce
great interest ' Insufficient knowledge how
Cloud can change the way
to make production:
cultural issue ' Additive Manufacturing is a
'process technology' with
limited usage ' Risk that in the gray
zone is hide knowledge
lack ' Importance test and PoC Quali tecnologie avete adottato/state adottando a supporto dei processi di sviluppo prodotto, gestione delle operations e gestione della supply chain' Panel 135 Aziende Fonte: Industria 4.0 in Italia: Vision & Execution 2018 IBM Corporation 8 Logical steps to realize the benefit Gather the data Visualize the patterns Advance to analytics Infuse with cognitive ' Instrument your
equipment/assets to
col ect data ' Gather already
existing data ' Visualize your data in
dashboards ' Start to see patterns ' Build with Bluemix ' Gain insights from
the data ' Produce models,
recommendations ' Refine models with
cognitive machine
learning ' Utilize other cognitive
functions to improve
engagement Asset needs to be connected,
outfitted with sensor or data
gathered Use analytical models to
predict equipment failures and
provide recommendations Use the platform to
quickly build dashboards
for data visualization Use speech, video, image
to diagnose complex
problems 2018 IBM Corporation 9 Image Analytics Enables monitoring of unstructured data from images snapshots to identify quality defects and failure patterns Machine Learning Automates data processing, identifies the best model for the data and continuously monitors new data to learn and improve results Textual Analytics Enables mining of textual sources to find correlations and patterns in structured and unstructured text such as logs and notes Acoustics Analytics Utilizes audio as an additional source of unstructured data to enable anomaly detection and pattern recognition Equipment Advisor Visual Inspection Audio Insights Plant Advisor Begin the journey to cognitive with use case driven application for value 2018 IBM Corporation 10 IBM Watson IoT for Manufacturing drive cost savings and operational efficiency across the factory value chain Intel igent assets and equipment Cognitive processes and operations Smarter resource and optimization Intelligent assets and equipment utilizes IoT and cognitive capabilities
to sense, communicate and self-
diagnose issues
so they can optimize
their performance and reduce
unnecessary downtime Cognitive operations and processes bring more certainty to business by
analyzing a variety of information from
workflows, context and environment to
drive quality, enhance operations and
decision-making. Utilize IoT and cognitive insight to optimize resources (worker, energy,
using geolocation data,
individual data, usage data and
environmental conditions along with
analytics. IBM$Watson$IoT$Platform 34% Decrease in equipment downtime at major global auto manufacturer 25% Increase in overal productivity at major European automaker 8% Annual saving in energy cost at IBM facilities 2018 IBM Corporation 11 Andrea Boccotti IoT and Industry 4.0 Solution Leader +39-348-13 18 566

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