digital disruption in steel - futuresteelforum.com & demand planning supply chain optimization...
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Digital Disruption in SteelManish Chawla, GM, Global Industrial Products @ [email protected]
@mcchawla2manishchawla1
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Topics
Introduction
Cognitive Value Chain – Our approach to Industry 4.0
Ecosystems – The Path to Value
Concluding Thoughts
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Three shifts are transforming our industry
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The manufacturing industry will see the highest impact from these shifts
Hence, we believe that digital is not the destination. It is the foundation… Cognitive becomes the real game changer.
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Topics
Introduction
Cognitive Value Chain – Our approach to Industry 4.0
Ecosystems – The Path to Value
Concluding Thoughts
7© 2017 IBM Corporation7
Cognitive & analytics CloudMobile
Internet of ThingsSecurity
Social
Material Balancing
Shop Floor Control Physics-based Models
Preventative Maintenance
Failure Analysis
Asset Assurance
Process Safety
Production Scheduling
Supply & Demand Planning
Supply Chain Optimization
TelecommunicationsInfrastructure
Water Disposal
Big DataData Lakes
Autonomous Mobile Equipment
Federated Asset Models
Real-time Visualization
eLearning
Production Validation & Reporting
Materials R&D
Complex Event Processing
Mobile Computing
Predictive Analysis
Integrated Asset Operational Optimization
Semantic Knowledge Management
Material Integrity
Integrated Planning
Mobile Equipment Monitoring & Health
Material Genealogy
Training SimulationCorrosion Prediction
Sensors
Equipment Effectiveness
Collaborative Work Environments
Interoperability
Energy Analytics
Semantic Technologies
AI-Based Assistant
MTTRModel Predictive Control
Prescriptive Analytics
Automated Tests
Water Management
AR/VRSecurity
Cyber Security
Robotics & Automation
Blockchain
IT/OT Integration
Automated Inspections
Strategic Procurement
Edge Computing
Storage (e.g. Data Lakes)
Context Based Visualisation
Geo fencingWearables
Industry 4.0 CONNECTED | INTEGRATED | INTELIGENT
Advanced Process Control
Digital Twins
Descriptive Analysis
Deep Learning
Technology is not the problem – What to do with is it is the question…
Machine Learning
Drones
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Gather the dataVisualise the patterns
Advance to analytics
Infuse with cognitive
• Instrument your equipment/assets to collect data
• Gather already existing data
• Visualise your data in meaningful dashboards
• Start to see patterns• Build with Bluemix
• Gain insights from the data
• Produce models, prediction recommendations
• Refine models with cognitive machine learning
• Utilise 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 visualisation
Use speech, video, image to diagnose complex problems
Embracing IoT for Operations through logical steps of value
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IBM Vision & Strategy to realize full potential of IoT and Industry 4.0
Specialized Model 1
Specialized Model n
On- Premise, OwnedProvide insights
Open LoopHuman Required for Action
CyberModel-1
CyberModel-2
CyberModel-n
Cloud-based, as a ServicePre-Defined / Automated Processes
Closed LoopHuman Supervision
Cloud-based, as a ServiceDynamic / Self Configured Processes
Closed LoopCognitive Value Chain / Human Collaboration
WatsonCyberModel-1
CyberModel-2
CyberModel-n
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Example: End-to-End Asset Management & Optimization in a Cognitive Value Chain
Planned maintenanceor unplanned breakdown
Work orders enteredand prioritized in
maintenance system Repair technicianget worker order
Repair technician does diagnostic and checks
spare parts availability
Repair is completed andmaintenance system updated
Spare parts replenished order is issued
AS-IS
EquipmentAdvisor
MaintenanceScheduling
TechnicianAdvisor
Spare PartsOptimization
Cyber
Physical
Predict anomaly& diagnose problem
Open work orderconsidering severity
Schedule maintenance to minimize production disruption
Technician assisted inrepair procedure, virtual shields protected Spare parts replenishment
automatedTO-BE
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IBM Approach to 4th Industrial Revolution
1 Leverages on existing infrastructure - physical equipments, systems and applications
2 Focuses on time to value: adopt powerful accelerators for fast value realization
3 Enables companies to exploit all sorts of data: structure, unstructured, internal, external
4 Leverages on powerful capability-rich Cloud and Cognitive Platform
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Topics
Introduction
Cognitive Value Chain – Our approach to Industry 4.0
Ecosystems – The Path to Value
Concluding Thoughts
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Manufacturing & Resources Ecosystem –An Example
Engineering, OEMs, Process Technology Resources & Manufacturing Maker of Things Operator of Things
IT / Network / Data Integrators and Industrial Automation
IT/OT Service Providers
ILLUSTRATIVE ONLY
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Topics
Introduction
Cognitive Value Chain – Our approach to Industry 4.0
Ecosystems – The Path to Value
Concluding Thoughts
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“The 7 Habits of Highly Digitally Effective Companies”
Cloud
Cognitive &Analytics
Mobile
Internet of Things Social
Security
New Focus
New Expertise
New Ways to Work Actionable
InsightResponsiveOperations
OrchestratedEcosystems
RestlessTalent New
Business Models
MarketActivationExperience
Cloud
Cognitive &Analytics
Mobile
Internet of Things Social
Security
Experience§Creating differentiating experiences for customers, clients, colleagues, and partners
§Driving the way the organization works (people, process and technology)
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Digital Reinvention TM: Self Funding Roadmap
New Experiences
New Technologies
New Channels
New Business Models
Product
Cus
tomer
New
Existing
NewExisting
Optimize
Grow
Reinvention
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Digital Disruption in SteelManish Chawla, GM, Global Industrial Products @ [email protected]
@mcchawla2manishchawla1