KoçDigital IoT Solution Portfolio
Platform360 Industrial IoT Solutions
using Azure Services
1
Platform360 Industrial IoT Solutions
USING MICROSOFT AZURE
TABLE OF CONTENTS
1 INDUSTRIAL IOT CHALLENGES
2 KOÇDIGITAL INDUSTRIAL IOT SOLUTIONS
3 INDUSTRIAL USE CASES
4 APPENDIX
2
Source: KoçDigital
Digital Transforms Manufacturing Projects
Manufacturing field workforce CIO, CDO, CTODecision
Makers
Variety of vendors for piecemeal
traceability
End-to-end manufacturing transparency
Governance
Automation Firms IoT firms, Digital Transformation firms
Suppliers
Monitor basic KPIs with manual input Connected Digital twin of manufacturing
Technology
Operational Needs Business Value
Incentive
3
WHY DO WE NEED INDUSTRIAL IOT?
Increase
Efficiency
Improve
Quality
Increase
Safety
4
OT
Security
Applications
and analytics
Communication
IoT Solution
IoT backbone/
platform
Connected Things
Services
KoçDigital is
IoT System Integrator
which provides
end-to-end solutions
Iot Solution Stack
Solution Ecosystem
Managed Services
5
Engaging in IIoT based digital manufacturing solutions create
substantial impact
Increase in
equipment uptime
10-20%
Industrial IoT creates business values, increases productivity, and customers gets/stays competitive
Throughput increase with
horizontal product line
optimization
5-10%
Reduction of unplanned
downtime
50-70%
Increase in engagement of
maintenance teams
35-50%
Source: KoçDigital Customer Insight
Reduction of spare
parts usage
15-20%
Decreased Energy
Usage
5-10%
Eliminate process related
production downtimes
100%
Eliminate paper
based processes
100%
6
Platform360 Industrial IoT Solutions
USING MICROSOFT AZURE
TABLE OF CONTENTS
1 INDUSTRIAL IOT CHALLENGES
2 KOÇDIGITAL INDUSTRIAL IOT SOLUTIONS
3 INDUSTRIAL USE CASES
4 APPENDIX
7
KoçDigital’s solution set to digitize existing/new factories
Offerings of KoçDigital
in Industrial IoT
Assembly Management
System
Remote Asset
Management
Quality Monitoring
RTLS (Manufacturing Traceability)
Energy Management
Manufacturing Information
System (MIS)
Predictive Maintenance
Manufacturing Analytics
Manufacturing Execution
System
Industry 4.0 Health Check
Source: KoçDigital
Manufacturing Execution Platform
9
Industrial IoT Platform
(IIoT Platform)
10
Platform360 is the common service layer, enabling
numerous Industrial IoT Applications & Analytics
Source: KoçDigital
Internet of Things - Platform 360
…
Manufacturing
Information
Systems
Assembly
Management
RTLS –
Manufacturing
Traceability
1
EV Charging
Management
Manufacturing
Execution
System
Industry 4.0
Consulting
Remote Asset
Monitoring
1
Predictive
Maintenance
1
11
Platform360 is based on OneM2M, the global standards
initiative for Machine-to-Machine and IoT technologies
The purpose of OneM2M is to
specify, promote and maintain a
Common IoT Service Layer
allowing every component to
communicate as one system
It provides a flexible architecture
to accommodate a variety of
device platforms
• Requirements
• Architecture
• API specifications
• Security
• Interoperability
Provides technical support
artifacts …
Over 200 participating partners
and members …
Home automation
eHealth
Industrial automation
Used across industries …
Standardization
12
2
Platform360 on Azure
Data Processing,Analytics Solutions
Azure IoT
Hub
Stream Processor
Big Data
Storage
Analytics &
Machine
Learning
Service
Bus
Modules
Hot Storage
Asset
Management
Low Powered
Devices
Non-OneM2M
Devices
OneM2M
Devices
IoT Gateway
(IPE)
Manufacturing
Execution System
Energy
Monitoring
Connected
Vehicles
Applications
Devices Edge
“OneM2M module” content will be shown on the next page
13
3
OneM2M Modules
Registration Group Management SecurityDiscovery
Data Management&
Repository
Application &Service
Management
DeviceManagement
Subscription &Notification
CommunicationManagement
Service Charging&
Accounting
Location
Network ServiceExposure
Transaction Management Semantics
14
Horizontal IoT Platform
Vertical
Information Flow
Smart
Manufacturing
Platform360 provides horizontal information flow with Azure Services
Smart Energy
Smart Wearable
Horizontal Information Flow
Oth. Vertical
Solutions or 3.
party systems
Manufacturing
Intelligence
Vertical
Information Flow
Vertical
Information Flow
Assembly
Management
Remote Asset
Management
Automated
Meter Reading
Common IoT Service Layer
Competitive
Advantages
15
Self Service Dashboard
Self Service :
Widgets allow designing user-
defined dashboard views
Stream Data:
Investigate real-time data
streams/events in real-time
Query Data:
Investigate existing data using
data queries
Map Layer:
Visualize location services and
monitor device positions
User Defined Dashboard Views
Visualization of IoT Daa
16
3-Step Approach for Self-Service IoT Dashboards
Define Dashboard and Widgets
Connect to Assets and Data
Deploy Dashboards
17
Platform360 Industrial IoT Solutions
USING MICROSOFT AZURE
TABLE OF CONTENTS
1 INDUSTRIAL IOT CHALLENGES
2 KOÇDIGITAL INDUSTRIAL IOT SOLUTIONS
3 INDUSTRIAL USE CASES
4 APPENDIX
18
Manufacturing Information
System (MIS)
192021
Asset Performance & Job Per Hour
Manufacturing Asset Layout Management
Rule Based Machine Monitoring
Cycle Analysis
Bottleneck Analysis
Asset Downtime & Alarm Management
Root Cause Analysis
MTBF & MTTR Reporting
Anomaly Detection
Productivity KPIs
Bottleneck Analysis
Maintenance Management
Tangible impact in decision making with
actionable insights
22
Manufacturing Information Systems Objectives
Aggregate & process sensor
generated data into a
unified platform
Unification of machine data to
single semantic layer
Create a digital data platform for
advanced manufacturing analytics
Up to % 10
Throughput increase with horizontal
product line optimization
Up to % 50
Increase in employee engagement with
real-time monitoring and predictive
maintenance
23
Platform deployed across the whole factory
Press shop, welding, paint shop & assembly
Large Automotive Manufacturer Customer Case
2200
Stations
250+
PLCs
450k
sensors
20+ TB
of data
annually
Source: KoçDigital
Increased overall output without additional investment
on capacity.
Maintenance employee engagement increased.
Paper-based data collection has been eliminated on KPI
calculation and plant monitoring.
Automated processes have increased employee
productivity.
Project Impact
At the first year of the project, KPIs reached
KoçDigital Client Example
Customer
Case Example
25
Track & Trace
26
Product Traceability
Correct position of products are traced during manufacturing process
Support for variety of technologies
RFID Tags
Photoelectric Sensors
Barcode Scanner
OPC UA PLC Connectivity
SCADA Integration
Position Data
Photoelectric sensors
Physically Wired
HMI1
Vehicle positions
over LAN
Position data
Carrier
RF-TAG
Reflectors
Vehicle
Barcode
Carrier
RF-TAG
Reflectors
Vehicle
Barcode
PLC (Siemens S7-1200)
LAN
Barcode Scanner
OPC Server App
Position Data
HMI(n)
.NET
OPC UA
Client
.NET
OPC UA
Client
Including .NET
Apps For
Operators
Örnek Body Tracking
teknolojilerini gösteren
örnektir
Encoder
Case Example
27
Track & Trace: Palletizing Process Example
Move
packages
into pallets
Move pallet
to forklift
Move Pallet
to the
storage
Packaging
Barcode
Writer
Sensors
Static
Barcode
Reader
Mobile
Barcode
Reader
HMI
Integrates with MES and prints
relevant barcode code on the
package according to the
production plan
1
Checks validity of printed
barcodes
2
Packages are traced and
packaged into pallets in
synchronization with MES system
3
Packages are stacked in pallets,
and pallets are barcoded
4
Palet information is synced with
ERP system
5
Case Example
28
Assembly Management
29
Manufacturing Assembly Management
30
Assembly Management System (ASM) Objectives
Shop-floor integration with
Manufacturing equipment and
Product traceability
Human machine interfaces
for worker guidance
Trace and enforce how and from
which parts each end-product
manufactured
Increased Manufacturing quality
Through monitoring and
enforcing quality guidelines
Zero
Defect
Targeted assembly
process
Objectives
Decrease worker costs for
Adapting to Manufacturing
different product variants
31
Shop Floor Connectivity
Collect Manufacturing Data from Assembly Equipment and Human Machine Intefaces
Different Screen Sizes
Industrial Grade HMIs customized according to
requirements
• Supports asynchronous operations
• Different installation methods according to
shop floor layout
• Edge industrial data collection
• Visual and Audio Alarms
Human Machine Interfaces
Tablets
Commercial or Industrial Tablets
• Shows status of manufacturing quality operations
• Allows digitized entry of defects to system by
quality personnel
Assembly Equipment
32
• Guides worker through assembly
process
• Monitors the procedure and parts of the
assembly
• Can be integrated with assembly and
quality tools such as electric wrench (
Open Protocol support)
• Support with a-sync operation, network
latencies doesn’t effect manufacturing
process
• Can be integrated to customer Product
Lifecycle Management Solution
Worker Guidance for Assembly Operations
Employees are driven to quality with visual guidance
33
Remote Asset Management
(RAM)
34
Energy Status: Ok
Enviromental Factors: Ok
Security: Ok
Remote Asset Monitoring
Status: Healthy
System Room
Cellular
Tower
ATM
Enviroment Infrastructure …
Observe: Status, Operation, Enviromental Factors
Manage: Data and workflows
Optimize: Historical data, asset reliability, utilization,
usage and efficiency
35
Asset Monitoring Dashboard Example
Map with Asset Layout
• Asset data can be overlayed on map
or sketches
• Assets in with different conditions are
color coded. (Critical condition can be
denoted as red etc.)
• Important asset attributes are
accessible on Mouse hover
• Detailed asset information can be
shown on a seperate dashboard
• System events/alarms can be shown in
table format
3
5
Gizlilik Sınıflandırması : HİZMETE ÖZEL
Dashboard layouts are completely configurable using widgets
36
Detailed
Dashboard
Detailed Asset Dashboard Example
Detailed Telemetry Data of Selected
Asset
• Temperature gauges, Battery Pack
Voltage graphs, Currents Grid and
Generator Analyzer Graphs, and all
other telemetries configured, can
be displayed at detailed asset
Dashboard.
• This is a configurable dashboard
that can be expanded by adding
new widgets for each telemetry
that are expected to be seen on
the page.
• All alarms and warnings can also be
displayed here for the pole
selected.
Door-2 isopened
Door-2 isopened
Door-1 isopened
Temperature in
Lower section of
cabinet is in
alarm status
Temperature in
Lower section of
cabinet is in
alarm status
3
6
Gizlilik Sınıflandırması : HİZMETE ÖZEL
37
Telecom Operator – Remote Asset Management
Instantaneous Monitoring of CCTV Poles andAssets
Assuring the stations health by monitoring sensor data collected by P360 RAM platform
• Aims to monitor 1400 CCTV poles setup located in
multiple cities
• Monitoring each pole on a map design to see instant
condition
• Poles assets health by collecting sensor data such as;
• Cameras condition
• DC power supply status
• Air Condition of all cabinet assets
• Security of the cabinet by checking sensors on
• cabinet doors
• User friendly, configurable dashboard and rule
management mechanism for configuration and reporting
1400
CCTV Poles
3
500
Sensors per
pole
Customer
Case Example
38
Manufacturing Analytics
39
40
Advanced analytics
KoçDigital advanced analytics and IOT solutions in core mining
Value chain
Value drivers
Cost
reduction &
margin
improvement
Throughput
increase
Quality
increase
Productivity
Safety
Other
(HR, people, etc.)
HR Analytics
Safety and Security with Intelligent Video Analytics
Predictive Maintenance
Production Forecast
Productivity Optimization
Bottleneck Analysis
ImplementedOngoing
Source: BCG case experience
41
Manufacturing Analytics Customer Case in Mining
Results
Client Situation
•
Large mining company with numerous distributed mining
fields wants to increase operational efficiency using IoT
and analytics
•
Operational IoT and IT systems unified in single datalake
•
Analytical use cases improved business processes
%21
decrease in
downtime
duration
1.2M
annual
operational
efficiency in
just 3 mines
%8
less energy
usage
%17
less usage of
additive
material
Customer
Case Example
42
Planned/ Predictive Maintenance
43
Maintenance Workflows
Maintenance
Types
Planned
Periodical Usage Based
Periodical
and Usage
Based
Unplanned
Prediction
Downtime
44
Platform360 Maintenance Flow
Maintenance
Management
Real-time
Condition
Monitoring
Gather Data
Enrich with
Predictive
Models
Optimize
• Real-time data
collection with IoT
• Integrate with
operational systems
for context
• Asset monitoring
& management
• Evaluate alarm
data using
context
• Planned
Maintenance
management
• Downtime
management
• Use asset sensor data
and work history to
predict asset health
and future failures
• Enrich with user
defined rules
• Continuous model
improvement through
feedback loops
45
50-70%
reduction of
unplanned
downtime
10-20%
increase in
equipment
uptime
10-30%
reduced overall
maintenance
costs
Source: KoçDigital, BCG, Deloitte, Mckinsey
Predictive maintenance reduce surprises and cost
while increasing equipment uptime
46
VISION
• Minimize unplanned downtimes and improve
asset availability
• Doing the most efficient preventive
maintenance
• Minimize mean time between failures (MTBF)
• Autonomous control of equipment condition
• Completely paperless maintenance activities
VALUE SOURCE
• Reduced equipment downtime at core
machinery
• Improve first-time-fix-rate (FTFR) and reduce
mean-time-to-repair
• Reduce cost of maintenance without
sacrificing reliability
Predictive Maintenance Solution
Source: BCG case experience
50
Energy Management
Efficiency Improvement
51
What to Expect from Energy Monitoring?
How much energy do we consume?
• What is my manufacturing area/line or even product based
energy consumption?
• What is my real cost for manufacturing?
• How can I react to energy spending fluctuations?
Trends of Energy Usage
• Is my energy usage better or worse than before?
• What are my trends in energy consumption that reflect
seasonal, weekly, and other operating patterns?
Waste & Problems
• Where are the specific areas of wasted energy?
• Is there anomalies in energy consumption?
• How can I make warning signs visible to maintenance staff?
Analytics
• How much energy will I consume next month?
• How can I correlate this data with other connected factory
data?
Facility
Manager
Manufacturing
Area Manager
Industry 4.0
Transformation
Manager
52
Industry leaders follow a holistic IoT platform based approach
in energy management
• User defined rules to be enforce known business rules
• Analytical models can be deployed on the system to detect advanced data
correlations
• Create user/role specific dashboards and widgets for
customizable usability
• Cross-functional data ingestion
• Clear process & APIs for data dissemination
• Horizontal information flow
• Analytical products for Industry standard gains
• Predictive statistics tailored to specific needs
Real-time data processing
to detect events and alarms
Self service dashboards for
visualization
Common service layer,
enabling numerous IoT
analytics & applications
Advanced analytics to
predict and prescribe
Collect energy information
from variety of systems
1
2
3
4
5
Energy Meter
Energy Analyzer Remote Assets
EV Charging
Station*
53
Manufacturing Execution
System
54
Manufacturing Company Example
Mix of legacy machines and new
machines from various vendors
Variety of sensors communicating in
different protocols
Diverse family of products
manufactured by same manufacturing
assets
More than one manufacturing plant but
no single view of manufacturing
Shop Floor Status Governance
• Increased manufacturing throughput
• Decreased unplanned downtimes
• Traceable and improved manufacturing
quality
• Data driven decision making by
convergence of IT & OT
Targets of Industrial IoT
IT generally not involved in acquisition
of OT systems.
OT software acquisitions were driven by
operational needs
Data connectivity is not an issue to be
considered in new asset acquisitions
OT management software vision was
focused on asset KPIs such as OEE
(Overall Equipment effectiveness)
Decisions are not driven by data
55
Personas in Manufacturing
Manufacturing Manager
What is happening in manufacturing in real-time?
How can I minimize unplanned downtimes?
How does my manufacturing line efficiency change per
product type?
Where are my manufacturing bottlenecks?
How can I increase quality of products?
How to optimize energy spending?
How can I add an IT capabilities in OT systems?
Can I create a backbone for all my industrial systems?
Can I build-up on the system without vendor lock-in?
How can I become a data-driven company?
Can I create a single view for all my manufacturing
areas/plants?
How can I create a secure infrastructure?
IT & Digital Transformation Manager
56
Manufacturing Execution on Internet of Things Modules
IoT Platform
• Manufacturing
Backbone
• Operational
Data Store
• Rule Engine
• Common API
Layer
Data Collection
• Shop Floor
Connectivity
• Energy
Monitoring
• PLC
• SCADA
• MQTT
Tracking
• Track Items
inside
manufacturing
process
• Track workers
• Track
Equipment
• RFID read/Write
• Barcode reader
• Labels printing
Plant KPIs
• OEE
• Job Per Hour
• Bottleneck
analysis
• Cycle Analysis
• Plant
Performance
• Station
Performance
per product
type
Maintenance
• Asset
Downtime,
MTTR, MTBF
monitoring
• Anomaly
Detection
• Root Cause
Analysis
• Predictive
Maintenance
Operational
Intelligence
• Self service
dashboard
• Digital Twin of
the Plant
Quality
Monitoring
• Quality
Inspection
• Video Analytics
based quality
inspection
Procedural
enforcement
•Manufacturing
process steps are
performed;
•in the correct
order
•At the right time
•By the correct
resource
•In conformance
with quality req.
Planning&
Scheduling
•Production
Planning
•Shift Management
•Batch production
execution
•Components
picking list
Manufacturing
Process
Management
•BOM Recipe
•Process Planning
/Work instructions
Resource
Management
•Equipment
•Materials
Dispatching
•Dispatch work
acc. To source
avail. Schedul. nd
capacity
Production
Management
•Process to order
management
Integration
•ERP Integration
•PLM Integration
•Supplier
/Customer system
integration
57
Manufacturing Execution System Customer Case
Source: KoçDigital
MES including operational data store, equipment
tracking and plant performance.
Model & critical part matching process for 12
production points
Station based production, fault, downtime &
anomaly detection reports
31
Stations
4
Production
lines
700
sensors
500+GB*
of data
annually
Project Impact
Eliminate quality errors in manufacturing
Platform360 deployed to an Air Conditioner Plant as
manufacturing execution system
Customer
Case Example
58
Platform360 Industrial IoT Solutions
USING MICROSOFT AZURE
TABLE OF CONTENTS
1 INDUSTRIAL IOT CHALLENGES
2 KOÇDIGITAL INDUSTRIAL IOT SOLUTIONS
3 INDUSTRIAL USE CASES
4 APPENDIX
59
KoçDigital is a Digital Center of Excellence, combining strengths
of BCG and Koç Holding & KoçSistem
KoçDigital
Academy
Advanced
Analytics
Data Platform
Design & Development
IoT
Solutions
World class
capabilities
in analytics
Access to >3,000
digital experts
>3,000
State-of-the-art
enablement
Digital
capabilities and
infrastructure
Very strong
implementation
capabilities
Trusted
Koç brand
Source: KoçDigital
KoçDigital overview
60
KoçDigital
Overview
We already have 100+ staff in KoçDigital, supported
by 850+ Gamma and 1500+ KoçSistem professionals
100+
Data analytics &
IoT professionals
850+
Data scientists and
engineers of BCG
GAMMA
9
1500+
System Integration&
Managed Services&
Business Applications
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