Webonise uses a six dimensional approach to help manufacturing companies on their path to a Smart factory with 4th Industrial Revolution. The deep dive to pure Tech Adoption Strategies + Data Driven Play for Future Factories.

1. Smart Factory with Industry 4.0
6 Dimensional Model

3. Problem Statement
Excess Inventory
According to HACKETT GROUP
2018 WORKING CAPITAL
SURVEY, excess inventory worth
$443 Billion is stranded in
supply chains.
Inefficient Logistics
According to AMERICAN TRUCKING
ASSOCIATION, 42 Billion trucks
are driving empty miles worth,
per year – creating 97 million tons
of CO2.
Carbon Footprint
As per US Environmental
Protection Agency, 4 Trillion
Pounds CO2 is emitted from
manufacturing companies (that’s
4,000,000,000,000), 35x the mass
of the Great Wall of China.
Sounds like the problems worth solving!

4. Problem Statement
Downtime cost
98% of organizations say a
single hour of downtime costs
over $100,000.
Sounds like the problems worth solving!
Skilled labor shortage
Approximately 22% of skilled
manufacturing workers will be
retiring within the next 10 years.
Scrap generated due to
faulty products
The estimated annual wastage is
$1,200,000, due to scrap
generated from faulty products.

5. Problem Statement
Excess Inventory
Demand Prediction AI
algorithms combined with
historical demand patterns,
with automated production
commodity, global news, and
macroeconomic events can
unlock powerful breakthroughs
in forecast accuracy for optimal
level of inventory.
And, Here is the Solution
Inefficient Logistics
Creation of Digital Twin with Health AI
and fleet mapping - mapping every
trip, breakdown, or other unplanned
incident, and then feeding that data
into machine learning models can
enable optimised Logistical Planning
Carbon Footprint
Automation, augmented reality and
the Internet of Things (IoT), could
accelerate the deployment of
renewable energy in manufacturing;
reduce carbon emissions; optimize
energy-use; and enhance
productivity and cost savings.

6. Problem Statement And, Here is the Solution
Downtime cost
Predictive maintenance, can
determine from sensor data that a
failure is imminent on a particular
piece of equipment. Operators can
plan an appropriate time to take it
offline, and internal systems can
automatically check for necessary
spare parts in advance of repairs.
Timely maintenance will lead to a
reduction in operation costs and
keep unplanned downtime to a
minimum.
Skilled labor shortage
Robotic process automation for
repetitive tasks, floor automation
and Collaborative robots, called
cobots, designed to augment the
capabilities of human workers
rather than replace them, to boost
productivity.
Scrap generated due to
faulty products
Automated workflows,
synchronization of assets,
improved tracking and scheduling,
and optimized energy
consumption inherent in the smart
factory can increase yield, uptime,
and quality, as well as reduce costs
and waste.

7. Strategy model for industry 4.0 : Steps & Drivers
A taxonomy for designing aligned multi level strategies

8. Industry 4.0 - The Six Dimensional Model
Smart Technology
Physical components equipped with technical
components:
● Sensor based technology combined with IoT
● Additive manufacturing with 3D printing
● Digital Twinning
Smart Operations
● Information sharing
● Process Automation
● Cloud usage
Workforce
● Analyze employee’s current skills
● Analyze employee’s ability to acquire new skills
● Get them well equipped with the digital workplace
Smart Factory
● Digital modelling
● Equipment/component
infrastructure
● Data usage
● IT systems/infrastructure
Data-driven Services
● Enrich the after sales
business with analysis
of collected data
● Enterprise-wide
integration
Strategy and Management
● Review existing strategies through a
system of indicators
● Measure enterprise investments relating
to Industry 4.0
● Understand the innovation management
● Evaluate the current state of research
and development

9. Industry 4.0 Smart Technology
Industrial IoT - Black & Decker
Problem
The company wanted to:
● Reduce manufacturing
complexity.
● Increase visibility and
productivity gains at its plant.
● Increase the equipment
effectiveness.
● Reduce labeling defects.
Solution
● A real-time location system in the
form of Wi-Fi radio-frequency
identification tags that attach to
nearly every material, so that
tracking them becomes nearly
effortless.
● Integration with the company’s
Programmable Logic Controller,
which monitors quality control and
delivers its results once the product
reaches the end of the line.
● This allows floor managers visibility
at every step of the production
process, giving them the ability to
slow down or speed up processes,
and see how quickly employees are
completing their respective tasks.
Impact
● 10% greater labor efficiency.
● Improved labor utilization rates from
80% to 90%.
● Equipment effectiveness on the
router production line rose 24
percent.
● Immediate notification of issues
made for faster decision making.
● Labeling defects fell by 16 percent.
● Throughput increased by around 10
percent.

11. Solution
● Took a multi pronged approach in
advising latest technology use,
analyzing existing system
capabilities, and understanding
existing data.
● Utilizes cloud hub as a gateway to
establish two-way communication
between the connected sensors and
cloud.
● Uses Web/Mobile Dashboard to
visualize data for quick analysis and
decision support.
● Included a Notification engine that
generates alerts/alarms based on
the sensor conditions, helping the
operations team to keep a watch on
the instruments.
Industry 4.0 Smart Operations - Process automation
Pulp & Paper manufacturing industry
Problem
The existing system lacked:
● capabilities to aggregate,
process, analyze & visualize
collected data for quick analysis
and decision support.
● Didn’t provide tracking and
reporting of instrumentation
health, analyze sensor
conditions & availabilities
● Didn’t generate alarms or errors
in case of emergency.
Impact
● Organisation wide smart process &
compliance monitoring helped
capture the non-compliances in real
time.
● Rich Analytics Dashboard provides
predictive analysis and actionable
intelligence for informed decision
making in real time.
● Predictive maintenance with SMART
sensors reduced the downtime by
30%
● 14% increase in NPC achieved by
well designed notification system.
● Reassigned workflows keep
customer involved and informed.

12. Solution
● Platform to on-board both sales and
management team and make them
work together seamlessly.
● Smart Sales Appointment planner
for better sales follow-up resulting in
increase sales.
● Gamification of channel partners’
performance to enhance the sales
achievements.
● Smart chatbots for all stakeholders
for seamless communication.
● “Offline Maps” to reduce internet
dependency.
Industry 4.0 Workforce
Salesforce App
Problem
● Demotivated Sales Team
● Management Trust Issues
● Longer Sales Cycle
● High Cost of Inventory
● Low Sales
Impact
● Empowered the sales team by
generating smart leads from CPs &
eco-system directory services such as
MAHARERA, JustDial, etc. Sales up by
5% from 6 months of launch
● Real time notification to all
stakeholders for order lifecycle e.g:
generation, approval and order
status reduced the sales cycle by 40%
● Real time tracking of sales team on
field and smart reporting to
management on day to day basis
reduced the friction by 99%

13. Solution
● The company implemented Digital
twins that was fundamentally, an
evolving digital profile of the
historical and current behavior of a
physical object or process that helps
optimize business performance.
● The company is using the technology
to predict these maintenance
problems and aims to have sensors
connected to most of its high-value
equipment by 2024.
Industry 4.0 Smart Factory
Chevron
●
Problem
● Chevron Corporation is an
American multinational energy
corporation. One of the
successor companies of
Standard Oil was dealing with
maintenance problems in its oil
fields and refineries
Impact
● Several Million of dollars savings
anticipated in maintenance,
especially at remote locations.
● Training new employees on the set
ups and explaining them the
systems as is in near real time
simulation mode.
● Modelling changes and doing
impact analysis even without
changing anything physically

14. Solution
A BI solution that is:
● For the product delivery team to
analyze test result data from the
subcomponents of microchips. They
are performing root-cause analysis
by component and defect to see
what areas are causing the biggest
problems and fix them quickly.
● For the engineering operations team
to optimize the supply chain, and
have eliminated delays in the
product pipeline.
● For the customer service team to
identify trends around cases by
customer, product and region.
Industry 4.0 Data-Driven Services
Semiconductor Manufacturing Company
Problem
● The company needed a solution
that allows for analysis across
multiple data sources, and still
would be easy enough for
anyone to use.
● The existing BI tools were too
complex for the engineers to
use, they relied heavily on the BI
team to set up their data and
produce reports for them.
● The overworked BI team
struggled to get data into
engineers’ hands fast enough.
And this proved to be a
bottleneck of it’s own, slowing
production across product lines.
Impact
● Delivering products to customers 10%
faster.
● Improved productivity and customer
satisfaction by 15%.
● With access to search-driven analytics,
business users at this manufacturing
company are performing 1,300
searches a week. Teams have been
able to increase productivity, reduce
material waste, and streamlining
operations at all levels of the
business.

15. Industry 4.0 Strategy and Management
Commercial Equipment Manufacturer
Problem
● The company wanted to
expand its business to get
more profit, but was unable to
do so.
● Poor visibility on consumer
behaviour, product
performance and user
engagement channels.
● To remain up to date about
consumer markets and its
latest trends, the company
needed rich data and
analytics.
● The company was struggling
with marketing its products
due to lack of an efficient
strategy.
Solution
● Streaming analytics provided the
company with real-time insights on its
connected products.
● With continuous data from connected
products, multiple stakeholders were
empowered with diverse actionable
insights.
● Purpose-built IoT analytics solution and
data science expertise, provided a
complete picture of when, where and
how products were being used.
● Drilling down to see interactions between
products and customers, the company
could determine when there was a
problem with a given commercial lock
and the important context around that
problem.
Impact
● Started to leverage product usage
data to design new service
packages with higher value
product performance guarantees.
● With complete visibility on the
product lifecycle, the company
uncovered new opportunities
across each sales channel.
● Product management, sales and
marketing, operations, and
C-level gained end-to-end visibility
on actual product performance
and usage, user engagement and
customer profiles.

16. Awesome!
But what’s
next?

17. New Technology Investment Priorities
Data Intelligence
● Enhanced data availability
● Real-time availability of
critical business information
● Enhanced analytical
capabilities
Operational Efficiency
● Higher productivity
● Enhanced production
flexibility
● Reduced time to market
Customer Engagement Strategy
● Deeper knowledge of customer
preferences
● More efficient workforce
management
● Deeper supply chain visibility
● Enhanced collaboration with
customers and suppliers
Execution Strategy
● Enhanced operational visibility
● More effective strategic
execution
Market Intelligence
● Enhanced market
intelligence
● More effective customer
communication
● More accurate forecasting
Responsiveness
● Easier product customization
● Faster responsiveness to
customer orders and requests

18. Where you are overworking?
Too many
competing priorities
Sub-optimal
inventory and
Supply Chain
Compliance &
Reporting blues
Customer
Management
Too many
tools
Intuition-led
Decision

19. Solution Architecture

20. ADaFT - Adoption+Data Focussed Tech
The method leverages user
experience-led applications for
adoption of product and services
by your customers, processes by
your workforce, and efficiency by
your supply chain partners.
Capturing data as it happens - a
customer feedback, right
truckload or a partner concern -
creates deeper visibility.
DATA
DRIVEN
EASE OF
BUSINESS
USER
CENTRIC

21. The power can be “Yours”
You

22. Get
it
Webonised!

23. Saurav Mishra
COO
+91-9689928195
saurav@weboniselab.com
Contact Information