The document discusses how the Industrial Internet of Things (IIoT) can benefit manufacturing operations. It explains that IIoT involves collecting sensor data from machines and using that data to optimize processes, increase efficiency, and reduce costs. Specifically, IIoT can help improve financial metrics like sales, costs of goods sold, expenses, and profits through predictive maintenance, continuous improvement efforts, and optimizing operational processes with large data sets. The document provides examples of how IIoT data collection and analysis can benefit areas like disposables procurement, production machinery maintenance, production line efficiency, and employee performance monitoring.

1. THE INTERNET OF THINGS
The business case for the manufacturer

2. What is IoT
• IoT stands for ‘Internet of Things’
• It’s really about collecting data on things
managed and acting on that data
• Think input of sensors, communication via
networks, and actionable data as the
output
• Now think industrial
• IIoT stands for ‘Industrial Internet of
Things’
• Think more sales, lower Cost of Goods Sold,
lower expenses, more profit
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Internet of Things:
(stylized Internet of Things or IoT)
the internetworking of physical devices, vehicles
(also referred to as “connected devices” and “smart
devices”), buildings, and other items – embedded
with electronics, software, sensors, actuators, and
network connectivity that enable these objects to
collect and exchange data. (from Wikipedia)

3. Why Operations should care about IIoT
‘…highly instrumented verticals like manufacturing and
transportation, large data sets are used to optimize operational
processes and extend the life of high capital cost assets.’ - IDC
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4. Why Operations should care about IIoT
4 Study in 2014 by Tata Consultancy Services
$100 MILLION
12% of 795 executives were going to
allocate
to IoT in 2015
1 in 10
15.6
%
Avg.
Revenue Increase
30%

5. Why Operations should care about IIoT
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invested in the U.S. alone in 2016
Investment Leaders
Transportation
Manufacturing
$200+ BILLION
Study in 2016 by IDC

6. Why Operations should care about IIoT
Predictive Modeling Benefits
• Will provide significant improvements in up-time (predictive maintenance)
• Will provide significant information on equipment performance (real time)
• Data for continuous improvement efforts – ever better efficiencies/utilization
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7. Industrial Internet of Things Adoption
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35% are either
moving forward or
have pilot projects
Moving Forward
13%
Pilot Projects
22%
Don't
Understand…
Don't Care
19%

8. How IIoT Will Improve Financials
• Improve your P&L
• Sales Income
• Increase sales by reducing product waste via monitoring data indicators
• Improving efficiency with data will increase production, annual sales volume,
and capacity
• Cost of Goods Sold (COGS)
• Reduce COGS by using data to maximize efficiencies and reduce production
costs
• Selling, General & Administrative Expenses (SG&A)
• Reduce SG&A by monitoring/automating disposable reorders
• Better proactive preventative maintenance through ‘data’ eliminates
collateral damage failures, or undetected early indicators of improper
maintenance, etc.
• Reduce insurance premiums – better safety record, reduced facility damage
due to catastrophic failures
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9. How IIoT Will Improve Financials
• Improve your Balance Sheet
• Debt Load / Current Ratio Improvements
• Reduce potential unplanned debt on balance sheet by proactive
data-driven maintenance and repair
• Assets
• Improve lifetime of capital equipment purchased and unplanned costs
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10. How IIoT Will Improve Financials
• Improve your Cash Flow
• Work In Process (WIP)
• Increase WIP by maximizing up-time of equipment via data-driven
maintenance
• Increase production efficiency by looking through data for good/bad
practice, and operation of machinery.
• Accounts Receivable (AR)
• Increase cash inflows by getting more production by looking for
efficiency and utilization issues in the operation data.
• Accounts Payable (AP)
• Less failures, lower insurance, fewer catastrophic events, longer
lifecycles of machines and disposables all reduce your AP burden.
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11. Example market. Whey does ‘Agriculture’ care about IoT?
• Seems everyone in agriculture is investing in IoT
• Costs of sensors and computer technology has
dropped
• Computer processing power has increased
• Using statistical process control
• Leveraging programmable automation
• Improve efficiency and utilizations
• Production improvements through data analysis
• Increased sales, reductions in COGS and SG&A
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12. Why manufacturers should care about IoT
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• Learn and improve
safe operation
• Learn about
performance
of the equipment
• Improve the
procurement process of
disposables
• Reduce insurance cost
• Improve employee
performance
Improved financials by using data
• Learn and improve
efficiency
• Learn and improve
utilization numbers
• Improve up-time
• Detect issues with other
machinery or processes
• Learn and improve
productivity

13. Example: Monitoring Disposables using IIoT – Actionable Data
Blade
• Data on items purchased
• Promotional offers based on use of preferred brands vs. alternatives
• Enhanced features and functionality based on use of IIoT enabled disposables vs. alternatives
• Predictive analysis on when disposables need to be purchased, repaired, discarded
• Automation in procurement of new disposable products
• Option to disable operation due to use of unapproved disposables.
• Data on disposables performance
• Track and estimate amount of production waste per disposable, per employee
• Determine with data which disposable to use in which operation
• Detection of aging so as to replace before productivity, safety are compromised
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14. IIoT – Actionable Data – Production Machinery
Production Machinery
• Preventative maintenance
• Proactive detection of issues/failures within the system itself
• Lifecycle as a function of other factors (usage, operations, etc.)
• Maximize up-time using the above information and coordinate
repair timing to minimize downtime
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15. IIoT – Actionable Data – Production Machinery
Production Line
• Efficiency, safety, utilization measures as they relate to:
• Other production lines (line-to-line comparison)
• Team members, supervisors
• Other identical equipment on other lines
• Other machinery – can indicate whether another machine is underperforming past results or other
machines
• Product tracking
• Use data collected from machine to determine varying levels of efficiency and utilization
• As part of a larger IIoT system, track product as it moves through the process. Providing real-time
performance indicators
• Are we slowing down or speeding up?
• Are we stopped?
• Are we spending too much time at one phase of the process or too little?
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16. IIoT – Actionable Data – Other Systems
Other Systems
• How well are machines being maintained?
• Are there correlations with data supported issues/problems and other
systems being used?
• Can we integrate our data with other systems’ data so as to model
the entire production process and look for improvements in
utilization, efficiency, safety, production, etc.?
Part of an IIoT Infrastructure
• Eventually all systems within a plant will have sensors and data which
can be integrated with all machine IoT data to improve top- and
bottom-line performance
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17. IIoT – Actionable Data – Employee
Employee
• Time productive vs. total time on
• Unsafe patterns in use recognized and recorded
• Inefficient use of a tool observed via algorithms
• Frequency of a tool being maintained.
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18. THANK YOU