The document discusses how companies can use data collected from machines and processes to improve operations. It describes how Blackbird collects machine data from over 1,000 equipment across 21 countries. Any process can be improved with data by identifying variations that affect things like output, time, and root causes. The document provides examples of connecting sensors to track flow, stop reasons, and batch performance. It emphasizes that training people and establishing review routines is key to acting on data. A "sandbox" approach of testing in one area first is recommended before full rollout. Options are presented for connecting new and old machines to collect and send data to the cloud.

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Turning your data into gold
Finn Hunneche
Blackbird CEO,
Founder & Senior Partner emendo consulting group

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The 1st Industrial revolution
Power from Steam engines changed the
world
The 4st industrial revolution
Use of data is changing the world
Today
A few facts to get us started

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Blackbird collects data from your machines and analyse it for
you
• +1000 equipment’s daily on-line
• In 21 countries
• 300 mil IOT data entries per day
• First customer in May 2016
• Annual growth rate 75%

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Any process can be improved with data
The question to ask in your company is:
“What data can significantly improve our process?”

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Find improvements by looking for variation in the data
Output
Time
Understand the root cause of the variation – and take actions to control the variation
A
B
C
8:27 9:03 11:46 14:11
B = Golden minute

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Look for variation in repeated data or relations between
data
Golden year

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Let’s get practical in your factory
Data you can get from just connecting one sensor on your machine

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Level 1 – Track flow
Connect one sensor on the bottleneck of the line, to
count and time-stamp flow of products
Data you can extract from simple tracking of flow:
• When did we start and finish
• How much have we produced
• How much value adding time
• How many stops and how much down time
• Average stop time
• Longest non-stop
• Product cycle time (speed)
• Trends and averages over time
The data plot will look like this:

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When the line stop, track the stop time and ask the
operator the reason for the stop – Or if possible, get the
Stop cause from the machine PLC
The data plot can be a chart showing a ranking of the reasons for stops
Level 2 – Track reason for stops
Data you can get from tracking reasons for stops
• Reason and duration for every stop on the line 24/7/365
• Split of time for technical stops, change-overs, breaks, repair, etc
• Pareto chart showing what to improve
• Operator comments to stops
• Visualization of individual stop causes over time

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The black line is
your accumulated
target output for
the batch
Level 3 – Set a batch target and track the actual performance
Data you can get from tracking vs a batch target
• Cycle time data per product
• Duration time for different batch sizes per product
• Time loss data for, technical stops, speed loss, change-over activities and
non-production related activities
• Data for total capacity utilization
• Basis for Big data analysis per product
The red/green is the actual
output from the sensor on the
line
The data plot can be an Overall Equipment Efficiency waterfall showing:
• OEE1 Speed loss, technical stops and scrap
• OEE2 Batch change over related time
• OEE3 Non-production related activities
• Line closed time

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Your biggest challenge will not be technical
Data alone will not improve anything!
• You need to train your colleagues in how to act on the data
• Establish daily routines for how to review data
• Provide time for people to adapt to the new digital mindset

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Use a sandbox to get your digital journey started
Make a test area in your factory – Do not go all-in from day one
• Do experiments with data collection and new technology
• Develop the routines for data review and performance management
• Train the operational team in the test area
• Do not roll-out from the sandbox before you have good results

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65% of all industry processes are not connected to anything!*
* Source, McKinsey & Company
The technical challenge you will face in many factories

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The easy solution: Connect machines with wireless IOT hardware

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Connecting “old” machines
Option 1: Add extra sensors and connect to the cloud with IOT hardware
Option 2: Use a “copy cable” to snap the signal from existing sensors and connect to the cloud with IOT hardware
Option 3: Use Kepware/KepServer to connect to the PLC and forward data to the cloud

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Connecting “new” machines
Option 2: Use the OMRON NX1 PLC – Connect direct to Amazon Web Services and Blackbird - Zerro layers in between
Option 1: Use Kepware/KepServer to connect to the PLC and forward to a cloud
Option 3: Use IOT box if there is no value in a deep integration

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Observe Think Improve
Digital vision for operational excellence
Visit www.blackbird.online to see the full interactive presentation

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