The document outlines key technological trends over the last 15 years, including hyperscalers, SaaS, new sensors, and AI/ML, influencing industrial production. It emphasizes the limitations of hardware replacement cycles compared to rapid software updates and discusses the transition to a software-defined factory. Furthermore, it raises questions about emerging categories and players in this evolving landscape.

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WUNDERVC
Industrial Tech
- Software Trends
Christian Dahlen, September 2024

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Executive summary
• Multiple technology trends have emerged over the past 15
years - hyperscalers, SaaS, new sensors, converged IT/OT, and
AI/ML - and are making their way into production
• SW can be updated in minutes, but machines are only
replaced every 25 years, and electronics every 10 years
• The push towards the Software Defined Factory is underway.
Which new categories and players will emerge based on these
new technologies?

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Multiple technology trends have emerged
3
New
sensors
Hyper
scalers
IT/OT
convergence
AI and
LLM
Design Plan Procure Make Assemble Deliver Operate
Bus.
ops
Monitoring
Supervising
Sensing
Manipulating
Production
SW as a
Service

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Hyperscalers have emerged as a massive force
Source: Synergy Research Group
Hyper
scalers

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Case study VW and Amazon: Manufacturers and
hyperscalers heavily invest into digital platforms
Source: AWS re:Invent 2022
Hyper
scalers

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7 reasons why SaaS is more than just cloud
Usability &
Functionality
Consumeriz
ation
Self service
Budget
control
Subscription
Cloud
deployment
Market
maturity
• Enterprise:
buying power
shifts from the
CIO to the
functional
heads
• SME: Usability
and
accessibility
SaaS

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Case Study Tulip: Composable MES

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Cloud adoption extends all the way down to level 2
8
ERP
MES
SCADA/
DCS
SaaS

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New sensors are generating a wealth of new data
and allow for new use cases
Tech: Electric current
Use case: machine usage
Exemplar: Amper
Tech: Streaming video
Use case: Location analysis
Exemplar: Darvis
Tech: Streaming video
Use case: Movement analysis
Exemplar: Deltia
Tech: Low energy radio
Use case: Location analysis
Exemplar: Kinexon
Tech: RF/BLE Bar code scanner
Use case: Hands free workflows
Exemplar: Proglove
Tech: Streaming video
Use case: Quality control
Exemplar: Relimetrics
New
sensors

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Case study cell phone: Sensors are consumerized
• Camera
• Infrared camera
• Microphone
• Proximity sensor
• Ambient light
• Accelerometer
• Gyroscope
• Barometer
• Magnetometer
• FaceID
• LiDAR scanner
• …
New
sensors

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Monitoring systems are getting squeezed
Hyperscaler
ERP
MES
SCADA/
DCS
PLC
SENSORS
IT-style approach (e.g., low-code,
integrated development
environments, containerization)
to configure/engineer/deploy OT
applications and control logic
Deluge of new data from
new sensors and increased
connectivity
Top
down
pressure
Bottom
up
pressure
IT/OT
conver
gence

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PLCs are entering the DevOps age
IT/OT
conver
gence
•PLC suppliers offer an independent
and rich integrated development
environment (IDE) with their own
added layer of programming
methods on top
•Different PLC programming styles,
such as ladder logic, function
blocks, and structured text
•PLC code often resides within
proprietary project files on individual
laptops, creating inefficient and
error-prone version management,
code integration, and testing.
Source: Software Defined Automation

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Industrial Control as a Service: Data virtualization
bridges the gap between PLC and cloud
IT/OT
conver
gence
Hyperscaler
ERP
MES
SCADA/
DCS
PLC
SENSORS
Source: Software Defined Automation

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At every level of the pyramid: It‘s the data, stupid
Hyperscaler
ERP
MES
SCADA/
DCS
PLC
SENSORS
• What data can you run LLMs against?
• How deal with the explosion of data?
• How to capture data time series and history?
• How to deal with different data structures ?
• How to contextualize data?
• What is the impact of new data on business
processes?
How to move
data bi-
directionally
and in real
time?
IT/OT
conver
gence
• How to connect legacy OT and unlock data?
• What to do with data from new sensors?
• How does real time data change production?

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The pyramid becomes a data source; system of record
and engagement happen outside in hub and spoke
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Hyperscaler
Bus.
Planning
Manufact.
Operations
Monitoring and
supervision
Sensing and manipulating
Production process
Frame
work &
Broker
App
PDM
Histori
an
AI
Model
Data
Lake
OEE
Digital
Twin
IT/OT
conver
gence

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Data needs to be contextualized to make is usable
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IT/OT
conver
gence
Source: Highbyte

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AI use cases stretch from the top of the automation
pyramid to the bottom
Source: LXT Path to AI Maturity 2024
AI and
LLM

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Convergence challenge - cybersecurity
IT/OT
conver
gence

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The push towards the Software Defined Factory is underway
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109
288
2021 2026
IT
OT
Industrial Software vs. Operational Technology Market
$ Billion
20% CAGR
IT:OT
~1:1
IT:OT
~3:1
Source: IoT Analytics 2022

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SW can be updated in minutes. Machines are only replaced
every 25 years, and electronics every 10 years

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Which new categories and players will emerge based on
these new technologies?
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Industrialists SW Generalists SW Specialists
Siemens 1847
GE 1892
Schneider 1836
Rockwell 1903
Honeywell 1906
ABB 1883
SAP 1972
Oracle 1977
Epicor 1972
PTC 1982
Dassault 1981
Autodesk 1982
Ansys 1970
1870 1969 2011
INDUSTRY 2.0
Mass production,
assembly line,
Electrical energy
INDUSTRY 3.0
Automation,
computers,
electronics
INDUSTRY 4.0
Hyperscalers, SaaS,
convergence,
sensors, AI/ML
?
?

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WUNDERVC
Multiple technology trends have emerged over the past 15 years -
hyperscalers, SaaS, new sensors, converged IT/OT, and AI/ML - and are
making their way into production
SW can be updated in minutes, but machines are only replaced every 25
years, and electronics every 10 years
The push towards the Software Defined Factory is underway. Which new
categories and players will emerge based on these new technologies?