Production Performance Management
The Production Performance Management demonstrates how to continuously monitor the performance of heterogeneous industrial equipment on a shop floor.
A key challenge of the manufacturing industry is to improve capacity, quality and flexibility, while lowering costs.
The Eclipse IoT Open Testbed for Production Performance Management demonstrates how to gather performance data from heterogeneous industrial assets, and how to analyze it in backend systems.
Key challenges for the manufacturing industry are to improve
capacity, quality and flexibility, while lowering costs.
To overcome these challenges, factories look to improve
optimization of factory equipment, referred to as Production
Performance Management (PPM). However, the heterogeneous nature of the
equipment used in the manufacturing industry sometimes makes it
difficult to get an overall perspective. The equipment used in
factories is often based on proprietary software that uses proprietary
protocols, and it’s often difficult to update to more modern
protocols. This environment makes it challenging to create solutions
that monitor equipment across entire factory floors, and across
The Eclipse Production Performance Management
Testbed aims to showcase how consistent monitoring across all
factory equipment leads to improved factory equipment optimization.
At the heart of the testbed is the Production Performance
Management Protocol (PPMP), which allows uniform representation of
all the data and information related to manufacturing processes.
The testbed showcases how performance data from different
industrial assets can be connected to the same IoT Cloud backend,
so that this data can be further processed, or simply visualized.
Standardized communication using PPMP
PPMP specifies a format that allows to capture data that is
required to do performance analysis of production facilities. It
allows monitoring backends to collect and evaluate key metrics of
machines in the context of a production process. It is doing that
by allowing to relate the machine status with currently produced
All the devices that are part of the testbeds are leveraging PPMP
as a way to describe measurements in a consistent format. The
implementations of the PPMP libraries used in the testbed come
from the Eclipse
Unide™ open source project. As of today, Unide provides a Java
and a Python implementation of PPMP.
Open Source based PLCs and IoT Gateways
A typical Industry 4.0 IoT architecture will include PLCs
that actually control the manufacturing process and, either
directly or through a more general purpose IoT Gateway, are
communicating with a backend server where data is being stored and
can be further analyzed. More and more, edge computing scenarios
are implemented, where part of the data processing is actually
performed directly in the factory, i.e. on the gateways.
➔ Eclipse 4diac™️
4diac is an open source PLC environment that allows to
implement industrial control solutions in a vendor neutral way.
4diac implements IEC 61499 extending IEC 61131-3 with better
support for controller to controller communication and dynamic
reconfiguration. 4diac provides support for PPMP, that is
leveraged in the testbed for connecting a boiler (simulated using
a sample application made available with 4diac, but it can be
easily replaced by a real machine) to the backend.
➔ Eclipse Kura™
The testbed includes a Kura based gateway with a PPMP plug-in
that allows to easily interface a Modbus PLC to a PPMP backend.
Enabling Advanced Data Analytics
The different endpoints of the testbed are all communicating
with the same backend server that runs InfluxDB, a time series
database that stores all the PPMP messages.
The PPMP specification is pretty
straightforward, which enables people to easily implement data
analytics based on the collected metrics (measurements,
information regarding the industrial processes, …). An example of
data visualization and analytics is provided in the form of a Grafana
dashboard that aggregates and displays all the measurements coming
from the different assets that are part of the testbed.
Integration with vendor ecosystem
The testbed is a great example of how open source can help
implementers easily get started with their Industrial IoT
solution, and get support from a vendor ecosystem to go to
The Production Performance Management testbed features a grinding
machine simulator that can be connected indifferently to the
Eclipse Unide open source backend (based on InfluxDB and Grafana),
or to e.g. CONTACT Elements or Bosch Production Performance Manager.
“The Production Performance Management
Testbed shows how simple performance monitoring can be quickly
implemented using open standards and open source software, like
Eclipse Unide. This collaboration shows how different vendors can
work together to solve Industry 4.0 solutions.” – Dr. Nils-H.
Schmidt, Portfolio Management Industrial IoT
“CONTACT is committed to the outstanding work
of the Eclipse Open Source community. The PPM Open IoT testbed and
our implementation of the PPMP protocol are excellent examples,
stimulating future editions of CONTACT’s Elements for IoT
framework.” — Frank Patz-Brockmann, Director Software-Development
“We are excited to support the new Eclipse
IoT Open Testbeds for Industry 4.0 with our partners. We continue
to believe that testbeds are an important initiative in showcasing
how open source components provide solid building blocks to
accelerate the development and the deployment of IoT solutions and
applications.” – Marco Carrer, CTO
“With the Production Performance Management
Testbed we can show how production performance data can easily be
generated within Eclipse 4diac PLCs programs reducing the effort
of integrating monitoring functionalities in PLC programs.” – Dr.
Alois Zoitl, Head of Competence Field Industrie 4.0
“InfluxData is pleased to be contributing to
the Eclipse IoT Working Group’s Open IoT Testbed. As the leader in
time-series event monitoring, InfluxData is excited to see the
Open IoT Testbed’s continued progress towards IoT monitoring
solutions which utilize time series data to increase efficiencies
and lower costs.” – David G. Simmons, Senior Developer Evangelist