=Paper=
{{Paper
|id=Vol-1875/paper3
|storemode=property
|title=Semantic Web of Things for Industry 4.0
|pdfUrl=https://ceur-ws.org/Vol-1875/paper3.pdf
|volume=Vol-1875
|authors=Aparna Saisree Thuluva,Darko Anicic,Sebastian Rudolph
|dblpUrl=https://dblp.org/rec/conf/ruleml/ThuluvaAR17
}}
==Semantic Web of Things for Industry 4.0==
https://ceur-ws.org/Vol-1875/paper3.pdf
Semantic Web of Things for Industry 4.0
Aparna Saisree Thuluva1,2 , Darko Anicic1 , Sebastian Rudolph2
1
Siemens AG - Corporate Technology, 2 TU Dresden, Germany.
aparna.thuluva@siemens.com, darko.anicic@siemens.com,
sebastian.rudolph@tu-dresden.de
Abstract. Industry 4.0 which is also referred to as the fourth industrial
revolution aims at mass customized production with low-cost and shorter
production life-cycle, by digitalizing and automating the manufacturing
process. The Automation Systems (AS) used in the manufacturing pro-
cess should be flexible in order to achieve this goal. But, lack of interop-
erability between AS devices from different domains makes it harder to
achieve this goal. In this study, we employ Web of Things and Semantic
Web Technologies to address the cross-domain interoperability problems
in AS. Then, we propose an approach to engineer and configure an AS
with minimum effort; and show the preliminary results as a demonstra-
tion on a process automation workstation to show the feasibility of our
approach.
1 Introduction
Mass customized production faces the challenges of higher production costs and
longer production life-cycle. The fourth industrial revolution also known as In-
dustry 4.0 [1] aims at reducing the cost and production time for mass customized
production. Manufacturing processes are being digitalized and automated by
employing Automation Systems (AS) for manufacturing processes. A goal in
a manufacturing process is achieved by letting the AS devices communicate,
co-operate and exchange information in a certain manner.1 Mass customized
production requires ever-changing settings such as dynamic configuration of in-
teractions between AS devices and constant update of functionalities on an AS,
in order to manufacture products to fulfill the demands of every customer. There-
fore, to meet the ever-changing settings the AS should be flexible. But, if the AS
devices used in manufacturing belong to different domains and they use different
information models and protocols such as OPC UA2 , BACnet3 and so on, that
restrains the interoperability between the devices which in turn makes it harder
to achieve flexibility in an AS. Therefore, interoperability problems between the
AS belonging to different domains should be addressed.
1
https://www.plattform-i40.de/I40/Redaktion/EN/Downloads/Publikation/
interaction-model-I40-components.pdf
2
https://opcfoundation.org/about/opc-technologies/opc-ua/
3
http://www.bacnet.org/
Today, the AS used in manufacturing are increasingly becoming part of In-
ternet of Things (IoT). IoT is the system where the physical devices are em-
bedded into electronic systems which can connect to the internet and can be
discovered, monitored, controlled and interacted with each other over various
network interfaces. But, IoT lacks an universal application protocol which hin-
ders the integration of devices from various manufacturers into a single appli-
cation [2]. Web of Things (WoT) [3] addresses this limitation by leveraging the
Web standards to the embedded devices, which by addressing the interoperabil-
ity problem, enables the devices from various manufacturers to be integrated
with the Web applications with minimal effort. Employing Semantic Web Tech-
nologies (SWT) also enables cross-domain interoperability. Semantic modeling of
the WoT-enabled devices, their services and applications provide un-ambiguous
and machine-readable device descriptions and also creates interoperability be-
tween the devices and their services across domains. Therefore, in this project
we propose an approach to engineer and configure an AS with low-effort and
minimum human intervention by employing SWT on WoT-enabled devices.
The main contribution of this project is to: create transparency of AS infras-
tructure, develop a low-effort approach to engineer and configure the interactions
between AS devices in order to fulfill a goal specified by a manufacturing task.
We also develop a low-effort approach to re-engineer the AS devices to update
their functionality, whenever it is required by a manufacturing process. We will
make this semantic-based approach easily usable for an AS engineer with little
knowledge of the SWT.
2 State of the Art
Web of Things: Initial standards are being developed for the Web of Things by
the W3C WoT working group4 to address the concerns regarding interoperability
between IoT platforms. The standard provides an interface for a physical thing
called Thing Description5 (TD). TD describes a Thing in terms of its interactions
and meta-data.
Industry 4.0: The Reference Architectural Model [4] (RAMI 4.0) is an ini-
tial standard developed for Industry 4.0. It proposes that all the Industry 4.0
components need common standards for communication and a standardized lan-
guage for exchange of information. RAMI 4.0 proposes that every Thing should
have its own Administrative Shell [4] which stores all the important data of a
physical thing or a software in digital format in a standardized language. TD can
be used as a basis to model the Administrative Shell of a Thing, as it provides
common standard for communication and enhances inter-operability between
the things in Industry 4.0.
4
https://www.w3.org/WoT/WG/
5
https://w3c.github.io/wot-thing-description/
Semantic Web Technologies (SWT): provides standardized knowledge
representation formalisms such as RDF6 , RDF Schema7 and OWL8 and query
language over the semantic data, called SPARQL9 . There exists a number of
semantic models for WoT which provide domain-dependent and domain - inde-
pendent vocabularies. Few of them are: (1) Semantic Sensor Networks ontology
(SSN) [5] is an OWL 2 ontology which models the sensors, actuators and their
contextual information. (2) eCl@assOWL [6] is an OWL ontology that models in-
dustrial products and services. It is created based on the eCl@ss10 cross-industry
data standard. Adoption of SWT has been a recent development in the industrial
domain [7, 8]. An important application of these technologies has been the for-
malization of information models and physical devices using ontologies providing
interoperability, un-ambiguous and machine-readable descriptions.
The state-of-the-art engineering of AS devices is typically done using
Software Engineering approach based on model-driven design. There are five
phases in the engineering of an embedded AS device. They are: 1. Design phase
2. Development phase 3. Engineering phase 4. Commissioning phase and 5. Op-
erating phase. According to the model-driven design, an engineer specifies a field
function or a data point in a model in the Design phase. The code generation is
run to produce a skeleton of a service that is supposed to implement the function
or data point in the Development phase. Finally, in the Engineering phase, the
engineer implements the service skeleton, deploys it in a service run-time (that
is embedded in a device) in the Commissioning phase and starts it. The current
way of engineering of embedded AS devices is time consuming and demands a
lot of human effort for implementation of the application and deployment. This
method is not suitable for ever-changing nature of mass customized production.
In contrast to this method, we propose a low-effort engineering method which
involves minimum human intervention in Section 4.
3 Research Challenges and Goal
We have set the following research goals to achieve flexibility in an AS for
mass customized production:
– Facilitate an AS infrastructure to be transparent in order to enable rapid
application development.
– Develop an end-to-end engineering approach to establish and configure
the interactions between the AS devices and re-engineer an AS to install
new functionality on it with low-effort and minimum human interven-
tion.
– Make the proposed semantic-based engineering approach easily usable for an
AS engineer with little knowledge of SWT.
6
https://www.w3.org/RDF/
7
https://www.w3.org/TR/rdf-schema/
8
https://www.w3.org/OWL/
9
https://www.w3.org/TR/rdf-sparql-query/
10
https://www.eclass.eu/
We identified the following research challenges that should be addressed
in order to achieve the goals mentioned above:
– How to make an AS infrastructure transparent for rapid application devel-
opment?
– The AS are complex, there exists large number of functionalities and inter-
connections on an AS which should be taken into consideration during the
engineering process. How to discover the functionalities on a complex
AS?
– How to engineer, configure and re-engineer an AS with low-effort,
minimum human intervention?
– We believe that SWT can tackle the above challenges. But, to make the pro-
posed semantic-based approach usable for AS engineers with little knowledge
of SWT is a challenge by itself.
The next section presents our approach to achieve the above mentioned re-
search goals by addressing these challenges.
4 Methodology
In this project, we develop a semantic-based approach for engineering and con-
figuring a WoT-enabled AS. Employing SWT in Web of Things is called SWoT
[9]. In this approach, an AS device is embedded into an electornic system which
can connect to the Web and interact with other devices using existing Web stan-
dards11 [10–12]. The following paragraphs present our approach ib WoT-enabled
AS:
Traperency of the AS infrasturture: We model the WoT-enabled AS,
their services and applications semantically using W3C WoT Thing Descrip-
tion (TD). A TD is semantically annotated by re-using the existing domain-
independent and domain-dependent models to enable cross-domain inter- oper-
ability [13] between the Things and their services. The TD of a device is stored
on the device itself . Enriching the device with its semantic description, rules
[14, 15] and semantic reasoning techniques makes an AS infrastructure trasperent
for rapid application development and equips the device with decision-making
support. This is a key feature for engineering with minimum human in-
tervention in our approach. As it enables local discovery [7, 16, 17] of function-
alities on an AS protecting its data ownership and also enables compatibility
check between the AS devices to be done in an automated fashion, during the
commissioning phase of the engineering process.
Low-effort Engineering: In a manufacturing process a task is usually per-
formed by letting the AS devices interact in a certain manner. It would be
beneficial to store this composition of interactions as a template for a later use;
In such a way that, a template can be effectively discovered and extended with
other templates. In order to achieve this, we have come up with a concept of
11
http://mqtt.org/documentation
”Template based engineering” where interactions between certain devices are
stored as an Engineering Template (ET). We develop a light-weight semantic
model to describe an ET, which can be stored and discovered from a semantic
repository as shown in Figure 1. In order to engineer an AS, an engineer discov-
ers an ET from the repository and instantiates it with the matching devices on
the AS, then the interactions between the devices is established by implement-
ing and configuring the interactions using scripts and existing Web standard
methods.
Low-effort Re-engineering: In the mass customized production, the de-
vices need to constantly update their functionality to meet the customer de-
mands. In order to update new functionality easily, we have come up with a
concept called Apps. An App is a semantic model which defines an added-value
functionality. Apps are stored in the semantic repository as shown in Figure 1,
which enables discovery and re-use of the Apps. An App model describes the
functionality of the App; and requirements that should be fulfilled by a device
to install the App. The App and the device semantic models enable automated
compatibility check in the commissioning phase, to ensure that the device has
the capability to run the App. Therefore, it minimizes the human intervention
during re-engineering. Moreover, the App model is directly run-able on the de-
vice using device run-time, which minimizes the effort during the engineering
process.
Easy-to-use Engineering Tool: Our semantic-based approach for end-to-
end engineering could be complex to use for an AS engineer with little knowledge
of SWT. Therefore, in oder to overcome this limitation, we develop an graphical
tool for our engineering approach as shown in Figure 1. The tool should support
an AS engineer in all phases of engineering. It should have the ability to guide
an engineer to model TDs, ETs and Apps; and do semantic-based discovery
on the semantic repository to discover the Apps, ETs and TDs and download
them to the tool (see Figure 1). The tool should have the ability to communicate
with an AS through a RESTful API to discover the functionalities on AS, install
Apps and scripts on a device; or instantiate, implement and configure an ET to
engineer an AS.
4.1 Basic Building Blocks
The devices under our consideration are resource-constrained devices which have
limited memory and processing power, PC-based semantic reasoning techniques
are not feasible on these devices [18]. Thus, in this project we use an embed-
ded micro reasoner which can run on the resource-constrained devices (see
Figure 1) with Unix / Linux platforms. The micro reasoner consists of two parts:
a micro event processing engine implemented in C, which is based on the
work from [19]. Event rules are used to do Complex Event Processing (CEP) of
the events from the AS devices. The rules can be added/deleted easily to the
engine over a RESTful API. The event rules and scripts can be directly deployed
on the devices from the engineering tool as shown in Figure 1. The second part
is a datalog reasoner12 which provides datalog reasoning on the device. The
micro reasoner is embedded in the edge device which in our case is SIMATIC
IOT204013 . An edge device is embedded on an AS which acts as a gateway be-
tween the AS and the cloud. In some cases, the micro-reasoner can also run on
the Class 2 resource-constrained devices [20] as shown in Figure 1.
Discovery of Semantically annotate
App & ET Register Script Library
Semantic Models Download Download
Add/Update/ Semantic-enabled
Delete/Query end-to-end engineering tool
Discover matching devices Deploys Apps, event rules, scripts
Edge Device
Micro reasoner
Micro Event Engine
...
CPS Embedded Device
Thing Description
...
Fig. 1: The System Architecture with basic building block components
5 Preliminary Results
We performed a feasibility test of our methodology presented above for the low-
effort re-engineering of an AS device to install new Apps on an AS with minimum
effort.
Demo setup: The implementation is demonstrated on the FESTO14 process
automation workstation shown in Figure 2. The workstation is equipped with a
few edge devices15 with micro reasoner running on them. All the sensors and the
actuators on the workstation are embedded with NodeMCUs16 and connected to
the edge devices. There is a binary float sensor on Tank 1, which detects overflow
in the tank. There exists a pneumatic valve which takes Boolean value as input
and turns on the valve to pump out the liquid from Tank 1. The workstation is
12
http://www.ccs.neu.edu/home/ramsdell/tools/datalog/datalog.html
13
http://docs-europe.electrocomponents.com/webdocs/1536/0900766b815365c3.pdf
14
http://www.festo-didactic.com/int-en/learning-systems/process-
automation/compact-workstation/mps-pa-compact-workstation-with-level,flow-
rate,pressure-and-temperature-controlled-systems.htm
15
http://docs-europe.electrocomponents.com/webdocs/1536/0900766b815365c3.pdf
16
https://nodemcu.readthedocs.io/en/master/
engineered such that when overflow occurs in Tank 1 then the pneumatic valve
will turn on to ensure overflow protection on Tank 1.
Use case: Our use-case was to ensure overflow protection on Tank 1. Imagine
a situation where the float sensor is malfunctioning then, the whole process will
be disturbed. In order to avoid the machine downtime, we re-engineered the AS
by installing an App on it which uses the liquid level values from the ultrasonic
sensor (which measures the level of liquid in the tank) on Tank 1 as shown in
Figure 2 to detect the overflow of the tank.
Demo steps: We implemented the proposed semantic-based re-engineering
approach and corresponding features in the engineering tool. The tool provides
an interface to the semantic repository to discover Apps, TDs and download
them to the tool. The tool connects to the edge devices on the AS (through a
RESTful API), and does distributed discovery for the devices and automated
compatibility check between the App and the device, locally on the edge de-
vice. We installed an App on the discovered edge device which fulfills the App
requirements. The App reads the liquid level values from the ultrasonic sensor
and detects the tank overflow. Thus, the AS is re-engineered with low-effort.
Result: We measured the time taken for distributed discovery and auto-
mated compatibility check. We tested the integration of engineering tool with
semantic repository and its interaction with the AS. It proved that our approach
is feasible to be applied on real-world use cases.
Ultrasonic sensor
Tank 1
Edge devices
Pneumatic valve
Float sensor
Tank 2
NodeMCU
Embedded
Ultrasonic
sensor
Fig. 2: Festo MPS Process Automation Workstation
6 Use cases and Evaluation Plan
We demonstrate the engineering of an AS using ETs and re-engineering of an
AS device on the following use cases:
– Plug and Play use case: When a new device is introduced into the worksta-
tion, we will demonstrate how our approach can be used to re-configure the
an AS easily using engineering ETs with minimum human effort, to adopt
the new device into the system. After the feasibility test, we will also evaluate
our approach on a large-scale industrial manufacturing unit.
– Re-engineering use case: In addition to the demo on the FESTO workstation,
we will demonstrate our approach for low-effort re-engineering on a large-
scale industrial manufacturing unit.
We will perform quantitative analysis to check the (1) time taken for distributed
discovery and automated compatibility check to find matching devices, (2) time
taken to implement and configure an ET. We will perform a qualitative analysis
as follows: we will invite the engineers of the AS with little knowledge of SWT
to test the engineering tool: We will give the engineers a task to engineer an
AS. (1) measure the time taken by them to do the engineering, (2) check the
quality of their engineering using our approach, (3) give a questionnaire to the
AS engineers and get their feedback regarding the pros and cons of the tool.
7 Conclusion and Future Work
In this project, we proposed a semantic-based approach for low-effort engineer-
ing and configuration and re-engineering of a WoT-enabled AS with minimum
human intervention. This approach makes an AS flexible for mass customized
production. We demonstrated our implementation of re-engineering approach
on a FESTO process automation workstation to test the feasibility of our ap-
proach. The following are the future steps in this project: (1) as a first step,
we develop an approach of engineering the AS devices with ETs, do distributed
automated compatibility checks between the AS devices, instantiate an ET, im-
plement and configure the interactions between the AS devices with minimum
effort. (2) second, we work further on the engineering tool to design, engineer
and implement ETs. (3) at last we do quantitative and qualitative analysis of
our approach according the evaluation plan mentioned in Section 6.
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