ArticlePDF Available

Abstract and Figures

The growing importance of manufacturing SMEs within the European economy, in terms of Gross Domestic Product and number of jobs, emphasizes the need of proper ICT tools to support their competitiveness. Major ICT players already offer one-does-all Product Lifecycle Management suites, supporting several phases of the product-process-plant definition and management. However, these do also show consistent shortcomings in terms of SME accessibility, degree of personalization and they often lack of an acceptable level of interoperability. These problems are being addressed by the development of a Virtual Factory Framework (VFF), within an EU funded project. The approach is based on four pillars: 1) Semantic Shared Data Model, 2) Virtual Factory Manager (VFM), 3) Decoupled Software Tools that lay on the shared data model and can interact through the VFM, 4) Integration of Knowledge. This paper will focus on the Virtual Factory Manager, proposing an evolution of the former VFF second Pillar (Sacco et al, 2010), that acts as a server supporting the I/O communications within the framework and its stored knowledge for the decoupled software tools needing to access its repository.
Content may be subject to copyright.
Proceedings of DET2011
7th International Conference on Digital Enterprise Technology
Athens, Greece
28-30 September 2011
VIRTUAL FACTORY MANAGER OF SEMANTIC DATA
Giorgio Ghielmini
ICIMSI-SUPSI
giorgio.ghielmini@supsi.ch
Paolo Pedrazzoli
ICIMSI-SUPSI
paolo.pedrazzoli@supsi.ch
Diego Rovere
ICIMSI-SUPSI
diego.rovere@supsi.ch
Walter Terkaj
ITIA-CNR
walter.terkaj@itia.cnr.it
Claudio R. Boër
ICIMSI-SUPSI
claudio.boer@supsi.ch
Giovanni Dal Maso
Technology Transfer System S.r.l.
dalmaso@ttsnetwork.com
Ferdinando Milella
SimX ltd.
f.milella@simx.co.uk
Marco Sacco
ITIA-CNR
marco.sacco@itia.cnr.it
ABSTRACT
The growing importance of manufacturing SMEs within the European economy, in terms of Gross
Domestic Product and number of jobs, emphasizes the need of proper ICT tools to support their
competitiveness. Major ICT players already offer one-does-all Product Lifecycle Management
suites, supporting several phases of the product-process-plant definition and management. However,
these do also show consistent shortcomings in terms of SME accessibility, degree of personalization
and they often lack of an acceptable level of interoperability. These problems are being addressed
by the development of a Virtual Factory Framework (VFF), within an EU funded project. The
approach is based on four pillars: 1) Semantic Shared Data Model, 2) Virtual Factory Manager
(VFM), 3) Decoupled Software Tools that lay on the shared data model and can interact through the
VFM, 4) Integration of Knowledge. This paper will focus on the Virtual Factory Manager,
proposing an evolution of the former VFF second Pillar (Sacco et al, 2010), that acts as a server
supporting the I/O communications within the framework and its stored knowledge for the
decoupled software tools needing to access its repository.
KEYWORDS
Virtual Factory, Enterprise Modelling, Reference Model, Interoperability, Semantic Data Model
1. INTRODUCTION
Market needs and expectations require a
continuously rapidly evolving production
framework: thus production systems, from small to
large scale and integrated factories, have to be
conceived and set-up in shorter and shorter times
(Chryssolouris et al, 2008). Several critical aspects,
related to this need of rapid prototyping of factories,
have to be addressed: it is critical to provide
sufficient product variety to meet customer
requirements, business needs and technical
advancements (Huang et al, 2005), while
maintaining economies of scale and scope within
the manufacturing processes (Terkaj et al, 2009).
Therefore, the current challenge in manufacturing
engineering consists in the innovative integration of
the product, process and factory worlds and the
related data, aiming at synchronizing their lifecycles
(Tolio et al, 2010).
The creation of a holistic, integrable, up-
gradable, scalable Virtual representation of the
Factory can empower this synchronization,
promoting high cost savings in the implementation
of new manufacturing facilities or reconfiguration
of existing ones, thanks to the effective virtual
representation of buildings, resources, process, and
products: this is shown both by industrial practice
and academic scientific research. The entire factory
is simulated as a continuous and consistent digital
model, which can be used, without interruption, all
the way from the product idea to the final
dismantling of the production plants and buildings
(Bracht and Masurat, 2005).
These challenge is being addressed by the
development of a Virtual Factory Framework
(VFF), within an EU funded project
(http://www.vff-project.eu/). The approach is based
on four pillars: 1) Semantic Shared Virtual Factory
Data Model (VFDM), 2) Virtual Factory Manager
(VFM), 3) Decoupled Software Tools, based on the
VFDM and that can interact through the VFM, and
4) Integration of Knowledge. VFF objective is to
fosters an integrated virtual environment that
supports factory processes along all the phases of its
lifecycle.
This paper will focus on the Virtual Factory
Manager (VFM), proposing an evolution of the
former VFF Pillar II (Sacco et al, 2010). This
evolution finds its justification in the identified
weakness of the former second Pillar, found both in
the support to the data consistency check against
modifications performed by different modules and
in the integration of the knowledge layer with the
pure factory data layer. A viable solution has been
identified in the adoption of ontology as means for
data and relationships representation, promoting
knowledge integration in the data-model. This
approach introduces a modification in the overall
VFF architecture, where pillar IV (knowledge
integration) is no longer seen as foundation of Pillar
I (reference data model), as presented in (Sacco et
al, 2010), but rather considered as an additional
decoupled module (Figure 1).
This paper presents the new VFF framework born
from this evolution.
2. VIRTUAL FACTORY FRAMEWORK
As mentioned, an answer to the market
requirements previously highlighted has been
provided by the development of a first version of
the Virtual Factory Manager (Sacco et al, 2011).
That solution proved the validity of the concept of
having an integrated virtual environment supporting
the design and management of all the factory
entities, ranging from the single product to the
network of companies, along all the stages of the
factory lifecycle. The centralized data management
platform based on a common description of the
digital factory demonstrated the capability to
improve the integration process between software
design tools (existing and new developed ones) and
to provide a shared knowledge base to be used
during the factory modelling phases. Nevertheless,
the former approach showed some weaknesses both
in the support to the data consistency check against
modifications to parts of the factory instances
performed by different modules and in the
integration of the knowledge layer with the pure
factory data layer. The result, highlighted by
advanced tests, was a framework affected by some
problems of usability.
The main cause of this situation has been
identified in the impossibility of the previous
implementation of the VFDM, to represent not only
valid data structures, but also their semantics. A
viable solution has been identified in the adoption
of ontology as means for data and relationships
representation in order to improve the integration of
knowledge among the VFF pillars. This approach
introduces some modifications in the whole VFF
picture, affecting the way the components of the
architecture interact. Therefore, the result is a
tighter cooperation between the Knowledge
Manager and the VFDM pillars.
2.1. SEMANTIC VIRTUAL FACTORY
FRAMEWORK ARCHITECTURE
Figure 1 shows the new architecture of the Semantic
Virtual Factory Framework composed by the four
pillars of Semantic Shared Data Model (Pillar I),
Semantic VF Manager (Pillar II), Decoupled VF
Modules (Pillar III) and Knowledge Manager (Pillar
IV).
The Semantic VFDM establishes a coherent
standard extensible set of ontologies for the
common integrated representation of the factory
objects and of the factory knowledge domain,
basing on the tools of the semantic web (mainly the
Web Ontology Language - OWL). Section 3 is
dedicated to a thorough description of the new
Figure 1 - The Semantic Virtual Factory Framework architecture
Semantic VFDM approach and of the reasons that
drove the change.
This common ontology set is governed by the
Semantic VFM (Pillar II) that completes the
functionalities of access control, data versioning and
selective data query, already implemented by the
previous VFM, with a full support to the semantic
data validation. In this way, Decoupled Modules
(Pillar III) modifying single parts of the factory data
immediately receive feedback on the consistency of
their actions with the overall definition of the
factory instance. Section 4 and Section 6 are
respectively dedicated to the analysis of the
Semantic VFM and to the description of the current
prototype implementation.
In order to couple with the new features of the
VFM and with the new data exchange formats, it
has been necessary to intervene on the internal
architecture of the Decoupled Modules and, in
particular, of their VF Connector modules. Section
5 reports on the new structure of Pillar III, while an
example of new module interacting with the
Semantic VFM prototype is provided in Section 7.
Also the Knowledge Manager (Pillar IV), that was
the only component of the previous architecture
already based on the usage of ontologies, has been
affected by the new approach. With the new
structure, in fact, it can directly interface the
Semantic VFM as a decoupled module managing a
dedicated part of the Semantic Data Model
ontology. In this way it has been removed another
weak point of VFF that was represented by the need
for adaptation of formats and protocols between
pillars.
3. SHARED SEMANTIC DATA MODEL
The Reference Model (Pillar I) establishes a
coherent standard extensible Virtual Factory Data
Model (VFDM) for the common representation of
factory objects related to production systems,
resources, processes and products. The common
data model can be considered as the shared meta-
language providing a common definition of the data
that will be governed by the VFM (Pillar II) and
used and updated by the Decoupled Functional
Modules (Pillar III).
According to the original requirements, the
VFDM has to be holistic, covering all the relevant
fields related to the Factory domain and exploit
existing technical standards to represent the data.
Moreover the VFDM has to be extensible and
guarantee the proper granularity, providing at the
same time the enablers for data consistency, data
safety, and proprietary data management.
Sacco et al (2011) conceived the VFDM as a set
of XSD files (W3C, 2004c) defining the structure of
the XML files that would be stored and managed by
the VFM. This solution offers relevant advantages
in terms of:
Syntactic validation of the XML files according
to the defined XSD files.
Rich expressiveness since several default data
types can be further extended and complex
constraints and properties can be modelled.
Possibility to integrate several XSD files within a
single project.
However, the XSD technology alone is not suitable
for knowledge representation and several flaws can
be highlighted:
No explicit characterization of data with their
relations on a semantic level.
Intradocument references are supported but
interdocument references (cross-references) are
poorly modelled, thus endangering referential
consistency.
Distributed data can be hardly managed.
The integration of different knowledge domains
can be cumbersome.
The presented considerations led to evaluate and
finally adopt the Semantic Web technologies which
offer key advantages to the whole VFF because they
enables to:
Represent a formal semantics.
Efficiently model and manage distributed data.
Ease the interoperability of different applications.
Process data outside the particular environment in
which it was created
Exploit generic tools that can infer from and
reason about an ontology, thus providing a
generic support that is not customized on the
specific domain.
The new semantic VFDM has been designed as an
ontology (W3C, 2004a) by adopting the OWL
language (W3C, 2004b). In particular, it defines all
the classes, properties and restrictions that can be
used to create the individuals to be stored in the data
repository (Pillar II). Given the wide range and
heterogeneity of the knowledge domains to be
covered by the VFDM in the scope of VFF, it is
necessary to integrate various knowledge domains
as already highlighted by Colledani et al (2008) and
Valente et al (2010) in previous related works.
Therefore, the VFDM has been decomposed into
macro areas (i.e. bricks), creating a hierarchical
structure of sub-ontologies that have been named
Factory, Building, System, Resource, Process,
Product, Strategy, Performance and Management.
This architecture allows decomposing the problem,
downsizing its complexity while keeping a holistic
approach. These sub-ontologies have been
developed by referring to the state-of-the-art
technical standards available in the different
domains, and in particular the Industry Foundation
Classes (IFC2x3, 2006), STEP-NC (ISO 14649-
10:2004), and ISA-95 (ISA-95).
4. VIRTUAL FACTORY MANAGER
This section presents the analysis of the
requirements for the VFM (Sect. 4.1) and its
proposed architecture (Sect. 4.2).
4.1 VFM REQUIREMENTS
The main goal of the VFM design and
implementation consists in obtaining an open
integration platform representing a common and
shared communication layer between already
existing and newly developed software tools to
support the factory design and management.
The preliminary architecture of VFM proposed
by Sacco et al (2011) was related to a VF Data
Model based on the XSD/XML format. The
adoption of an ontology-based representation of the
VF Data Model in the VFF project has led to a re-
design of the VFM where Semantic Web
technologies have been exploited. In the new
architecture previous basic requirements have been
extended to include specific semantic
functionalities:
Platform independent interfacing capabilities.
The VF modules are software tools developed by
different vendors/organizations, with different
programming languages, operating systems and
HW architectures. The VFM has to interface all
of them by providing its service in an open and
“proper” way.
Management of concurrent access and data
consistency. Several software tools can access
and/or modify partial areas of the factory data at
different, and possibly overlapping, times.
Therefore, the VFM is required to ensure that
concurrent accesses occur without endangering
the data integrity and slowing down the planning
process to unacceptable levels.
Management of evolving Factory Data. The
VFM has to provide functionalities for managing
the evolution and revision of the data related to
complex entities like production systems,
processes and products. A typical VFDM object
is made by several files, depending on the sub-
ontologies it refers to, as described in section 3.
Hence, a coherent versioning mechanism must
take into consideration the inter-document
references between sub-ontologies.
Data safety must be ensured in case of hardware
failures or user errors.
Addition of customized functionalities. Third
party developers need an appropriate mechanism
to enrich the set of functionalities provided by the
VFM without impacting on its core.
Response time. The interaction between VFM
and the VF modules requires the support of
communication mechanisms that are able to
provide answers in an appropriate time frame.
A Semantic Web Endpoint which enables
stakeholders to query virtual factory models with
the required level of granularity for a more
efficient and selective data access.
Most of the above underlies the development of
the previous version of VFM. For this reason the
architecture of the new semantic version shares
similar features with its predecessor. However the
ability to support validation and queries of semantic
data introduces novelty aspects in the overall design
of VFM.
4.2 SEMANTIC VFM ARCHITECTURE
The architecture of the semantic VFM was designed
to provide support to the required functionalities.
Each solution implemented by the VFM is based on
stable and well established technologies in order to
obtain an overall system capable to respond to
industrial needs of reliability. The resulting VFM
architecture is shown in Figure 2 as an UML
component diagram.
The functionalities of the VFM are exposed as
web services that have been identified as a suitable
and widely adopted solution to guarantee platform
independent interfacing capabilities. The
Application Server provides the front end for the
exposure of VFM functionalities and takes care for
the information transport of the VFM.
The Information Exchanging Platform (IEP) is
the main component of the VFM and provides VF
modules and plugins with a high level access to the
two functional cores of VFM: the Versioning Layer
and the Semantic Layer. It represents the preferred
way (even if not the only one) to connect to the
VFM, since it provides a complete set of methods
for structured data retrieval and semantic validation,
data locking mechanism and factory version
management.
The Versioning Layer contains the VF Data
Repository where all the shared data are stored. The
evolution of the factory data is managed by the
Versioning System that organizes and updates the
set of virtual factory instances. The Versioning
System guarantees the data safety as well, since it
allows restoring an older version at any time, thus
preventing data losses due to user errors. Moreover,
rollback methods can be used in case of data
inconsistencies due to broken connections or other
factors, always ensuring data safety. In particular,
the locking mechanism exposed through the IEP
helps to manage the concurrent access of the VF
modules.
Figure 2 - Semantic VFM Architecture
The Semantic Layer is implemented by
embedding in VFM one of the most common and
reliable Semantic Web Frameworks: Jena (Jena,
2011). Through the IEP users can carry out
semantic validations of VFF models using Jena
functionalities directly on the server. Thanks to
Jena, the IEP can also provide a VFM SPARQL
endpoint. By starting a Query Session on data
extracted from the VF Data Repository it is possible
to perform SPARQL queries (W3C, 2008a).
Through queries each module (or plugin) can select
and aggregate information and be fed with exactly
the data it needs for its business process. Model
modifications can also be executed using the
SPARQL Update language (W3C, 2008a). Modified
models can then be serialised in output files in the
same format used by the VF Data Model ontology
(RDF/XML).
5. DECOUPLED VF MODULES
Currently many software applications, called VF
Decoupled Modules, are under development and
will interface the VFM for accessing the
information kept in the data model.
Since the VFM is the centre of the data exchange
among modules, it has been conceived with
openness in mind to be able to deliver data to the
large variety of tool involved in the factory planning
process. The decoupled modules range from
completely new developments to integration of
existing application, to off-the-shelf commercial
software, characterized by different operating
systems and development languages, among them
Windows, Linux and Java, C++, Python.
5.1. REQUIREMENTS ORIGINATED BY THE
VF MANAGER
Since the exposed functionality of the VFM is
implemented as a web service (W3C, 2011), all the
modules are required to implement a web service
client according to the WSDL file (Booth and Liu,
2007) describing the published interface.
Additionally, to address the issue that web services
are intrinsically stateless, the VFM has implemented
a few specific functions to keep track of the state of
its clients. Therefore the decoupled modules need to
actively support this mechanism. Finally, the data
received from the VFM are in RDF/XML format
(Beckett, 2004) and the utilization of third party
libraries for the handling of that format is essential.
5.2. ARCHITECTURE
The listed common requirements lead to a similar
overall module architecture which foresees a few
predefined component.
The following diagram illustrates the generic
architecture of a VF decoupled module with the
mentioned components and a section of the VFM in
the bottom part of the picture.
Figure 3 - Decoupled VF Module Architecture
5.2.1. VF Connector
Since all the decoupled modules will face common
tasks related to the VFM connection, in order to
avoid repeated development efforts among the VFF
partners, a specific VF Connector for the most
common development languages (C++, Java and
Python) has been implemented.
The VF Connectors take care of the web service
client implementation and the connection state
mechanism.
5.2.2. RDF/XML Library
Each decoupled module will manage different parts
of the data model in different ways. Nevertheless
most of the results coming from the VFM are in
form of RDF/XML streams so that the development
effort will be reduced using already existing third
party libraries conceived for RDF/XML data
manipulation. The following table lists some of the
most used open source libraries.
Table 1- RDF/XML Libraries
Library
Language
Redland RDF
Libraries
C with Python-
Perl- PHP-
Ruby-
Interfaces
RDFLib
Python
Jena RDF
API
Java
Protegé API
Java
Sesame
OpenRDF
Java
Semantic data handling obviously is more
complex than the one required for XSD/XML-based
models. Most of the VF Decoupled Modules are not
semantic applications (Motta and Sabou, 2006). As
such they access the VFDM semantic representation
only to extract and modify “plain” data. Indeed this
is one of the few disadvantages of the proposed
semantic approach that can be mitigated only by
fully exploiting the related technology to ensure the
full integration of the four Pillars of VFF.
5.2.3. Business Logic
This part of the software is peculiar to each module
and will be developed on top of the mentioned
components.
Nevertheless it is possible to distinguish two
substantially different functionalities; the ad hoc
developed modules will provide a specific logic and
expose it through a graphical user interface while
the adaptation modules will provide the required
interface for a seamless integration of existing
commercial tools.
6. VF MANAGER PROTOTYPE
The Semantic VF Manager has been implemented
on the basis of the previous prototype presented in
Sacco et al (2011). Even if this version is a
complete rewrite of the software, the main inspiring
guidelines that have driven the first prototype
release have not been changed. The choice of
development based on an open source and cross
platform architecture is still valid. This allows the
deployment of the tools in real industrial scenarios
where the VF Manager should be integrated into
existing legacy intranet architectures. Having
chosen to adopt technologies with proven reliability,
cross platform compatibility and well known by IT
personnel grants a smooth integration and
successful operation inside most of the existing
network configuration.
We hereby describe, for each of the main
components of the architecture shown in Figure-2,
the prototypal choices of the applied software tools.
The Application Server was implemented with
Apache HTTP Server, one of the most deployed and
reliable HTTP servers (The Apache Software
Foundation, 2011a). The Servlet Container was
developed with Apache Tomcat (The Apache
Software Foundation, 2011b), used in numerous
large-scale, mission-critical web applications across
a wide range of industries and organizations.
Tomcat is paired with “Tomcat mod” to support
integration with Apache HTTP server: this
connector redirects the information received by the
Apache Server to Tomcat, and therefore to the plug-
ins. The Versioning Layer was developed by
adopting Subversion (Collins-Sussman et al, 2004)
that is an open source version control system widely
used in the open source world. Access to the
ontology model, i.e. creating, writing and reading
models from OWL, has been implemented on top of
the Jena framework (Jena, 2011) which is a proven
library that implements Web Semantic in Java.
FRONT&END
MANAGERS
UTILITIES
IEP
Web'Service
Administration
Web'Pages
Users
Web'Pages
Jena Subversion Transaction Users
Projects Working'
Copies
Ontology'
Models Logging
Figure 4 - Architecture of the VF Manager Prototype
The architecture of the VF Manager in Figure-4
highlights the internal division in tree main layers:
front end, managers and utilities.
The front end layer consists of three components
that expose the functionalities:
IEP provides a SOAP Web Service to the VF
modules.
Administration lets the administrative personnel
manage the user and the opened sessions using a
web-based interface.
Users Pages are web pages that a user can access
to see his open session and to chat with other
active users.
The managers layer groups most of the business
logic of the VF Manager and is composed of the
following components:
Jena handles the ontology model using the Jena
framework;
Subversion is responsible for data storage and
versioning using the SVNKit library (SVNKit,
2011);
Transaction manages user sessions and commits,
coordinating the Jena, Subversion and Users
components;
Users manages the user database, access control
and sessions lists.
The utilities layer consists of components
providing a common infrastructure to handle:
Projects
Working copies
Ontology models
Logging
All this components have been developed in Java
and JSP (Java Server Pages) and deployed as
Tomcat web application.
This prototype is an evolution of the software
presented in Sacco et al (2011) and focuses on the
implementation of a wider set of features:
Data versioning
SPARQL Query
Locking
Granularity
Dependencies
Web access
The previous prototype focused only on
versioning and locking. A key feature introduced in
this version is granularity, implemented with the
concept of projects to represents the minimal
independent unit (i.e. set of files) that can be locked.
A project can have one or more dependency on
other projects, allowing reusing of shared resources.
A project can not only declare its dependencies
allowing a module to manually retrieve them - but
can also automatically include them to build a
complete ontology model. This model can be
queried using SPARQL language (W3C, 2008a).
Finally in this prototype we have implemented the
ability to access the VF Manager using an Internet
browser: administrators and registered user can
access some functionalities of the VF Manager
without needing to use a module application.
Further development of the prototype is targeted
at consolidating the robustness of the implemented
features and at improving the functionalities that
can be accessed from the web interface. This last
development will eventually enable a user to access
the data in the VF Manager without relying to any
module, maybe allowing limited editing
capabilities. Another important features that will be
enabled by the web interface is the access from
mobile devices, such as smart phones and tablets.
7. FLP – A DECOUPLED VF MODULE
In order to illustrate the interaction of decoupled
modules with the VFM one among the several tools
developed for the VFF project has been chosen, the
Factory Layout Planner (FLP) (Ceruti et al, 2010).
The FLP, together with other two applications
(GIOVE Virtual Factory by ITIA-CNR and Visual
Components with SimX adaptation module), was
already involved in the feasibility demonstration of
the former VFM (Sacco et al, 2011).
7.1. FUNCTIONALITY
FLP is a client/server application that enables the
collaborative development of a factory layout.
The main functionality of the FLP consists in:
3D visual editing of the layout
3D visual editing of the building
running Discrete Events Simulation (DES)
Figure 5 - FLP Main Window
The application is characterized by a two-level
architecture with a fat client dealing with complex
3D models and real time requirements, and a server
which acts as a synchronization manager and as
VFM web client.
7.2. IMPLEMENTATION
FLP is an application written in Java. For handling
the data received from the VFM in RDF/XML
format, the third party library Jena (Jena, 2011) is
used.
7.3. ACCESSED DATA
FLP will interact with different areas of the VFDM
to exploit its functionality:
the multisite information - the production plants
of the enterprise [read-write]
the building data [read-write]
the resources templates - for every resource
template (or type) a set of information (icon,
VRLM file(s) for 3D representation, properties
and further data) [read-only]
the layout data (which contains for example the
instantiated resources, their position and their
property values) [read-write]
the production plans and processes data to feed
the DES engine [read-only]
the results of the DES simulation [read-write]
7.4. SAMPLE USE CASES
The prototype of the VFM hosts a partial Data
Model and enables the FLP to access data related to
the layout of a factory, both resource types and
instantiated resources. The FLP use cases treated
here are related to those data.
7.4.1. Caching resources types (read only)
The FLP composes a layout by creating and placing
into the 3D window instances of resources from the
resources catalogue. The FLP itself does not modify
the resource templates, which consists of resource
type description data and typically very large 3D
model files (those data are not subject to frequent
changes). Given those assumptions, for performance
purposes, the FLP maintains a local cache of the
data by checking from time to time if a
synchronization of the local cache is required.
The steps to accomplish this task consist in
select the current revision of the sub-project
“Resource Library
download the ontology file(s) containing the
individuals
load the file(s) into a Jena ontology model in
order to access the content
retrieve all the 3D files from the “resource
cataloguefolder and store them locally
7.4.2. Layout planning (read-write)
The FLP user selects the current version of a layout
with the purpose of modifying it. It must signal to
the VFM its intention, so that other users do not
modify the same data and the Data Model remains
consistent. Precondition for this use case is that the
local catalogue of resources has been successfully
synchronized for the selected project.
The additional steps (compared with use case
7.4.1.) required to accomplish this task consist in:
start a transaction on the selected project
display all the instances of resources defined in
the project in a editable 3D view of the layout
apply the modifications to the Jena ontology
model and modify the local project file(s)
send back the modified files to the VFM
make the changes permanent and available to all
others VFF users by committing the open
transaction
8. CONCLUSIONS
The new approach driven by the Semantic VFDM
and enabled by the Semantic VFM represents a step
forward in the improvement of the Virtual Factory
Framework and in particular towards the target of a
fully integrated architecture of all the Pillars. Data
individuals and their Semantics come now from the
same coherent source and can be seen by different
perspectives, according to the needs of the
accessing clients (Knowledge Manager or
Decoupled Modules).
A first prototype of the Semantic VFM exploring
the potentials and the issues related to this new
approach has been presented. In particular, the
applied Semantic Web technologies represent the
cornerstone to obtain a framework where the
different stakeholders can effectively contribute in a
harmonized way to the definition of the virtual
factory along all the phases of its lifecycle.
In the coming months improved versions of the
VFM will implement the defined architecture and
fulfil the expected functionality. An increasing
number of Decoupled Modules will interface the
VFM and fill in the VF Data Repository with
individuals according to the developed Virtual
Factory Data Model, thus validating the new
approach.
9. ACKNOWLEDGMENTS
The research reported in this paper has received
funding from the European Union Seventh
Framework Programme (FP7/2007-2013) under
grant agreement No: NMP2 2010-228595, Virtual
Factory Framework (VFF).
REFERENCES
Beckett, D., “RDF/XML Syntax Specification
(Revised)”, W3C, 2004, Retrieved: 15.06.2011,
<http://www.w3.org/TR/rdf-syntax-grammar/>
Booth, D. and Liu, C.K., “Web Services Description
Language (WSDL) Version 2.0 Part 0: Primer”, W3C,
2007, Retrieved: 15.06.2011,
<http://www.w3.org/TR/wsdl20-primer/>
Bracht, U., Masurat, T., "The digital factory between
vision and reality", Computers in Industry, Volume
56, Issue 4, 2005, pp. 325333
Carroll, J.J., Dickinson, I., Dollin, C., Seaborne, A.,
Wilkinson, K. and Reynolds, D., “Jena: Implementing
the Semantic Web Recommendations”, Proceedings of
the 13th international World Wide Web conference,
2003, pp 74-83
Ceruti, I.F., Dal Maso, G., Ghielmini, G., Pedrazzoli, P.
and Rovere, D., “Factory Layout Planner”, ICE - 16th
International Conference on Concurrent Enterprising,
2010, Lugano, Switzerland
Chryssolouris, G., Mavrikios, D., Papakostas, N.,
Mourtzis, D., Michalos, G., Georgoulias, K., "Digital
manufacturing: history, perspectives, and outlook",
Proceedings of the Institution of Mechanical
Engineers Part B: Journal of Engineering
Manufacture, Volume 223, No. 5, 2008, pp.451-462
Colledani, M., Terkaj, W., Tolio, T. and Tomasella, M.
“Development of a Conceptual Reference Framework
to manage manufacturing knowledge related to
Products, Processes and Production Systems”, In:
Bernard A, Tichkiewitch S (eds), Methods and Tools
for Effective Knowledge Life-Cycle-Management”,
Springer, 2008, pp 259-284.
Collins-Sussman, B., Fitzpatrick, B.W. and Pilato, C.M.,
“Version Control with Subversion”, 1st Edition,
O'Reilly Media, Sebastopol, CA, 2004, p 320
Colombetti, M., “Ingegneria della conoscenza: modelli
semantici”, 2010-11 Edition, Facoltà di ingegneria
dell’informazione, Politecnico di Milano, Italy, 2011,
p 42
Huang, G.Q., Simpson, T.W. Pine II, B.J., “The power of
product platforms in mass customization”,
International Journal of Mass Customisation, Vol. 1,
No. 1, 2005, pp 1-13
ISA-95, “ISA-95: the international standard for the
integration of enterprise and control systems”, ISA-
95.com, Retrieved: 15.06.2011, <http://www.isa-
95.com/>
Jena, “Jena A Semantic Web Framework for Java”,
SourceForge.com, 2011, Retrieved: 15.06.2011,
<http://www.openjena.org/>
IFC2x3, “IFC2x3 Release”, buildingSmart, 2006,
Retrieved: 15.06.2011, <http://buildingsmart-
tech.org/specifications/ifc-releases/ifc2x3-release>
Mc Bride, B., “An Introduction to RDF and the Jena
RDF API”, 2010, Retrieved: 15.06.2011,
<http://jena.sourceforge.net/tutorial/RDF_API/>
Mc Carthy, P., Search RDF data with SPARQL”, IBM,
developerWorks, 2005, Retrieved: 15.06.2011,
<http://www.ibm.com/developerworks/xml/library/j-
sparql/>
Motta, E. and Sabou, M., “Next Generation Semantic
Web Applications”, 1st Asian Semantic Web
Conference (ASWC), 2006, Beijing, China
Sacco, M., Dal Maso, G., Milella, F., Pedrazzoli, P.,
Rovere, D. and Terkaj, W., “Virtual Factory
Manager”, HCI International, 2011, Orlando, USA
Sacco, M., Pedrazzoli, and Terkaj, W., “VFF: Virtual
Factory Framework”, ICE - 16th International
Conference on Concurrent Enterprising, 2010,
Lugano, Switzerland
SVNKit, “[Sub]Versioning for Java”, TMate Software,
2011, Retrieved: 15.06.2011, < http://svnkit.com/>
The Apache Software Foundation, “Apache HTTP Server
Project”, The Apache Software Foundation, 2011,
Retrieved: 15.06.2011, <http://httpd.apache.org/>
The Apache Software Foundation, “Apache Tomcat 6.0”,
The Apache Software Foundation, 2011, Retrieved:
15.06.2011, <http://tomcat.apache.org/tomcat-6.0-
doc/index.html>
Terkaj, W., Tolio, T., Valente, A., “Designing
Manufacturing Flexibility in Dynamic Production
Contexts”, In: Tolio, T. (ed) Design of Flexible
Production Systems. Springer, 2009, pp 1-18
Tolio, T., Ceglarek, D., ElMaraghy, H.A., Fischer, A.,
Hu, S., Laperrière, L., Newman, S., Váncza, J.,
“SPECIES -- Co-evolution of Products, Processes and
Production Systems”, Cirp Annals-Manufacturing
Technology 59 (2), 2010, pp 672-693
Valente, A., Carpanzano, E., Nassehi, A. and Newman,
S. T., “A STEP compliant knowledge based schema to
support shop-floor adaptive automation in dynamic
manufacturing environments”, Cirp Annals-
Manufacturing Technology 59 (1), 2010, pp 441-444
W3C, “OWL Web Ontology Language - Use Cases and
Requirements”, W3C, 2004a, Retrieved: 15.06.2011,
<http://www.w3.org/TR/webont-req/#onto-def>
W3C, “OWL Web Ontology Language - Reference”,
W3C, 2004b, Retrieved: 15.06.2011,
<http://www.w3.org/TR/owl-ref/>
W3C, “SPARQL Query Language for RDF”, W3C,
2008a, Retrieved: 15.06.2011,
<http://www.w3.org/TR/rdf-sparql-query/>
W3C, SPARQL Update”, W3C, 2008b, Retrieved:
15.06.2011,
<http://www.w3.org/Submission/SPARQL-Update/ >
W3C, “Web Services Activity”, W3C, 2011, Retrieved:
15.06.2011, <http://www.w3.org/2002/ws/>
W3C, “XML Schema Part 1: Structures Second Edition”,
W3C, 2004c, Retrieved: 15.06.2011,
<http://www.w3.org/TR/xmlschema-1/>
“ISO 14649-10:2004 Industrial automation systems and
integration -- Physical device control -- Data model
for computerized numerical controllers -- Part 10:
General process data
... As an example, the location of information about orders, products, machines, the available work force and the overall factory are rarely available in a unified database and a uniform format. The related idea of a Virtual Factory [15] proposes a framework Figure 1: Virtual Factory Framework as proposed by [5] that links all this information together, providing a mirror of the real factory (see Figure 1) and thus paving the way towards more innovative factory prototyping, assembly line optimization, product design and mass customization [13]. In order to realize such a virtual factory, a number of interoperability challenges need to be solved. ...
Conference Paper
Keeping factories running at any time is a critical task for every manufacturing enterprise. Optimizing the flows of goods and services inside and between factories is a challenge that attracts much attention in research and business. The idea to fully describe a factory in a digital form to improve decision making is called a virtual factory. While promising virtual factory frameworks have been proposed, their semantic models lack depth and suffer from limited expressiveness. We propose an enhanced semantic model of a factory, which enables views spanning from the high level of supply chains to the low level of machines on the shop floor. The model includes a mapping to relational production databases to support federated queries on different legacy systems in use. We evaluate the model in a production line use case, demonstrating that it can be used for typical factory tasks, such as assembly line identification or machine availability checks.
... As an example, the location of information about orders, products, machines, the available work force and the overall factory are rarely available in a unified database and a uniform format. The related idea of a Virtual Factory [15] proposes a framework Figure 1: Virtual Factory Framework as proposed by [5] that links all this information together, providing a mirror of the real factory (see Figure 1) and thus paving the way towards more innovative factory prototyping, assembly line optimization, product design and mass customization [13]. In order to realize such a virtual factory, a number of interoperability challenges need to be solved. ...
... The current software system is integrated with the Virtual Factory Framework (VFF) and is able to: (1) load data concerning manufacturing system's bill of material, bill of processes and resource; (2) write data concerning the short term scheduling of the manufacturing system, in particular the Gantt chart and the key performance indicators (KPIs) derived by the scheduling. VFF is a framework providing a collaborative virtualized environment, which facilitates the sharing of factory resources, manufacturing information and knowledge, and supports the factory planning phases ranging from the requirements definition up to factory dismantling [13]. The interoperability between different SW modules used during the phases of factory lifecycle that is offered by VFF reduce time and effort required for data translation to the various formats of each SW module. ...
Article
The aim of this paper is the presentation of a scheduling method, its implementation to a software system, and its application to a commercial refrigerator factory. The method employs the modeling of the factory's resources and the assignment of the workload of the resources in a hierarchical fashion. The developed software system simulates the operations of the factory and provides a schedule for the manufacturing system's resources. The system is integrated with a holistic virtual platform, namely Virtual Factory Framework that allows it to exchange data related to product, process, resources, and key performance indicators along with other software components also integrated with the Virtual Factory Framework. A set of digital scheduling experiments with data, coming from a real manufacturing system are conducted in order to validate the proposed method and the implemented system under different operational conditions.
... However, the XSD technology alone is not suitable for data consistency checks and knowledge representation. A more viable solution has been identified in the adoption of ontology as means for data and relationships representation, promoting knowledge integration in the data-model (Ghielmini et al, 2011). According to its latest architecture, the Information Exchanging Platform (IEP) is the main component of the VFM and provides VF modules with a high level access to the two functional cores of VFM: the Versioning Layer and the Semantic Layer. ...
Article
Full-text available
Virtual manufacturing concepts have been adopted by most of the industrial companies, including the small and medium ones, to face the global competition and deal with the top challenges of manufacturing industry, i.e. improving the quality, reducing the delivery time and decreasing the costs. However, most of the virtual manufacturing methodologies, tools and software systems are not integrated well enough to perform the required activities in an efficient manner. The attention is usually focused on local and specific proficiency, thus jeopardizing the sharing of information between the departments, the parallelization of work and the communication along the product or factory life-cycle. Indeed, the transmission of data and results is usually difficult and carried out by means of expensive and/or time-consuming manual work. This paper presents a software tool, named Design Synthesis Module (DSM), to face some of the aforementioned problems by adopting the approach proposed by the Virtual Factory Framework project, consisting in a holistic virtual environment that integrates several decoupled functional tools sharing the same data model to support the design and management of factories. The proposed solution represents one of the tools integrated in VFF and aims at improving the proposal and design phases of production lines in terms of quality, time and cost by supporting the management of production system configuration data across several departments. DSM will support the bidding and system design activities by enabling a quick evaluation of system configurations, easy adjustments and reuse of data, and the concurrent design and integrations with other tools.
... A possible communication architecture could be based on "High Level Architecture " (HLA) [23], a standard that provides a common Application Program Interface (API) allowing all modules to invoke specific primitives to exchange data each other. VHM is based on the "Virtual Factory Manager" (VFM) [24] that acts as a server supporting the I/O communications within the framework for the modules needing to access its data repository. Since VHM has to manage the real time communication between software applications in the domestic environment, it is necessary to investigate an extension to what is already implemented in the VFF. ...
Conference Paper
Contemporary design is characterized by the paradigm shift from a one-size-fits-all, oriented to the standard man, to an holistic and inclusive one-size-fits-one, that takes into account the full range of human diversity. Following the new paradigm, the “Design for All” Italian research project aims at realizing an effective demonstrator of a framework that promotes a design of an AAL oriented to the real individual, considering everybody in his peculiarities. On the one hand, the framework handles the knowledge about the home environment, also through innovative approaches aimed at modeling specific scenarios representing the relevant states of the individuals (situation and context awareness). On the other hand, it allows various software tools supporting the entire home’s life cycle to exchange the knowledge in a smart manner. Mainly focused on interoperability aspects, the paper describes the motivations behind the “Design for All” project concepts, together with the goals and the first findings. Finally, it presents a demonstration scenario that aims at testing and validating the framework.
... VFF is a framework that provides a collaborative virtualized environment which facilitates the sharing of factory resources, manufacturing information and knowledge and supports the factory planning phases ranging from the requirements definition up to factory dismantling [10]. The approach of VFF is based on the four following pillars: 1) Semantic Shared Virtual Factory Data Model (VFDM); 2) Virtual Factory Manager (VFM); 3) Decoupled VF Modules; 4) Integration of Knowledge. ...
Conference Paper
Full-text available
This research work deals with the early design of manufacturing systems following a knowledge management approach. The proposed knowledge based framework facilitates the definition, storage and extraction of past knowledge in terms of production line layouts. Semantics technology and artificial intelligence approaches such as inference rules and similarity measurement are the main pillars of the framework. The knowledge based framework is integrated within a greater framework, virtual factory framework that allows the knowledge extraction from a series of software tools used during the whole factory lifecycle. The concept and the implementation is tested in the early design of a steel fabrication line case study. (C) 2013 The Authors. Published by Elsevier B.V. Selection and peer-review under responsibility of International Scientific Committee of the 2nd CIRP Global Web Conference in the person of the Conference Chair Dr. Sotiris Makris
Conference Paper
Full-text available
The aim of this paper is to introduce the main outcomes of the application of Augmented Reality (AR) features to manufactur- ing and industrial scenarios under a new perspective. While the request of industrial mixed reality technologies is continuously growing, the re- search community is still facing the crucial challenge to give a convenient answer to such needs. The problem of the development of adaptable and inexpensive AR solutions is herein addressed by proposing a new ap- proach for the application of augmented reality technology to lean-based visual communication transfer and exchange. This work starts from the concept of virtual factory, a place where the real production of future factories becomes fully merged with virtual reality features and utilities. Augmented reality applications may then be reinterpreted as lightweight tools that continuously interact with the virtual factory to support man- ufacturing and management tasks, providing just-in-time and adaptive augmented information to users. As a case study, several AR tools de- signed following these principles to support a real production process are presented.
Chapter
Full-text available
The aim of this paper is the presentation of a scheduling method, its implementation to a software system, and its application to a commercial refrigerator factory. The method employs the modeling of the factory’s resources and the assignment of the workload of the resources in a hierarchical fashion. The developed software system simulates the operations of the factory and provides a schedule for the manufacturing system’s resources. The system is integrated with a holistic virtual platform, namely Virtual Factory Framework that allows it to exchange data related to product, process, resources, and key performance indicators along with other software components also integrated with the Virtual Factory Framework. A set of digital scheduling experiments with data, coming from a real manufacturing system are conducted in order to validate the proposed method and the implemented system under different operational conditions.
Conference Paper
The purpose of this paper is to investigate Augmented Reality applied into a real industrial context (Industrial AR) from a new perspective: AR is not anymore seen as a standalone technology for assisting specific manufacturing tasks, but rather as a totally integrated framework within future factory workplaces. In the last 15 years, both academic and industrial research communities have seen the huge potentiality of AR in improving industrial performances in several scenarios, but it is undeniable that no killer-apps or de-facto standard as well as scalable solutions have been developed yet. The paper addresses the issue from a new and different point of view showing how AR can potentially be exploited in order to boost lean-based manufacturing and management processes, thus guaranteeing more efficient production and higher competitiveness. The paper is organized with the aim to underline the new and feasible opportunities offered by the proposed approach, as well as the main technological and conceptual challenges connected to it. Finally, a potential framework capable of enabling AR features for visual management in real factories is proposed.
Article
Full-text available
This paper serves as an extended editorial for this inaugural issue of the International Journal of Mass Customisation. Its main objective is to give a brief overview of the recent developments in Mass Customisation (MC) research and practices, although more comprehensive reviews should be referred to existing review articles (Silveira et al., 2001; Simpson, 2005). For this new journal, more position papers have been planned to appear. Materials are mainly drawn from well-cited monographs, conference proceedings and articles published on various MC topics. This new journal aims to serve the MC community as a major forum to exchange substantial ideas and share experiences, complementing newsletters and resources maintained at various websites (e.g., www.mass-customisation.org/; www.mass-customization.de/; www.mcustomization.de/).
Chapter
Full-text available
Manufacturing Flexibility is seen as the main answer for surviving in markets characterized by frequent volume changes and evolutions of the technological requirements of products. However, the competitiveness of a firm can be strongly affected by capital intensive investments in system flexibility. This chapter presents an approach to design new manufacturing system architectures endowed with the right level of flexibility required by the specific production problem. These systems are named Focused Flexibility Manufacturing Systems (FFMSs). The key idea consists in tuning system flexibility on the production problem to cope with uncertainty related to the evolution of product demand. The significance of this topic and its potential impact on the industrial sector in the medium-long run is testified by the interest shown by companies making initial efforts in this field.
Conference Paper
Full-text available
The current complex market highlights the need of software tools supporting product engineering and manufacturing during the various stages of product and factory lifecycles. These are designed focusing on specific tasks, thus missing to satisfy the requirements of networked collaboration and concurrent engineering for the design and management of products, processes and production systems. A major challenge consists in the integration and harmonisation of the knowledge related to the factory of industrial companies by using a variety of multidisciplinary software tools. The topic is addressed by software providers and the scientific community, as demonstrated by the European project "Virtual Factory Framework" (VFF) that aims at developing an integrated framework to implement the next generation virtual factory. This paper describes the motivations behind the VFF concepts, together with the goals and the first results. Finally, it is presented how the Virtual Factory will be permanently synchronised with the Real Factory to validate its expected time and cost savings during the factory lifecycle phases.
Article
Full-text available
Digital manufacturing has been considered, over the last decade, as a highly promis-ing set of technologies for reducing product development times and cost as well as for addres-sing the need for customization, increased product quality, and faster response to the market. This paper describes the evolution of information technology systems in manufacturing, outlin-ing their characteristics and the challenges to be addressed in the future. Together with the digi-tal manufacturing and factory concepts, the technologies considered in this paper include computer-aided design, engineering, process planning and manufacturing, product data and life-cycle management, simulation and virtual reality, automation, process control, shopfloor scheduling, decision support, decision making, manufacturing resource planning, enterprise resource planning, logistics, supply chain management, and e-commerce systems. These tech-nologies are discussed in the context of the digital factory and manufacturing concepts.
Chapter
Full-text available
The present work proposes a conceptual reference framework for the integrated modeling of product, production process and system data. The framework is flexible (easily adaptable to different production contexts), extendible and scalable (in terms of levels of details) and integrated (products, processes and systems are all considered and described). The framework has been developed as an object-oriented model by means of the UML (Unified Modeling Language) defacto standard. In particular, the class diagram of this UML model, representing the core portion of the framework, is described in detail. The conceptual reference framework was developed to support both researchers and industrialists – in different manufacturing domains – in the modeling activities behind their problem solving methodologies, also aiding them in exactly modeling the information they need. The basic idea behind the work is that a more effective use of the heterogeneous decision support methods, normally employed at the different enterprise levels, can be obtained if these methods are based a common conceptual model. The first two applications of the proposed reference framework are also described in the final sections.
Conference Paper
The Manufuture strategic research agenda identifies two fronts of intense and growing competitive pressure for European manufacturing: in the high-tech sector, we face other developed countries and, on the other hand, in more traditional sectors, low-wage countries pose a serious threat. One of the response envisioned and strongly promoted is the development of ground-breaking Information and Communication Technologies meant to support new approaches to industrial engineering. Clearly drawing inspiration from this vision, the tool presented in this paper, the Factory Layout Planning, aims to be such kind of technology, enabling the multi-site, multi-level distributed design of factory layout and performance simulation. This paper gives an overview on the main features, in terms of concrete software characteristics of this tool, that can be considered one of the cornerstones for the Next Generation Factory.
Article
https://www.w3.org/TR/rdf-sparql-query/ RDF is a directed, labeled graph data format for representing information in the Web. This specification defines the syntax and semantics of the SPARQL query language for RDF. SPARQL can be used to express queries across diverse data sources, whether the data is stored natively as RDF or viewed as RDF via middleware. SPARQL contains capabilities for querying required and optional graph patterns along with their conjunctions and disjunctions. SPARQL also supports extensible value testing and constraining queries by source RDF graph. The results of SPARQL queries can be results sets or RDF graphs.