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  <front>
    <journal-meta />
    <article-meta>
      <contrib-group>
        <contrib contrib-type="author">
          <string-name>Artem A. Nazarenko</string-name>
          <email>a.nazarenko@campus.fct.unl.pt</email>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Carlos Lopes</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Jose Ferreira</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Philip Usher</string-name>
          <email>philip.usher@informationcatalyst.com</email>
          <xref ref-type="aff" rid="aff1">1</xref>
          <xref ref-type="aff" rid="aff2">2</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>João Sarraipa</string-name>
          <xref ref-type="aff" rid="aff0">0</xref>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Caparica</string-name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <contrib contrib-type="author">
          <string-name>Portugal</string-name>
          <xref ref-type="aff" rid="aff1">1</xref>
        </contrib>
        <aff id="aff0">
          <label>0</label>
          <institution>CTS, UNINOVA, DEE, Faculty of Sciences and Technology, Nova University of Lisbon</institution>
          ,
          <addr-line>2829-516, Monte</addr-line>
        </aff>
        <aff id="aff1">
          <label>1</label>
          <institution>Data Harmonization</institution>
          ,
          <addr-line>(iv) Orchestration</addr-line>
        </aff>
        <aff id="aff2">
          <label>2</label>
          <institution>Information Catalyst for Enterprise (ICE)</institution>
          ,
          <addr-line>37 Crewe Road, Haslington, Crewe</addr-line>
          ,
          <country country="UK">United Kingdom</country>
        </aff>
      </contrib-group>
      <abstract>
        <p>Zero Defects Manufacturing Platform (ZDMP) is an initiative aimed at providing the necessary platform and tools to facilitate the transformation to the 4th industrial revolution. In this work we are addressing components that are being developed within the Package 5 (WP5). To suit ZDMP's objectives, the core functionalities are implemented as separate components and adjusted to the 4-tier architecture. In other words, every WP 5 component is aligned with corresponding layer: Developer Tier, Platform Tier, Enterprise Tier and Edge Tier. Moreover, every component belongs to one of the functional blocks that are also in the scope of the work: (i) Data Acquisition, (ii) Industrial Network Support, (iii) Autonomous computing, and (vi) Analytics. At the end of the article we present a small scenario with some of the WP5 components executed at design- or run-time. Platform, vf-OS Zero Defects Manufacturing Platform (ZDMP), Industrial IoT, Industry 4.0, Manufacturing</p>
      </abstract>
    </article-meta>
  </front>
  <body>
    <sec id="sec-1">
      <title>1. Introduction</title>
      <p>Importance of the transformation of the European industry in the context of the 4th Industrial
Revolution or Industry 4.0 is difficult to overestimate. One of the reasons is the necessity to remain
competitive in the highly turbulent environment of the present time, whereas being able to produce
high quality products at a low cost and reduce the amount of defected products, scrap output, failures
and downtime. In this regard, the concept of zero-defects in the quality management is one of the
corner stone’s during the transformation towards Industry 4.0, both in terms of the digitalisation of
production processes, as well as the digitalisation of the product quality control.</p>
      <p>The goal of the ZDMP (Zero Defects Manufacturing Platform – www.zdmp.eu) project is to
develop and provide a digital ecosystem with the digital marketplace for connected smart factories,
facilitating the compliance with the principles of the Industry 4.0. ZDMP will provide a set of tools
for each step of production, while giving a possibility to extend the features using an applications
store where end users will be able to add these applications as extensions to the platform according to
their needs. In this context, ZDMP allows end-users to connect their systems (i.e. shop-floor and
Enterprise Resource Planning systems) to acquire the platform`s functionality being able to control
different stages of the production process considering time constraints and product quality. Users can
also request new applications and software/hardware developers can use the ZDMP SDK (Software
Development Kit) to build new</p>
      <p>Apps for them quickly using the projects toolkit and platform
components. In this work we are addressing components that are being developed within the Work
Package 5 (WP5). To suit ZDMP’s objectives, the core functionalities are implemented as separate
components and adjusted to the 4-tier architecture.
EMAIL:</p>
      <p>2020 Copyright for this paper by its authors.</p>
      <p>In terms of the usability, ZDMP will reuse outcomes / concepts of other research projects, such as:
Cloud Collaborative Manufacturing Networks (C2NET), Cloud-based Rapid Elastic Manufacturing
(CREMA), and especially Virtual Factory Operating System (vf-OS) which already includes more
generic SDK/App. This will allow for better and faster development of the platform components in
WP5-8. In addition, ZDMP will focus on the integration activities and develop suitable kick-start
applications for the 4 domains pilots, as well as shape the holistic environment.</p>
    </sec>
    <sec id="sec-2">
      <title>2. WP5 review</title>
      <p>The overall architecture of the technical components of ZDMP is based on 4-tier model. The tiers
are as follows: Developer Tier, Platform Tier, Enterprise Tier and Edge Tier. The main task of the
Edge Tier is to enable the data collection from various heterogeneous sources such as sensors,
actuators, devices and system components. It also allows some critical functionality to be delivered in
the close proximity to the data sources, which might be useful in the case of asynchronous data
exchange patterns. The Enterprise Tier is responsible for implementing the high-level communication
among various users, as well as aspects related to running of the containers. This tier delivers the
components for set up and maintaining the platform, whereas not providing any core functionality of
the ZDMP. On the other hand, in the Platform Tier the core functionalities covering monitoring,
alerting, high-level orchestration of the platform components and data processing are implemented.
And finally, the Developer Tier targets particular users’ needs and requirements. The components of
this tier are provided as containers allowing building the complex applications comprised of
containers to be later uploaded to the Marketplace.</p>
      <p>
        This article targets exclusively the components developed within the WP5 of the ZDMP. To
clarify which components are belonging to which tier the general view of the WP5 components in
regard to the 4-tier model is presented in Figure 1. The general view of the mapping of all
components developed within the ZDMP project to the 4-tier architecture can be found in [
        <xref ref-type="bibr" rid="ref1">1</xref>
        ].
      </p>
      <p>
        Important detail that needs to be mentioned is that besides the consideration of the framework
through the prism of the 4-tier model, the components are also separated on run-time and design-time.
Thus, in the Figure 1 the components delivered within the Platform Tier are implemented at run-time,
whereas the components from the Developer Tier are created at design-time. This separation allows
identifying the decision space for the entities inside the Edge Tier through the models established at
the design-time inside the Developer Tier, whereas capturing the context and reflecting behavioural
parameters at the run-time inside the Platform Tier [
        <xref ref-type="bibr" rid="ref2">2</xref>
        ].
      </p>
    </sec>
    <sec id="sec-3">
      <title>3. WP5 review</title>
      <p>In this chapter the core services or components of the WP5 are represented. First component is the
Data Acquisition that collects data from factory’s shop floor, ERP systems, and partners to assist,
detect, and monitor the production process in real-time or close to real-time manner. This creates a
challenge in the interoperability area where security and reliability are of main concern. Thus, ZDMP
will offer the end users a set of applications to choose depending on the functionality, used
communication protocol, and data source types. Data Analytics is considered as one of the key pillars
in the ZDMP architecture. In this sense, the user will benefit from the reasoning applications that are
offered by the platform. Additionally, and intrinsic to this feature, Big Data management will be
employed to detect and/or predict any defects in the production process and parts that lead to delay or
inconsistency in the delivery of the further products. The Resource Orchestration is provided to act for
avoiding any defects in the production process. In addition, assessment will be provided by the
platform on product quality assurance in case there is misalignment with the product quality
standards. Further, the orchestration takes the human into account, where collaboration is needed in
manual production systems.</p>
      <p>The WP5 is divided into six components that are described in the next sub-chapters.
3.1.</p>
    </sec>
    <sec id="sec-4">
      <title>Data Acquisition and IIoT</title>
      <p>Data Acquisition and IIoT component delivers the main input to the platform. It provides an
interface with a number of external sources to gather data. The external sources can be represented as
industrial automation devices (PLCs, smart sensors, RFID readers, etc), ERP systems, SCADA/MES
systems/data, and existing databases. The component offers a set of interfaces to bridge the Platform
Tier with heterogeneous sources, whereas providing the abstraction level to hide the communication
complexity from the other components. This component has the following main elements:
 Data Source Adapters are intended to perform the read/write operations and manage
configuration, status and command data of the end-devices. Each Adapter bridges the end-devices
with the Data Source Manger that contains the relevant configuration data. Moreover, this
component contributes to interoperability by enabling conversion from the device-specific
protocols to the formats utilized within ZDMP. Both synchronous and asynchronous data
transmission patterns are considered.
 Data Source Manager is responsible for managing of end-device configuration and
metadata, and gathering the logs.
 Configuration UI, the main goal of this component is to allow the user to access and change
the configuration data of the end-devices.
 Data Source Registry: is the repository for the configuration data.
 Variety of APIs: the component provides a set of APIs including Metadata API, Logging
API, Security API, Data Source Query API and Data Source Gateway API. The last one provides
on the spot an access to configuration and end-device data for the rest of the platform, whereas
directly supplying the Harmonisation module with necessary data.</p>
      <p>This component utilizes some deliverables based on previous progress Cumulocity IoT2 and the
vf-OS IO toolkit3. This will allow the connection via various protocols (eg OPC-UA4, OMA
Lightweight Machine to Machine5, IPSO Smart Objects6).
3.2.</p>
    </sec>
    <sec id="sec-5">
      <title>Robust Industrial Network Support</title>
      <p>2 https://www.softwareag.cloud/site/product/cumulocity-iot.html#/
3 https://opensourceprojects.eu/p/vfos/iotoolkit/wiki/IO%20Toolkit/
4 https://opcfoundation.org/about/opc-technologies/opc-ua/
5 https://www.omaspecworks.org/what-is-oma-specworks/iot/lightweight-m2m-lwm2m/
6 https://www.omaspecworks.org/develop-with-oma-specworks/ipso-smart-objects/</p>
      <p>
        This component focuses on security and privacy aspects of ZDMP. The risks mitigation is assured
through a variety of measures [
        <xref ref-type="bibr" rid="ref3">3</xref>
        ], such as minimization of attack surface by isolation and zoning of
communications, implementation of robust encryption, enforcement of access control policies,
authentication of entities and introduction of security monitoring entities. In other words, the
particular component is intended to cover relevant issues around security and privacy domain. The
core elements of this component are: Secure Installation, Secure Communication and Secure
Authentication/Authorization [
        <xref ref-type="bibr" rid="ref4">4</xref>
        ].
      </p>
      <p>Secure Installation facilitates the secure installation of zApps from the marketplace to the
platform at the run-time. This component also manages trust and legitimacy of any installed zApp and
creates users, roles and policies required by the zApp.</p>
      <p>Secure Communication provides a public key infrastructure for other ZDMP components. This
element enables secure communication across the platform. Moreover, it includes certification and
registration authorities providing the core functionality of the sub-component – issuing, revoking
certificates and matching identification with certificates.</p>
      <p>Secure Authentication/Authorization is responsible for authorization and authentication within
the platform. This sub-component checks the accordance of the requests to the specific access policies
and in the case of the positive assessment issues the access token. It also makes use of the best
practices, while implementing the OpenID7 and the OAuth2.08 protocols to protect resources from
unauthorized access.</p>
      <p>These three security sub-components are linked closely with the key functionality of the platform,
namely with the Service and Message Bus, Portal, Application Runtime and Marketplace. This
protects from some critical vulnerabilities and allows security to be applied to the whole platform.
3.3.</p>
    </sec>
    <sec id="sec-6">
      <title>Data Harmonization and Interoperability</title>
      <p>
        The Data Harmonisation and Interoperability component is based upon and is further development
of the Semantic Management Component [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ]. Semantic Management Component is composed of two
modules the Harmonisation and the Storage. Harmonisation module is responsible for communication
with the Storage component, data cleaning and cross-format adjusting of the input files and detection
of the data patterns in the row data. The Storage module allows storing the ontologies and integrating
the newly imported ontologies to already existing Knowledge Base. The task of harmonization and
interoperability provision is split into the run- and design-time blocks:
      </p>
      <p>The Data Harmonization Designer, data transformation is one of the tasks of this component,
adjusting the data formats to the needs of requesting entity. Another task is the semantic
homogenization supporting the data mapping through ZDMP Knowledge Base. Further task of the
component implies the mapping of the users’ or applications’ data and metadata to the platform
reference model. Moreover, the component provides the necessary mechanisms to the user to create
Manufacturing Maps containing the rules for transforming the specific types of syntax.</p>
      <p>The Data Harmonization Run-time assures the proper deployment, and encapsulation of the
Data Harmonization Designer. Afterwards, the functionality of the Data Harmonization Designer is
available as a service at the Marketplace. The procedure follows the ETL workflow, whereas
extracting, transforming and loading the data. This is based, in particular, on the Talend Open Studio
for Data Integration.
3.4.</p>
    </sec>
    <sec id="sec-7">
      <title>Orchestration, Monitoring, and Alerting</title>
      <p>
        The component that is responsible for the orchestration is divided into two parts, namely the one
which is executed at the run-time – Orchestration Run-time, and the other at the design time –
Orchestration Designer. The approach is similar to the one used in vf-OS project for harmonization
component [
        <xref ref-type="bibr" rid="ref6">6</xref>
        ], where data mapping is accomplished at the design-time and data transformation at the
run-time.
7 https://openid.net/
8 https://oauth.net/2/
      </p>
      <p>
        The Orchestration Designer assists processes management using the business process model
notation (BPMN9). The BPMN models allow visual representation of a sequence of events for the
business modelling. Another important task of this sub-component is to map different file formats. In
other words, if the file format is not suitable to the consuming component’s acceptable format, it is
changed to fit it. Furthermore, the sub-component contributes to the improvement of suggestion
quality of the user’s requests, whereas effective mappings are added to the knowledge base. It also
supports the ontology storage, keeping the relevant knowledge in the graph form [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ], which is useful
for analysis of relations among the concepts.
      </p>
      <p>The Orchestration Run-time interprets and implements process flows delivered from the
Orchestration Designer. To do this, it connects to the required services and executes them according
to the logic described in the BPMN diagram. For this purpose the sub-component possesses the
BPMN parser and BPMN map API.</p>
      <p>The Monitoring and Alerting This component is used to collect the data from the end-devices,
which later are represented in the graphical form in a web-based user interface. It might be also used
for historic data and logs collection. The second function is to generate alerts, based on data received
and inform all involved counter-parts. The alert can be sent in various ways, such as, email, HTTP
endpoints or SMS.
3.5.</p>
    </sec>
    <sec id="sec-8">
      <title>Distributed and Autonomous Computing</title>
      <p>Distributed Computing provides mechanisms for applying the distributed computing
technologies, such as: fog, edge and mist environments. One of the key issues being in focus of this
component is the ability to efficiently divide the task onto smaller ones and distribution among
available nodes for further execution. This includes many aspects, such as managing the distribution,
mapping the locations of the computational nodes, load balancing and API to communicate with other
components.</p>
      <p>
        The Autonomous Computing component covers the issues related to the processes
automatisation, as well as communication automatisation among other components. The key elements
of it are:
 User Interface for setting the policies – on this stage the rules to activate the triggers are set.
Crucial is to specify “how each user may change the policy” [
        <xref ref-type="bibr" rid="ref7">7</xref>
        ] in order to avoid and resolve
conflicts, and predict the consequences of applying the certain policy.
 Triggers for autonomous processing – following the reactive paradigm, the triggers are
activated depending on the data obtained.
3.6.
      </p>
    </sec>
    <sec id="sec-9">
      <title>AI and Analytics</title>
      <p>
        The AI-Analytics Designer component enables creation of machine learning models from the
historical data, which later are run by the AI-Analytics Run-time [
        <xref ref-type="bibr" rid="ref4">4</xref>
        ]. The main goal is to detect and
predict defects in the production process. For this purpose supervised as well as unsupervised learning
algorithms are applied.
      </p>
      <p>The AI-Analytics Run-time is used for deploying the models on the platform and run them in
synchronous or asynchronous manner. Visualisation is also in the scope of this component as a user
interface with various dashboards. It detects the anomalous behaviours through analysis of
measurements and identification of deviations from the learning models delivered from AI-Analytics
Designer.</p>
    </sec>
    <sec id="sec-10">
      <title>4. Possible Application Example</title>
      <p>
        The components belonging to the WP5 are presented with accordance to 4-tier model and in terms
of functionality are divided into those that executed at the design- and the run-time. The basis for
9 http://www.bpmn.org/
some of the components is being developed within some passed projects. A good example is the Data
Harmonisation Designer, which was designed and developed within the vf-OS project [
        <xref ref-type="bibr" rid="ref5">5</xref>
        ]. However,
the basis will be enriched with more services to be consumed by the other components, such as
AIAnalytics (Fig. 2). In Fig. 2 the small scenario combining the AI-Designer, Semantic Management
Component which is the vf-OS analogue of Harmonisation Designer and Data Acquisition
Component is presented. All presented components are separated according to the execution at the
run- or the design-time. Data Acquisition component is responsible for the data flows management
from devices to other components and in particular to the Harmonisation Designer. The user that in
the same time can have the designer role can change the configuration through appropriate interface
provided by Acquisition component. The AI-Designer offers to the Harmonisation Designer a set of
algorithms for data enrichment or feature extraction, which can be accessed on demand. And finally
the Data Harmonisation Designer is represented in detail, including harmonisation part itself and the
ontology storage. Among the core deliverables of it are:
 Supplying the user with helpful suggestions when performing mappings between distinct
concept knowledge bases;
 Storage of ontologies with support of various data formats;
 Transformation of generic requests into semantic queries;
 Interface to manage the access to component enabling the reception of different file formats
and thus contributing to interoperability;
 Import and integration of third-parties ontologies.
      </p>
    </sec>
    <sec id="sec-11">
      <title>5. Conclusion</title>
      <p>The current research paper aims at giving the overview of the WP5 components being developed
within the framework of ZDMP project. This work package for Core Services and Middleware is
represented through key functional blocks: (i) Data Acquisition, (ii) Industrial Network Support, (iii)
Data Harmonization, (iv) Orchestration, Monitoring and Alerting, (v) Distributed and Autonomous
computing, and (vi) AI Analytics. The ZDMP platform is based on 4-Tier model and thus all the
components are represented in regard to it. Moreover, the functionality of most of the components is
divided onto two parts, the one which is executed at the design-time and the other being executed at
the run-time. The components within the Platform tier belong to the run-time, whereas components
within the Developer tier to the design-tier category. This allows considering separately the design of
the models and the execution of the models developed during the design phase. Important to mention,
that components are designed in the modular way in order to ensure the flexibility to add or remove
the needed functionality. Further work includes the finalisation and adjustment of the components
being developed within the WP5 with the other components of ZDM platform followed by the
application in the real-case testing scenario.</p>
    </sec>
    <sec id="sec-12">
      <title>6. Acknowledgement</title>
      <p>The research leading to these results received funding from the European Union H2020 Program
under grant agreement No. 825631 “Zero Defect Manufacturing Platform (ZDMP)”.</p>
      <p>We thank Perez Salvador (IKERLAN, Spain), Mircea Vasile (SIVECO, Romania), Laura Caroline
Ribeiro de Melo (Ascora GMBH, Germany) and Christian Melchiorre (Softeco Sismat S.r.L, Italy)
for the valuable assistance in designing of the framework’s architecture.</p>
    </sec>
    <sec id="sec-13">
      <title>7. References</title>
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