IIot Platform for Agile Manufacturing in Plastic and Rubber Domain

Ilaria Bosi, Jure Rosso, Enrico Ferrera and Claudio Pastrone

LINKS Foundation, Leading Innovation & Knowledge for Society, Turin, Italy

Keywords: Industry 4.0, Industrial Internet of Things Gateway, Federation of Platforms, Interoperability, Cross-Domain

Platforms, OPC UA, Euromap, Kura Framework, Zero Defect Manufacturing, Edge Computing, Smart

Factories.

Abstract: In recent years, the concept of integration as a key to digital transformation has also been associated with the

interconnection of hardware, software, data and information in Industry 4.0. One of the greatest challenges of

Industry 4.0 is to be able to ingest massive amounts of data coming out from machines: the eFactory platform

enable users to exploit innovative functionalities, experiment with disruptive approaches and develop custom

solutions to maximise connectivity, interoperability and efficiency across the supply chains. To achieve this

goal, it is necessary to work on standard communication protocols and architectures. By leveraging Industrial

Internet of Things (IIoT) technologies, this feasibility study focuses on the design and implementation of an

open source platform for plastic and rubber industry, that abstract data and functionalities provided by on-

board machinery sensors, exposing relevant services outside the machines to external cloud-based

applications. The federation of this new services related to the industrial scenario is supported by an

interoperable 'Data Spine' that simplifies cross-platform communication and securely capture information on

the multi-tier supply chain. The intent is to make the production process more automated, interconnected and

moreover to support a Zero-Defect strategy thanks to digital technologies involved in the project.

1 INTRODUCTION

Industry 4.0 refers to the Fourth Industrial

Revolution ̶ the recent trend of automation and data

exchange in manufacturing technologies. The key

fundamental principles of Industry 4.0 include data

integration, flexible adaptation, cloud/intranet,

intelligent self-organizing, manufacturing process,

optimization, interoperability, secure

communication, and service orientation (Ji, et al.,

2016) (Vogel-Heuser & Hess, 2016). These

innovative technologies are used to create a “smart

factory” where machines, systems and humans

communicate with each other in order to coordinate,

monitor progress and connect sensors to provide data,

along the assembly line (Peralta, et al., 2017). The

interconnectivity in this scenario is a challenge in

terms of interoperability: accessibility,

multilingualism, security, privacy, subsidiarity, use

of open standards, open source software, and

multilateral solutions, are definitely key concepts

(Xu, Xu, & Li, 2018) (Branger & Pang, 2015). In this

way manufacturers need to integrate connected,

discrete operational systems and smart manufacturing

assets of a factory and throughout the entire supply

chain, providing a complete vision of Industry 4.0

(Lu, 2017).

To simplify system development and resource

management, the ability to manage and maintain

complex distributed systems, common industrial

approaches based on the concept of Industrial Internet

of Things (IIoT) have been adopted, also to

implementing Industry 4.0 scenarios, such as:

Interconnected Factory (complete production

planning and machine management, production

optimization), Cyber Physical Systems (CPS) (to

know in real time every detail of the production

process), Decentralization (ability of CPSs to make

decisions on their own), Internet of Things (helps

people and equipment to communicate each other),

Virtualization (a virtual model of the factory to

simulate the production process), Real-time (collect

and analyse data in real time to make timely

decisions), Technical assistant and support systems

(intelligent process and production analysis tools to

control the process and react automatically in case of

problems) (Lom, Pribyl, & Svitek, 2016) (Schlick,

Stephan, Loskyll, & Lappe, 2014).

436

Bosi, I., Rosso, J., Ferrera, E. and Pastrone, C.

IIot Platform for Agile Manufacturing in Plastic and Rubber Domain.

DOI: 10.5220/0009573304360444

In Proceedings of the 5th International Conference on Internet of Things, Big Data and Security (IoTBDS 2020), pages 436-444

ISBN: 978-989-758-426-8

The scope of the feasibility study is to lay down

guidelines regarding the crucial features for the

management and the implementation of a IIoT

platform and the connection of a new base open

platform related to the Industry 4.0 scenario

developed within the Regional project

Pastic&Rubber4.0 (OpenPlast, 2018), to show the

concrete possibility offered by the European project

eFactory (eFactory, 2018) to promote interoperability

between cross-domain platforms.

The study begins with an overview of the two

projects mentioned, highlighting the aspects of

interconnection and the challenges to be faced in

order to implement in the future an ad hoc adapter to

promote such binding. To endorse these aspects is

proposed the general architecture for Industry 4.0 and

quick outline of the different industrial

communication standards and protocols supported by

the machinery connected to the platform, followed by

the presentation of the IoT gateway platform

(OpenLink) implemented in Plastic&Rubber 4.0

project. Afterwards is described the core of this work

related to the implementation through the Eclipse

Kura gateway framework for the collection and

processing of data from the various factory machines.

Finally, the paper proposes the discussion and the

conclusions of the first results obtained in terms of

increasing the system flexibility and the

performances of the cross-domain interoperability.

2 eFactory PROJECT

The eFactory project realises a federated smart

factory ecosystem by primarily interlinking 4 smart

factory platforms from the FoF-11-2016 cluster

[COMPOSITION, DIGICOR, NIMBLE, vf-OS],

with their integrated toolsets and services through an

open and interoperable Data Spine. The eFactory

platform allows users to take advantage of the wealth

of Industry4.0, Internet of Things (IoT), Artificial

Intelligence, Big Data Analytics and Digital

Manufacturing solutions displayed in the project

ecosystem. The eFactory federation is offered to the

manufacturing and logistic companies as an open

platform to utilise the offered functionality,

experiment with innovation approaches and develop

custom solutions based on specific needs.

As shows in Figure 1, the core of eFactory

ecosystem is the 'Data Spine', an interoperability

mechanism that provide support for secure and

interoperable data exchange (between internal and

external platforms), service calls and API integrations

across multiple systems and platforms. To help users

create their own software applications and services,

eFactory is equipped with an open Software

Development Kit (SDK) and a development

environment (Studio). The SDK uses Data Spine as

an integration layer and allows users to compose

applications or integrate services based on their

specific needs. The eFactory Marketplace

Framework uses the Data Spine to interlink the

marketplaces of multiple platforms in the eFactory

ecosystem. The Data Spine, that streamlines cross-

platform communication and securely captures multi-

tier supply chain intelligence, which is then

propagated within the platform (through interfaces

and a dashboard), is proposed as a bridge for protocol

heterogeneity and provide uniform access to services

between base platforms and apps/tools.

Figure 1: eFactory concept architecture.

Using these implementation features of the

eFactory platform, it is therefore possible to connect

throw the Data Spine new platforms built for different

domains, in the specific case treated in this paper, a

complete, open and security trusted base platform

related to rubber and plastic industrial domain is

taken as a feasibility study reference.

The use of common (de-facto) standards for

communication and data exchange at the shop-floor,

systems and business/enterprise levels is one of the

best practices of distributed systems development: in

this way, project partners would develop standardised

solutions to enable the interoperation of

heterogeneous and distributed solutions in the

eFactory federation. Standardisation is of special

importance in supporting the digital transformation of

industry. In this way, the eFactory project as also the

focus to inviting manufacturing companies, digital

solution providers, software developers and

researchers to carry out experiments related to the

development, prototyping, integration and validation

of innovative solutions using eFactory platform.

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437

3 P&R 4.0 PROJECT

This paper is also based on the use cases carried out

during the Regional project Pastic&Rubber4.0

(which for the market is renamed OPEN PLAST) that

focuses on implementing a real scenario of

technological innovation through defining,

developing and experimenting in real plastic and

rubber factory use cases new models and

organizational tools borrowed from Information and

Communications Technology (ICT) world.

The regional project focuses on three fundamental

objectives: the increase in performance at the process

level (in terms of processing times and overall

quality), the flexibility of the processing systems (in

terms of working conditions and autonomy) and the

rapid diffusion of the information for the involvement

of users in the process.

The services offered, that can be deployed as a

service in the Data Spine of the eFactory project, may

include integration with company Enterprise

Resource Planning (ERP) systems, shop monitoring,

scheduling and optimization of production planning,

energy management and optimization, remote and

predictive maintenance, control of feeding and

cooling systems, the integration of automated

warehouses up to augmented reality systems (e.g. in

the maintenance field). Benefiting from the above,

Industry 4.0 Factories ̶ or simply “Smart Factories” ̶

will be able to perform prognoses such as health

management of machine tools, enhancing

productivity and increasing the quality of processes

and services. The advanced elements of this project

are related to the possibility of implementing an open

source platform for plastic and rubber factories with

a modular IoT architecture for the management of

applications and an advanced data repository for shop

floor monitoring. In order to implement the hardware

and software components of this platform for the

retrofit of the existing machine, the researches exploit

new standard communication protocols (such as OPC

UA, Euromap 77/83, etc) and a multi-protocol

platform open to market standards.

This paper also focuses on the management and

software implementation of the various industrial

communication protocols used to describe a single

Data Model that allows correct storage of data from

the different factory machines on the Data Spine (or

generic Cloud platform). The common Data Model

will describe all the events, variables and resources

that could indicate quality issues, exploiting it to

reduce defects, the respective causes and the

strategies to avoid the propagation of the errors along

the shop floor.

In the implemented IoT architecture, in order to

provide the capability to offload computationally

expensive data processing from the Cloud to the Edge

(minimizing additional latency and operational

expenses) (Peralta, et al., 2017), a core role is

assigned to the Low Power Gateway (LPG). Edge

computing is mainly considered an extension of cloud

computing to the edge of the network, which enables

new applications and services related to a huge

number of heterogeneous IoT devices (Vaquero &

Rodero-Merino, 2014).

 Edge computing brings

significant benefits in terms of: low latency,

geographical and large-scale distribution, mobility

and location awareness, flexibility, heterogeneity and

scalability (Bonomi, Milito, Zhu, & Addepalli, 2012)

(Barcelo, et al., 2016). As an edge node, the Low

Power Gateway will have the capability of data pre-

processing (acquiring data directly from the machines

or trough adapters), conversion between protocols,

communication through IoT protocols and send data

to the Data Spine (as the Open Platform), using the

imposed requirements.



With the functionalities of filtering and pre-

processing on board of LPG, proposed as new project

implementations, it is also possible to monitor the

status of the manufacturing process in real time. This

provides the possibility to define new strategies based

on real data acquisition able to detect and prevent the

generation of errors and defects along the shop floor.

In case an error occurs, instead of wasting the part,

corrective actions are suggested based on correlations

and decision support mechanism. In this way, to

develop a Zero-Defect strategy to cope with

increasing competition and sustainability related

issues, plants should be designed and managed using

best practices from emerging key enabling ICT

technologies (May & Kiritsis, 2019).

4 INDUSTRY 4.0 GENERAL

ARCHITECTURE

Several architectures and conceptual platforms have

been proposed to develop Industry 4.0 applications.

As proposed by numerous studies, there are three

major types of integration: horizontal integration,

vertical integration and end-to-end integration (Qin,

Liu, & Grosvenor, 2016) (Oliveira & Alvares, 2016);

all this integration formats require changes in

enterprise architecture, ICT integration and processes

(GTAI, 2014). Liao et al. (Liao, Deschamps, Loures,

& Ramos, 2017) have specified these three types of

integrations in Industry 4.0 as (1) Horizontal

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Integration: integration of the different Information

Technology (IT) systems used in the various stages of

the manufacturing and business planning processes

within and between companies (e.g. inbound

logistics, production, outbound logistics, marketing,

value networks) (Kusiak, 2017); (2) Vertical

Integration: integration of the various IT systems at

the different hierarchical levels to deliver an end-to-

end solution (e.g. actuator and sensor level,

manufacturing and execution level, production

management and corporate planning levels); and (3)

End-to-End Digital Integration: the digital and real

worlds are integrated across a product’s entire value

chain and across different companies, whereas

incorporating customer requirements. Industry 4.0 is

expected to achieve all three major integrations as

described above, plus hardware integration, software

integration, and information integration. Efficient

real-time integration of data in Industry 4.0

production processes needs to be ensured, as the

support of automation in Industry 4.0 requires such

integration (Xu, Xu, & Li, 2018).

Figure 2: RAMI general concept architecture.

The German Electrical and Electronic

Manufacturers' Association and its partners have

developed the Reference Architecture Model

Industrie 4.0 (RAMI 4.0) (Rojko, 2017) which is now

supported by Platform Industrie 4.0 and is considered

a key standard for Industry 4.0. RAMI 4.0 groups the

main components of Industry 4.0 into a single three-

dimensional model that describes the space in which

Industry 4.0 manifests itself (see Figure 2). The three

axes of RAMI 4.0 represent the hierarchical levels of

a networked production plant, the life cycle of plants

and products and the IT representation of an Industry

4.0 component.

This 3D architecture and the concepts related to

RAMI 4.0, become the starting point for the

implementation of the IIoT platforms related to the

eFactory and Plastic & Rubber 4.0 projects, to

demonstrate how this platforms can be approached to

the features explained into RAMI 4.0 in order to have

an architectural model that can be replicated in

different production contexts, which is also one of the

objectives of the project.

5 STANDARD AND PROTOCOLS

INDUSTRY 4.0

In the last few years, another hurdle for both IoT and

Industry 4.0 has been the lack of standards.

Standardisation in IoT mainly aims at improving the

interoperability of different applications/systems (Da

Xu, He, & Li, 2014). Standardisation efforts are

needed to ensure devices and applications from

different countries to be able to exchange

information. Various standards such as

communication/identification/security standards,

used in IoT might be the major drivers for the spread

of IoT technologies (Miorandi, Sicari, De Pellegrini,

& Chlamtac, 2012).

The companies that join the OPC Foundation

(OLE for Process Control) (OPC, 2020) have

addressed the problem and have created a standard

protocol for the operation of the machines and

software systems that can now communicate with

each other using information models that enable a

large volume of data to be represented in a structured

manner and transferred in a standardized form.

With the introduction of service-oriented

architectures in manufacturing systems, the OPC

Foundation developed the OPC Unified Architecture

(OPC UA): a set of specifications to address

challenges in security and data modelling and at the

same time provide a feature-rich technology open-

platform architecture that was future-proof, scalable

and extensible (OPCFoundation, 2018)

The main reasons related to the adoption and the

greater use of the OPC-UA standard in the plastic and

rubber industrial sector, are the following: allows

Smart Manufacturing, contributes to reducing the

complexity of communication between devices and

machinery (thus improving the overall efficiency of

the systems), it is compatible with legacy systems,

new machinery and product lines, it is multi-platform,

it is not a proprietary format, it is able to receive and

interpret multiple data points from different sources.

Furthermore, Euromap, the organization that joins

plastic and rubber processing machinery

manufacturers' associations at European level, has

been involved for years in the development of an

interface for Industry 4.0 (EUROMAP, 2020). The

recent standard that describes the interface between

injection moulding machines and Manufacturing

Execution System (MES) for data exchange is called

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Euromap 77: this standard is based on OPC UA and

replaces Euromap 63, which is an obsolete text file-

based data transfer standard, but due to the longevity

of machine tools, Euromap 63 will still be of interest

for the next few years. The longevity of machine tools

is a fundamental challenge for the digitalization of

factories because new standards and old standards

have to be considered and those data has to be

harmonized (Behnke, Müller, Bök, & Bonnet, 2018).

With Euromap 77, machines from different

manufacturers can be easily networked for

monitoring the quality of the process and acquisition

of production data. In the Plastic&Rubber 4.0 project,

the focus is also related to the use of the new

standards (such as Euromap 77) to create a Data

Model concerning to the factory machine that is as

homogeneous as possible, however remembering that

inside the factories for plastic moulding and rubber

machinery may be present with more obsolete

standards and protocols (e.g. Modbus, S7,

Euromap63, Euromap83 etc).

6 FRAMEWORK

ARCHITECTURE FOR

OPENLINK IoT GATEWAY

The IoT eco-system will involve machines, factory

network and surrounding devices related to IoT, with

an attention to diffuse information rapidly on the

involvement of users in the industrial process,

increase the performance at the job level and the

system flexibility.

Figure 3: Plastic & Rubber 4.0 Open Platform.

Regarding the designed IoT architecture (Open

Plast Platform) as described in Figure 3, can be seen

as a set of four macro blocks:

• Machinery: representing different types of

machines (presses, chillers, drying systems, etc.) that

will be connected and integrated to the OpenPlatform

using the IoT Subsystem.

• OpenLink (IoT Subsystem): represents IoT devices

(Gateway and Adapter) that allow the machines to

communicate with the Open Platform.

• OpenPlatform: includes within it a series of

databases that will be used differently by the

applications and by the IoT Subsystem (OpenLink).

Moreover, some mechanisms will be implemented for

managing access and issuing certificates.

• Applications: this macro-block represents all the

applications that will be developed in Plastic &

Rubber 4.0 (Manufacturing Execution System

(MES), Planner and Optimizer, Energy Management,

Maintenance, Management and Real Time

Intelligence Console, RTLS & Video Tracking and

Factory Data Warehouse). While the Machinery and

the Open Link (IoT Subsystem) will be physically

located within the factories, the Open Platform and

applications can reside both within individual

factories and in the Data Spine.

In the OpenLink block, the smart IoT gateway

framework is a software solution that bridges the

semantic gaps between the raw machine sensor data

and the information context that is interested by high-

level applications. The Low Power Gateway (LPG)

implements an IoT platform that acts as an

aggregation point coordinating the connectivity

between the devices and the machines, and with the

different subsystems, as well as with networks and

external devices. Furthermore, it has the functionality

of IoT middleware, interfacing heterogeneous

physical devices (such as sensors and actuators) and

machinery, exposing data and features to the Open

Platform database and the Open Data Cloud.

For the design and the implementation of the Low

Power Gateway, some fundamental requirements

related to Industry 4.0, to the concept of

interoperability and cross-federation, have been taken

into account (Figure 4):

Figure 4: Development view Low Power Gateway.

• Interoperability: the LPG must be able to interact

(exchange of data and services transparently) with

heterogeneous devices, technologies, machinery and

applications, without the need for further adaptations

by the developer of application or service.

Interoperability can be understood from a

communication, syntactic or semantic perspective.

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- Communication Interoperability: allows the

platform to transparently transfer information

between sensor and actuator networks, devices,

machinery and subsystems that use different

transport protocols.

- Syntactic Interoperability: must allow the

harmonization of formatting and coding structures

of any information and service.

- Semantic Interoperability: refers to the meaning

of information or services and must allow the

correct interpretation of information exchanged

between sets of devices and services connected to

the platform.

• Service-based: the LPG will offer maximum

flexibility if new and advanced features are added

(such as support for a new machine). These and other

services can be designed, implemented and integrated

into an application container or runtime environment

that is a service-based framework (such as Java-

OSGi, Python, ROS, Node.js) that offers a flexible,

modular and simple application development

environment.

• Context-awareness: for building adaptive

applications and services, as well as for reading

detected values. The IoT subsystem must be aware of

the context through a model to be used for the

development of effective intelligent services that

operate in a specific way based on the context. To

enable context awareness, layered architecture has

been used to build frameworks for devices, raw data

storage and processing, context management, and

applications.

• Data Management: the LPG can provide

applications with data management services: these

include data acquisition and processing, data fusion at

the "peripheral" level and a local data storage capacity

to manage network latency and reliability.

• Event management, Analytics & UI: the LPG is

able to handle events with near real-time constraints.

The platform can have analysis capabilities and

expose processed and improved data to the Open Data

Cloud.

• Remote Management: the possibility of

instantiating, configuring, updating, monitoring,

starting and closing remotely all the different

software components (i.e. services and applications)

running on the platform.

• Security and Privacy: security must be

implemented both at the device and application level.

Functions such as authentication, encryption and

authorization must be part of the software

architecture. Furthermore, each block of LPG that

uses personal information must preserve the privacy

of the user who owns it.

• Open Standards: communication within and

outside the LPG must be based on documented open

standards to ensure interoperability.

• APIs: Providing Application Program Interfaces

(APIs) for application developers is an important

feature. The APIs allow easy integration with existing

applications and integration with other IoT solutions

and cloud services. The programming paradigm (e.g.

publish/subscribe, REST, etc.) concerns the model for

the development or programming of apps or services.

7 GATEWAY IMPLEMENTATION

As highlighted in the previous section on the design

of the Open Platform, the various machinery (directly

or through adapters) send the data to the OpenLink

which, after some procedures of filtering and

processing, exposes the processed data, through a

MQTT Broker, directly to the applications and

services on the Data Spine. The first tests in lab were

conducted using the Cloud available on Eclipse:

Kapua™ is a modular, integrated, interoperable IoT

cloud platform to manage and integrate devices and

their data and provide a solid foundation for IoT

services for any IoT application.

To implement the gateway/client framework, it is

chosen to use an Eclipse tool that basically acts as a

proxy between the field devices and the data centres.

Eclipse Kura™ is an extensible open source IoT Edge

Framework based on Java/OSGi (Open Service

Gateway initiative), that provides a platform for

building IoT gateways. Kura offers API access to the

hardware interfaces of IoT Gateways (e.g. serial

ports, GPS, watchdog, GPIOs, I2C, etc.). It features

ready-to-use field protocols (including Modbus, OPC

UA, S7), an application container, and a web-based

visual data flow programming to acquire data from

the field, process it at the edge, and publish it to

leading IoT Cloud platforms through MQTT

connectivity (Kura, 2020).

Kura (in particular, at the moment in which this

paper is written, it is suggested to use version 4.0) has

a user accessible web console that provides several

important features available out-of-the-box: the

ability to configure the gateway, connect to a remote

cloud and even a visual data flow programming tool

to dictate the data collection and processing pipelines

of devices connected to it (Lee & Nair, 2016).

The application implemented in Kura is provided

as an OSGi module and performed inside the

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container together with the other Kura components.

Applications can be remotely implemented as OSGi

packages and their configuration can be imported (or

exported) via a snapshot service.

Using the Kura tutorial, the first steps were taken

to configure Kura 4.0 on a Raspberry (Pi4), which

will be used as an IoT gateway and which provides

client interface with the factory machinery. Eclipse

Kura introduces a model based on the concepts of

Drivers and Assets to simplify the communication

with the field devices attached to a gateway. The

Driver encapsulates the communication protocol and

its configuration parameters, while the Asset, which

is generic across Drivers, models the information data

channels towards the device. When an Asset is

created, a “virtual” device is automatically available

for on-demand read and writes via Java APIs or via

Cloud though remote messages. In this Client/Server

model, the different standards and protocols managed

by the machines (e.g. Modbus, S7, OPC UA,

Euromap 63, Euromap 77, etc.) defines sets of

services that the servers can provide, and each server

indicates its own group of services that it makes

available. Information is exchanged using DataTypes

defined by the standards or by producers, while

servers use Data Models that clients can identify

dynamically by requesting metadata containing the

description of the format used.

For example, OPC UA can be mapped on various

protocols and supports several types of data encoding

allowing users to choose in order to optimize

applications in terms of portability and efficiency. It

should also be noted that the available Channels can

be set to read/write the values from the machines: for

this reason it is possible (retroactively, thanks to the

pre-processing on the gateway or possibly to new

configurations identified on the Cloud) set or block

some machine data, avoiding sudden breakages.

In Plastic&Rubber 4.0 project, a set of variables

from the rubber moulding and plastic extrusion

machinery has been defined, some of which are

related to the implementation set provided by the

Euromap consortium, but others are customized

directly by the owners of the factory machinery.

Figure 5: Kura GUI Channels.

Figure 5, shows the implementation of the

variables received from the various machines (the

values in Channels/Assets are updated in real-time),

via Kura's Graphic User Interface (GUI).

Since at present, an implementation bundle

relating to the Euromap 77 specifications does not

exist on the Eclipse Marketplace (from Eclipse Kura

Marketplace is possible to download additional Wires

components that can be installed into personal Kura

runtime with a simple drag-and-drop approach), a

comparison was made between the pre-existing Kura

package for the OPC-UA driver and the implemented

package which fulfils the requirements of the

Euromap protocol. Using this approach, during the

implementation of the Low Power Gateway, the

structure of the Kura bundle relating to OPC UA has

been partially extended to support the features related

to machines compatible with Euromap 77, especially

regarding the acquisition of customized variables. To

improve this, new classes have been implemented,

following the development line proposed by the OSGi

framework with the characteristics and DataType

referring to Euromap 77.

With the aim of having modular and visual data

flow tool, the Kura Wire Ghaph (Figure 6) define data

collection and processing pipelines at the edge by

simply selecting components from a palette and

wiring them together. With this tool users can:

configure an Asset, periodically acquire data from its

Channels, store them in the gateway, filter or

aggregate them using powerful SQL queries, and

send the results to the Cloud.

Figure 6: Kura Wires GUI.

Regarding the task of acquisition and processing

of the raw data from the various machines, it was

decided to carry out a decoding step of the machine

status (on/off) and a pre-filtering (evaluation of the

change in values acquired over the time) to ensure

that the data can be sent smoothly and according to

certain pre-established timings to the MQTT Broker

and subsequently to the Data Spine. Once the main

structure has been defined to collect all the raw data

from the sensors on the machine, the bundles

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developed on Kura can be used to proceed with the

publication of the data on an MQTT broker.

As mentioned during the description of the

eFactory architecture, the Data Spine interlinks the

APIs of the participating base platforms so that each

platform’s functionality is at least, visible and

accessible at the level of eFactory. This needs to offer

interoperation services at the level of protocols,

message formats, data structures, data models,

software services, and processes ranging from field

level control to business process performing.

Thanks to the possibility of pre-processing inside

the gateway (edge level computing), the security

model is simplified and improved. For example, it is

an advantage that despite many devices in the field,

the number of gateways that must be connected to the

Cloud is reduced. Obviously, the relationship

between device and gateway must be "trusted".

This solution is also required to reduce as much as

possible the defects, the respective causes and the

strategies to avoid the propagation along the line.

Decision Support Systems (DSS) are considered as a

robust technology able to provide an advantage to

several manufacturing companies, also to increase

Zero Defect Manufacturing strategy. The scope is to

facilitate real-time inspection, condition monitoring

and control - diagnosis at the shop-floor, utilizing

continuously mine multiple data streams and run the

suitable models to monitor operations and quality

performance, to classify products on the basis of

quality metrics, as well to predict occurrence of

defects and deviations from production and quality

requirements.

8 CONCLUSION & FUTURE

WORKS

This feasibility study has presented some strategies

for the implementation of an IIoT platform

interconnected to the deployment of the cross-domain

eFactory platform, contributing towards the creation

of an ecosystem of connected smart factories in

Europe: in this Industrial IoT scenario, connected

machinery, plants and production lines continuously

collect data "on the field", that can be pre-processed

and shared within wireless or wired corporate

networks to better synchronize processes.

The federated eFactory platform delivers

enhances value and reduces the barrier to innovation

by providing seamless access to services and

solutions that are currently dispersed. In parallel the

IIoT platform provides the necessary infrastructure,

tools and support for novel service creation and

validations by third parties. The expected result due

to the implemented IIoT platform is to translate into

a technological and competitive improvement of the

production system, an increase in the general

production capacity, as well as in an improvement in

the performance of the machines and processes,

reducing both economic and environmental costs and

also energy consumption of production plants.

A further result concerns the expansion of

communication protocols in the middleware based on

standard interfaces for interoperability (platform

independent), the safe and reliable exchange of data

between the machines and MES: the implementation

of advanced planning/optimization algorithms

applied to the production cycles of a 4.0

manufacturing plant, also provides the design and

development of a robust early stage data knowledge-

based inference engine to support Zero Defect

strategies in manufacturing environment.

The suggested implementation of the Low Power

Gateway promotes the adoption of common standards

for the development, the management and security of

systems, guaranteeing a certain level of transparency,

which is essential to reduce complexity and increase

the trust of both developers and end users. To further

expand the experimental part and for a better analysis

of the results, additional experiments and some

comparisons with the deployments of the other cross-

domain platforms on the eFactory Data Spine could

be planned as next steps.

Regarding the use of the Kura framework for the

implementation of the LPG software, as future work

it is possible to improve the proposed bundles in order

to extend and uniform the Data Model that foresees

the input values from different machines (with

different protocols) and then analyse themselves on

the Data Spine to offer various services. With this

architecture, the transfers required from IIoT devices

may be reduced, since the publishers would only need

to update in the Data Spine the predicted data in case

of mismatching: the progress of eFactory will be to

ensure that a whole federation of platforms can be

deployed in different cloud environments with

minimal reconfiguration.

In conclusion, this study highlights that cross-

domain platform level interoperation challenges are

about interoperability between various platform

layers, i.e. devices, network, middleware, application,

data and semantics. Next steps related to this

feasibility study in the plastic and rubber domain,

could provide validation scenario to demonstrate the

seamless access and utilisation of the 3rd party

system/application by eFactory services and users.

IIot Platform for Agile Manufacturing in Plastic and Rubber Domain

443

ACKNOWLEDGEMENTS

This work was supported by the projects “eFactory”

(H2020-DT-2018-1, grant agreement no. 825075)

and by “PLASTIC & RUBBER 4.0” (POR FESR

2014/2020).

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