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Flexible and Autonomous Manufacturing Systems for Custom-Designed Products

Periodic Reporting for period 2 - FASTEN (Flexible and Autonomous Manufacturing Systems for Custom-Designed Products)

Reporting period: 2018-11-01 to 2019-10-31

The 4th industrial revolution emerged in Germany in 2011 and is now a global innovation paradigm for the manufacturing industry worldwide. Starting from its initial conception of full adoption of Cyber Physical Production Systems, the Industry 4.0 paradigm has extended its scope to a broader set of technologies and to the most vital processes in the product and production systems lifecycle. The terms Industrial Internet of Things, Additive Manufacturing, Robotics, Mass Customisation, Product-Service Systems and Sustainable Manufacturing are key cornerstones and top priority challenges. However, in the context of an increasing demand on the diversity of products, products with shorter life cycles, and low volumes per order, the gap between the leading edge and lagging behind countries risks to become a serious problem, in the absence of a solid and inclusive innovation policy.

In line with the Industry 4.0 paradigm and the EU-Brazil collaboration program, the FASTEN project aims to be a key enabler of the full adoption of IoT technologies in digital manufacturing businesses, by demonstrating such technologies on both sides of the Atlantic. As such, FASTEN “mission” is to develop, demonstrate, validate, and disseminate an integrated and open modular framework (Figure 1) for efficiently producing highly customized products. This will be achieved by pairing digital integrated service/products to additive manufacturing processes, on top of tools for decentralizing decision-making and data interchange. Software technologies will be applied to build a fully connected additive manufacturing system by exploiting robotic, automation, simulation, as well as optimization and prescriptive analytics technologies. Demonstration of these technologies will be performed in two pilot cases: ThyssenKrupp Elevators in Brazil and Embraer Portugal in Europe (aeronautics).

The specific objectives of FASTEN comprise the following:
-To develop and demonstrate a flexible and scalable robotic system and its integration with mass customisation production lines,
-To design, assemble and demonstrate a Reference Architecture for Industrial IoT and Industrial Analytics made of open source components,
-To develop and demonstrate a real-time application for monitoring the performance of manufacturing and logistics systems, using simulation, optimization and predictive analytical tools,
Strategically, the project aims to foster the digital manufacturing sustainability and be an enabler of technology development between Brazil and Europe, thus contributing to the competitiveness of Brazilian and European industries.

Major results to be delivered are identified in Figure 2.
The project started in November 2017 and the initial focus was on the establishment of common working procedures, management practices and required supporting tools for managing the project. Shortly after, the consortium focused on the specification of the IIoT Reference Architecture and technology selection, on the robot and additive manufacturing systems integration architecture, and on the specification of both industrial use-cases.

A summary of the major technical achievement follows:
-Definition of the two use case experiments, focusing on the scenarios and requirements of EMBRAER (logistic warehouse and wing assembly line) and THYSSENKRUPP (maintenance services and additive manufacturing cells).
-Specification of the robotic system software architecture, addressing the vertical and horizontal integration, and comprising the first version of the following software components: Advanced Plant Model (digital twin for manufacturing plants, providing a unified data model of the physical manufacturing line), Production Manager (aiming to control and monitor the execution of production schedules), Task Manager (responsible for executing tasks on a robotic manipulator) and ROS-CodeSys Bridge (performing the horizontal integration between a robot and its own hardware equipment and external equipment).
-Design and first development of 2D and 3D object recognition algorithms by using samples of parts from the two use cases.
-Specification and first version of the skill-based robot programming framework.
-Design and development of a mobile manipulator aiming to perform tending operations.
-Analysis of available hardware solutions for robotic solutions (grippers, collaborative robots and sensors).
-Design of the Industrial IoT Reference Architecture, integrating data-in-motion and data-at-rest, and comprising two distinct “lanes”: FIWARE-based and Apache-based.
-Deployment and demonstration of two IIoT Platform instances in two different laboratories: I4.0 LAB at Polimi and at INESC Brazil lab, addressing energy monitoring and alarming.
-Development of an optimization and simulation tool set addressing supply-chain environments to help ensure its optimal design considering transport costs, localization of manufacturing additive cells and subcontracting.
-Initial design of an optimization and simulation tool set to support decision-making processes on the layout of logistic and manufacturing lines and on the assignment of production orders.
-First definition of eleven foreseeable key Exploitable Results.
-Development of project communication and dissemination material, including project logo, flyers, website, social media and shared information repository among others.
At the month 12 of the project, progress has been achieved on the major FASTEN pillars:
-Integration of Robot and Additive Manufacturing Systems – an open scalable architecture has been designed and partly implemented, comprising a 3D virtual representation of manufacturing lines and logistic areas, an execution manager able to assign and follow tasks defined in a production schedule by a Manufacturing Execution System and an orchestrator of navigation/logistic/assembly tasks by means of robotic manipulators. A first version of 2D and 3D object recognizer algorithms proved the feasibility of recognising the different parts to be manipulated in the two targeted use cases. This progress will be materialized in the automation of kit assembly activities in logistic areas and in the automation of machine tending operations involving robotic and 3D printer solutions.
-Open Source Industrial IoT Platform – a Reference Architecture was defined and two instances demonstrated in laboratory environment, based on available Open Source software coming from two different communities: FIWARE (mostly Europe based) and Apache (worldwide based). First deployment of the FASTEN IoT Platform proved the feasibility of connecting physical entities in the shop floor (like robotic systems and manufacturing equipment) with factory level applications for controlling and monitoring production (e.g. energy consumption and alarm generation) and by using two different sets of technology. Its impact will be mostly measured by the time and effort needed to connect existing manufacturing equipment with control and monitoring applications.
-Predictive Real Time Simulation and Optimization – the main goal of defining and applying simulation and optimization techniques to support decision-makers in strategic and operational planning has been achieved in the realm of a supply chain, comprised by additive manufacturing cells spread on different locations in Brazil and of different entities ordering the manufacturing of single parts in the provision of local maintenance services.
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