In order for KYKLOS 4.0 to successfully realise its vision, a set of objectives are set, covering the project’s scientific, and technological aspects throughout its duration as well as the exploitation of the project’s results exploitation after its end.

Objective 1

Decentralised Interoperable Agent-Based B2B Marketplace – KYKLOS 4.0 Industrial Symbiosis Platform

To develop an interoperable agent-based B2B marketplace, where each party is represented by one or more agents, endowed with sufficient autonomy to set up exchanges and to enable new economic collaboration models. This approach is one of the innovations brought by KYKLOS 4.0 as it allows for a sensible change of production topologies, from centralised production in one factory only, to a completely decentralised, collaborative and dynamic manufacturing set-up.

Objective 2

KYKLOS 4.0 Virtual Production Line Orchestration Module & Interoperative Fog Architecture Framework to Accelerate Advanced Deployments in Smart Manufacturing

KYKLOS 4.0 aims to provide distributed virtual production line orchestrator giving the opportunity to split the work and increase efficiency. This will be achieved through running an orchestration module with limited capabilities inside a smart gateway with the aim to facilitate the deployment of new generation mass customization and product personalization services, as well as dynamically instantiate, reallocate and programme KYKLOS 4.0 cognitive functions according to KYKLOS 4.0 production line dynamic needs and requirements. A Cyber-physical system (CPS) combined with cognitive and fog computing paradigms will create a flexible overlay of IoT infrastructure (sensors, gateways, applications etc.) in the Shop Floor and enable improved deployment, operation and security for next generation asset management applications. KYKLOS 4.0 will thus embrace the “Computing on the Edge” paradigm and apply it to existing infrastructures.

Objective 3

Continuous Deep Learning Toolkit for Re-Adaptation and Adjustments of Operational Metrics, in Real Time

The KYKLOS 4.0 Ecosystem will include a core set of data management and analytics tools to fuse data coming from different disjoint levels of the factory lifecycle. These tools will detect complex patterns of manufacturing processes and provide useful information both for supporting short-term analysis (e.g., optimization, scheduling, monitoring of KPIs) and refinement of long-term manufacturing strategies (reconfiguration, new processes). Analytics, innovative simulation tools and machine learning techniques will provide unified, dynamic, indicators of all aspects of design and manufacturing stages will be available to decision makers at various levels e.g., production line designers, engineers, shop floor managers, plant operators, supply chain.

Objective 4

Tailored Circular Manufacturing and Mass Customisation Services with Use of Anonymisation When/ Where Needed

KYKLOS 4.0 aims to embed an innovative architecture to fulfil the following purposes: (a) Energy and raw material consumption efficiency models (b) Individualised consumer centric and customised production line with dynamic manufacturing, including assembly control by exploiting a predefined (intra-factory) configuration and (c) re-usability of parts (e.g., processes, components, parts) of the current shop floor model across different KYKLOS 4.0 services.

Objective 5

KYKLOS 4.0 Big Data Aggregation and Integrated DSS for Optimising Production Capacity, Featuring Automatic Rapid Reconfiguration of Industrial Processes

KYKLOS 4.0 will design and develop a scalable analytical platform that will support the collection, storage and processing of data from multiple industry (inside and / or outer) sources and industrial processes. It will be able to connect to the existing plant environment utilize data to optimize the production processes and provide recommendations for refurbishment and / or upgrading of the existing industrial equipment. The predictive modelling approach will provide a way to streamline operational industrial processes, such as to warn decision-makers about undesirable events that are likely to happen in the future, giving an opportunity to intervene. Furthermore, KYKLOS 4.0 envisions developing and implementing an integrated multi-level knowledge-based Decision Support System (DSS) that will be able to provide vital functions and guidance to the industry’s floor managers and reduce human decision-making load. This system will be able to “learn from experience” and understand the complex interplay of the various industrial components and equipment and provide efficient control scenarios and actions towards the safety and maintenance of the factory shop floors.

Objective 6

KYKLOS 4.0 Auditing Mechanisms

Design and implement a Log Oriented Architecture, based on blockchain technology, ensuring the trusted, secure and automated exchange of supply chain data streams among all authorized stakeholders, to connect manufacturing infrastructures with consumers and support interoperability. In this context, Blockchain will be used to provide an audit trail for the KYKLOS 4.0 data, enabling both service data traceability and secure access for stakeholders.

Objective 7

Product Data Management

To provide a set of products–services simulation models using ISO 10303 standards considering the product specifications, standards and regulatory compliance. Furthermore, the product design &materials, suppliers, manufacturing strategy, product usage and the product-service components are also considered. Finally, product recycling/reuse and the security requirements complete the data management processes.

Objective 8

KYKLOS 4.0 Product Life Cycle Monitoring / Customer Feedback Mining & Adaptation

To design an integrated product Life Cycle Monitoring toolkit to monitor product operational properties during their life cycle and to cover the demanding, special and individual customer needs in a transparent way. KYKLOS4.0 ecosystem will exploit semantic technologies for collecting, understanding, and analysing product properties and customer expectations through social networks and HMI technologies (e.g., visual, language-independent 3D model for customer’s product interaction, 3D simulation and comparison between models proposed by different designers, opinion and sentiment analysis using text mining, emotional recognition).Consumer behavioural patterns will be identified and communicated to the enterprise product management triggering appropriate organisational changes with a potential remedial effect on the corresponding production line.

Objective 9

KYKLOS 4.0 Production Line “Smartification” System

To enable flexible and responsive manufacturing by “smartifying” legacy hardware on KYKLOS 4.0 production line, leading to next-gen cognitive factory. KYKLOS 4.0 Cyber-Physical System (CPS) will achieve seamless connection and interaction of cognitive system components, virtualized resources, and data driven techniques, mathematical and physical models to enable diagnosis of issues within the KYKLOS 4.0 manufacturing line, leading to product conformance. KYKLOS 4.0 will allow for accurate maintenance decisions and production scheduling, in coordination with ERP / MES suites.

Objective 10

Additive Manufacturing Simulation Modules

To enable active in-process monitoring and exploitation of factory-ready AM processes for the fabrication of customer specific components, line with the principles of the circular economy.

Objective 11

KYKLOS 4.0 Automated Refurbishment Certification

To implement and provide an open-source toolkit that enables the assessment of devices and related services throughout a product life cycle, including in the equipment maintenance domain. KYKLOS 4.0 Automated Refurbishment certification will have a two-fold mission. First, it will provide an automated workflow to process maintenance reports and evaluate a device status, that indicates whether an equipment is safe to be used or not. Secondly, it will provide a detailed compliance and certification report.