Technology

KYKLOS 4.0 aims at providing a system which automatically and autonomously creates the configurations, methodologies, production techniques, autonomous decision-making processes and actions at all different levels and stages of the manufacturing value chain.

Virtual Production Line Orchestrator

The “heart” of KYKLOS 4.0 ecosystem, as it will provide the digital interface within the KYKLOS 4.0 collaborative environment. The orchestrator and the connected smart gateways deployed in different factories; an automated virtual production line will be enabled.

The module will facilitate orchestration from user requirements, materials and service prices to selection of optimal production lines and controlling manufacturing equipment. The orchestrator, being a central node in the system, will work closely with other components too. Furthermore KYKLOS 4.0 will virtualize and orchestrate functions/ applications and services, increasing flexibility, scalability, adding automated, self-configuring capabilities, versatility and optimal management of production line IT resources. Key features of the Virtual Production Line Orchestrator are:

  • Smart and Dynamic
  • Continuous operation control, flexible and scalable maintenance
  • Robot systems goal and mission setting
  • Secure and encrypted design data
  • Implementable to small, conventional non-digitized shop floors
  • Add-on module to existing manufacturing infrastructure

PLM Module

KYKLOS 4.0 PLM module will be the hub to collaborate, interact and record the different configurations, methodologies, production techniques, decisions and actions that will be generated in the KYKLOS 4.0 process. As a reference point for all data related to the product It will provide traceability and configuration control and by using international standard formats for the data structure, information exchange and cooperation among manufacturers and designers are facilitated. Using ISO 10303 standards for data exchange, ISO TC 184/SC4 and its counterparts in CEN/CENELEC will promote Industrial Data standardization efforts and in turn innovations, quality of products, enhanced visibility, increased safety and environmental protection.

KYKLOS 4.0 Interface

To serve the data and services sharing within the KYKLOS 4.0 ecosystem, a dedicated KYKLOS 4.0 Interface (MI) encompasses the KYKLOS 4.0 Agent and the market wide KYKLOS 4.0 Exchange Language (MXL). A unique exchange protocol developed according to the needs of the ecosystem and of the partners. Each user can customise and control data/information flow and encourage collaboration on easy, comprehensive and transparent terms. The MI also acting as a universal translator of data within KYKLOS 4.0, homogenizing the system furthermore.

Integrated Decision Support System

The integrated DSS processes the events and semantically enriched data which are stored in the repository. Additionally, it is responsible for supporting decision making in circular and flexible manufacturing processes and operations (e.g. maintenance requirements and procedures, daily production details and flaws, etc.). The DSS provides to the Learning / Task Planner Toolkit and MR Services the necessary incident management actions and will be responsible for detecting important shop floor events. Enriched by a Visual Analytics Module, different state-related views of the supervised shop floor will be available to the relevant actors. Visual Analytics tools will lead to production line monitoring and assessment enhancement and to a new work frame. Integration of innovative collaborative tools to procedural changes like gamification of production are options available to the users of KYKLOS 4.0. The module will provide overall general-purpose architecture in order to model decisions, define dependencies among those decisions or artefacts and will provide an environment in which to implement the logic for the automatic generation of configuration files or documents.

KYKLOS 4.0 INDUSTRIAL COLLABORATION ENVIRONMENT – KYKLOS 4.0 Marketplace

The integrated DSS processes the events and semantically enriched data which are stored in the repository. Additionally, it is responsible for supporting decision making in circular and flexible manufacturing processes and operations (e.g. maintenance requirements and procedures, daily production details and flaws, etc.). The DSS provides to the Learning / Task Planner Toolkit and MR Services the necessary incident management actions and will be responsible for detecting important shop floor events. Enriched by a Visual Analytics Module, different state-related views of the supervised shop floor will be available to the relevant actors. Visual Analytics tools will lead to production line monitoring and assessment enhancement and to a new work frame. Integration of innovative collaborative tools to procedural changes like gamification of production are options available to the users of KYKLOS 4.0. The module will provide overall general-purpose architecture in order to model decisions, define dependencies among those decisions or artefacts and will provide an environment in which to implement the logic for the automatic generation of configuration files or documents.

The first layer of user interaction is a virtual marketplace which includes all the available services from different factories, logistics, pricing, etc. KYKLOS 4.0 Marketplace is realised by a set of components, including the KYKLOS 4.0 Customer / User Front-End, the Service Dashboard and associated supporting modules that enable users to interact with the Orchestrator platform for virtualised factory related services provision.

A web-app will allow stakeholders to interact with KYKLOS and combine the ecosystem’s components into a productive system. It will also allow users to monitor their objects of interest and in real time inform of salient incidents. AI technologies are part of the offering, to feed maintenance and early fault diagnosis, as well as hosted task planners for robotic agents. The architecture includes 3rd party app integration capacity to foster adoption in all industries.

KYKLOS 4.0 Transformable Manufacturing System

KYKLOS 4.0 Transformable Manufacturing System consists of distinct subsystems, aiming at achieving flexible and easily repurposed / reconfigured production lines, by applying transformable robot system on KYKLOS 4.0 shop floor.

A short description of the subsystems:

  • Cognitive Learning Toolkit (CLT) with advanced cognition capabilities to be able to learn new assembly and configuration skills, enhancing the fast customization process, assembly and manufacturing procedures of complex equipment and their spare parts as well as fast and effective equipment updatability, re-configurability and disassembly.
    The application will be capable of real time (RT) object recognition and camera tracking with a corresponding server communication module and both augmented reality contents visualization (2D/3D) as well as virtual reality interactive environments. Different content packs ensure applicability in all use case scenarios.

 

  • Automated Task Planner Toolkit will facilitate higher level task planning and provide the appropriate abstraction level and interface needed between low-level robot motions. Automated Task Planner will be equipped with a set of pre-modelled in PDDL software modules purposed with simple tasks, such as drive to location, pick up object, place at location and unload in feeder tasks, etc. stored in a library. However, the module will be able to define new tasks as per need.

 

  • Mixed Reality Product Simulators. With the use of input from wearable computing and sensorial equipment, a long-term goal of this project is to model the user’s actions, anticipate his or her needs, and perform a seamless interaction between the virtual and physical environment.

Rapid Prototyping Module (RPM)

The KYKLOS 4.0 rapid prototyping module will involve a set of technologies that can automatically provide physical models or 3D models, components or parts of components from Computer Aided Design (CAD) data. The materialised models will have numerous uses, as they will be an excellent visual aid for communicating ideas with co-workers or customers (through the recommendation engines, or other platforms). Additionally, the prototypes will be used for the design testing, reducing R&D time and costs.

The RPM module is connected with KYKLOS 4.0 Personalisation Framework, conveying user preferences and needs. A data translator (DT) will be deployed in order to transform the heterogeneous data into technical specifications. After engineers and designers validate final designs, KYKLOS 4.0 Gateway will feed data to the CNC machines. Furthermore, the RPM is going to exchange information with MES, ERP systems and the Cognitive Learning Toolkit.

Real-Time Simulation Module

The KYKLOS 4.0 Real-Time-Simulation (RTS) Module will provide tools and template workflows for efficient build and use steady and transient real-time simulation models. These models are also called Reduced Order Models (ROM’s) and will be built a posteriori in a non-intrusive way based on results from knowledge-based simulations (e.g. Finite Element Models – FEM, Computational Fluid Dynamics – CFD or system-level dynamic simulations). The RTS module, through ROM exchange standardization, will provide the following advantages for the KYKLOS 4.0 platform: simplification of knowledge management, product and process metadata traceability, improved value-chain communication, acceleration of design processes and improving control strategies.

Lifecycle Simulation Element

The Lifecycle Simulation Element will work along KYKLOS 4.0 Personalization Framework and provide simulation algorithms enabled to assess design process risks. It will be integrated as a web tool, capable of complete life cycle analysis for sustainability evaluation of the model’s design.

Carrying out a Life Cycle Analysis (LCA) methodology, inventories will be compiled, impact will be evaluated, and results will be interpreted.

After this process, a profile will be obtained, accenting weaknesses and optimization opportunities.

KYKLOS 4.0 Cyber-Physical Infrastructure

KYKLOS 4.0 Cyber-Physical System (CPS) will achieve seamless union of cognitive system components. KYKLOS 4.0 proposes a holistic mechanism where processes will be allocated and executed dynamically across distributed hardware resources, ensuring flexibility, reduced latency and high system performance. KYKLOS 4.0 highly flexible Cloud and FOG architecture forms a collaborative community of shop floor accelerators, fusing data from sources across KYKLOS 4.0 shop floor and team together with intelligent analytics to transform data into informed decisions.
KYKLOS 4.0 cognitive functions and services will be executed as applications in VMs and the Orchestrator will ensure the automatic placement and allocation of functions, supported by a monitoring system collecting and reporting on the behaviour of the resources.
KYKLOS 4.0 envisions to introduce next generation “smart production lines” through the combination of smart facilities, machines, products and equipment with built-in sensors, self-diagnostics connected to smart systems and applications inside and outside the enterprise boundary.
KYKLOS 4.0 solution will be based on interconnected, virtualised autonomic and cognitive agents (plug-n-play hardware accelerators for Industrial Internet of Things (IIoT) edge/ fog processing of early diagnosis/ prediction functions), effective both on virtual and physical worlds.
Existing shop floors are also part of the system by retrofitting with sensors which allow contribution and participation to the system. By integrating with Enterprise Resource Planning (ERP) and Manufacturing Execution (MES) systems, KYKLOS 4.0 solution will allow optimised workflow scheduling.

KYKLOS 4.0 Hardware Smartification System

KYKLOS 4.0 ecosystem, based on high-level automation and interplay between virtual and physical worlds, promises to bring the predictive power of self-learning, self-predicting analytics, leading to the realisation of “smart factories”. Large scale IIoT establishments will be addressed handling the data generated from different internetworked sources.

KYKLOS 4.0 will create a system of fully networked interconnected, virtualized autonomic and cognitive accelerators found in a fog arrangement within a manufacturing plant will also deal with the vast volume of isolated data that are often stranded in Industrial Internet of Things (IIoT) establishments. By utilizing both edge and embedded systems, KYKLOS 4.0 solution innovates and is practical at the same time. Big data, real-time IIoT insights and networking constrains, such as bandwidth limitations, latency and interoperability are dealt with, while automated deployment and ease of use, optimized resource allocation and flexibility, cost-effectiveness, installation without affecting existing IT infrastructure, expandability and upgradeability is achievable.

Some advantages are, extend component and equipment lifecycles; maintaining UpToDate inventory; optimized RoA (Return on Assets); stabilized work force and resources; reductions in maintenance costs and in total labour costs, allow in-process control ; improve product quality and customer satisfaction; faster reaction times within disruptive production processes.

KYKLOS 4.0 Maintenance Scheduler

The Real-Time Plant Operations & Maintenance Scheduler (RTPOMS) component will manage all information related to the maintenance activities enhanced by prediction algorithms increasing flexibility and productivity. RTPOMS will be a holistic system for all maintenance activities. A novel predictive maintenance model will be developed and integrated in the cloud, with other system components, aggregating data at fog level and providing decision tools optimised for predictive maintenance. The maintenance management solution will provide real-time data, communicate with other components, e.g. the production management. A key feature of RTPOMS will be a streamlined allocation process of staff based on maintenance priorities established by advanced diagnostics/prognostics and health management (PHM – Prognostics and Health Management). It will also be able to manage flexible calendars, working shifts, allocation operations and loading of technicians and distribute technicians on work orders ruled by skill level. Predictive findings will be stored in a database, further analysed and the information from inference engine will be visualised.