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Publications
Find out about the publications of the OMiLAB.
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Year |
Contributing OMiLAB |
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| Specification of FAIRWork Use Case and DAI-DSS Prototype Report – D2.1 | 2022 | FAIRWork Project | |
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Abstract. Deliverable D2.1 specifies the design requirements for the first relevant stage in the Horizon Europe project FAIRWork aiming at fair decision making within complex systems in the production domain. From the planned use cases of the industrial partners – FLEX “Automated Test Building”, “Worker Allocation”, “Machine Maintenance After Breakdown” and CRF “Workload Balance”, “Delay of Material” and “Quality Issues” – the report constitutes and specifies the basic design decisions for research and development directions in the project. A major contribution is the provision of the initial architecture of an innovative service framework for decision support systems.
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| DAI-DSS Research Specification – D3.1 | 2023 | FAIRWork Project | |
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Abstract. This report focuses on the deliverable “D3.1 – DAI-DSS Research Specification”, part of the Horizon Europe project FAIRWork. The deliverable aims to describe the specific research factors in selected use cases of industrial partners FLEX and CRF. It presents a research strategies and factors catalogue that serves as a framework for conducting research within the Democratized AI-based Decision Support System (DAI-DSS). DAI-DSS research specifications are closely related to deliverables “D2.1 Specification of FAIRWork Use Case and DAI-DSS Prototype Report” and “D4.1 DAI-DSS Architecture and Initial Documentation and Test Report”.
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| First DAI-DSS Research Collection – D3.2 | 2024 | FAIRWork Project | |
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Abstract. This report focuses on deliverable “First DAI-DSS Research Collection”, which is part of the Horizon Europe project FAIRWork. The deliverable aims to describe a first iteration on guidelines, methods and tools for democratising the production process in the light of their flexibilisation while using Artificial Intelligence, Optimisation, Human Factors Analytics, and Multi Agent Systems (MAS) as mediators in form of prototypes, physical experiments in laboratories, implemented questionnaires, modelling tools or semantic model of criteria catalogues. It presents a collection of concepts, methods, studies, and services of a research framework within the Democratised AI Decision Support System (DAI-DSS). The DAI-DSS research collection is based on the fundamental principles related to the research intended within the frame of this project that was described in Deliverable “D3.1 DAI-DSS Research Specification” and incorporates cross-connections with Deliverable “D4.1.1 DAI-DSS Architecture and initial Documentation and Test Report“ on the basis of functional components of the DAI-DSS system architecture.
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| Final DAI-DSS Research Collection – D3.3 | 2025 | FAIRWork Project | |
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Abstract. This deliverable shows the “Final DAI-DSS Research Collection” as part of the Horizon Europe project FAIRWork. The deliverable aims to describe guidelines, methods and tools for democratising the production process in the light of their flexibilization utilizing artificial intelligence (AI), Optimisation, Human Factors Analytics, and multi-agent systems (MAS) as mediators in the form of prototypes, physical experiments in laboratories, implemented questionnaires, modelling tools or semantic model of criteria catalogues. Importantly, this collection is published in the FARIWork Innovation Shop and represents the key support features for the Democratic AI-based Decision Support System Support System (DAI-DSS). The FAIRWork Innovation shop is accessible online as Deliverable 3.3. This document is considered the accompanying document of the deployed online version.
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| DAI-DSS Architecture and Initial Documentation and Test Report – D4.1 | 2023 | FAIRWork Project | |
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Abstract. This deliverable “D4.1 – FAIRWork Architecture and initial Documentation and Test Report” for is the first description of the architecture, which will be updated in M20 and M30 in form of updated deliverables.
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| DAI-DSS Architecture and Initial Documentation and Test Report – D4.1.1 | 2024 | FAIRWork Project | |
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Abstract. This deliverable “D4.1.1 – FAIRWork Architecture and initial Documentation and Test Report” is the second iteration of the deliverable D4.1 which has been submitted in the month M6 of the project. This iteration of the deliverable builds upon it and provides a comprehensive overview of the current status of the implementation of DAI-DSS components and services required for the decision support.
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| Initial DAI-DSS Prototype – D4.2 | 2023 | FAIRWork Project | |
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Abstract. This deliverable, “D4.2 – Initial DAI-DSS Prototype”, is the first reference implementation focusing on the synthesis of fundamental components to establish a shared comprehension of the operational principles behind DAI-DSS. It aims to describe how the different DAI-DSS components fit together, forming a complete and cohesive structure in which the functionalities of the blocks are well-defined, the complementarity of the structure is explored, and the technological component is described in terms of fulfilling its purposes and integrating with the neighbouring structures that are part of the architecture. Next is the DAI-DSS Orchestrator. The Orchestrator plays a very important and central role in the architecture of this system. Its purpose is to provide coordination in the exchange of information and decisions between the various parts of the system. Like the conductor in an orchestra, the DAI-DSS carries out the decision-making process, and the involved individual services retrieve the relevant data from the knowledge database. This currently takes place in two parallel ways. At a more advanced stage is the Workflow-based Orchestrator. In this orchestrator, a workflow engine offers the possibility of executing workflows, i.e., the execution of tasks that follow a well-defined path leading to the triggering or realisation of an AI service that offers a recommendation for decision-making on issues identified in the business process for which the system is built. For demonstration purposes, a workflow was built in which worker data is retrieved, and the order of a part is requested in the Workload Balance Use Case Scenario. The step-by-step execution of the orchestration is documented in order to elucidate how the orchestration of the building blocks can take place in a real, concrete case from the manufacturing industry in this example. It presents the DAI-DSS Configurator, a tool designed to enhance decision support systems through efficient configuration and integration frameworks. It explains the configurator's components: the Configuration Framework, which assists in creating decision models and strategies, and the Configuration Integration Framework, which generates system configurations from these models. The report details the prototype's configuration steps, illustrated for clarity. It also allows for microservices and workflow configuration, featuring a user-friendly interface with a wizard for UI components combination. The DAI-DSS Knowledge Base is highlighted as a central data repository, storing user properties, sensor data, and processed data. It plays a key role in the system's data flow, integrating with the Configurator and using REST API for data retrieval. The report covers the integration of AI services using REST-API endpoints, emphasising ease of access and industry-standard practices like Swagger documentation. It explores various algorithms, including Neural Networks and Decision Trees, and the integration of human factors data for assessing worker resilience. Deployment details of the AI services are discussed, focusing on hosting, management, and future enhancements like data catalogues and decision pattern services for resource allocation and predictive maintenance. Finally, the report addresses the extension of the DAI-DSS with new services for various industrial use cases. It discusses customising services through conceptual modelling and the advantages of rule-based approaches over machine learning methods. The services aim to optimise resource allocation, improve productivity, and address human factors, thereby enhancing the system's decision-making capabilities in complex industrial scenarios.
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| Final DAI-DSS Prototype, Documentation and Test Report – D4.3 | 2025 | FAIRWork Project | |
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Abstract. This deliverable, “D4.3 – Final DAI-DSS Prototype, Documentation and Test Report”, provides a comprehensive overview of the final implementation of the DAI-DSS. Building on the foundations established in “D4.1 – DAI-DSS Architecture and Initial Documentation and Test Report” and “D4.2 – Initial DAI-DSS Prototype”, this document details the integration, orchestration, and deployment of the components for AI-based decision-making within industrial applications. The prototype is designed to enhance operational efficiency and support decision-making for various scenarios. In this last version, the DAI-DSS Prototype extends its applicability across multiple industrial use cases, including workforce allocation, production planning, machine maintenance, and validation of documents. The demonstration materials can be accessed via the following link:
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| DAI-DSS FAIRWork Knowledge Base at Use Case Site – D5.1 | 2023 | FAIRWork Project | |
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Abstract. This document is Deliverable D5.1, which focuses on the FAIRWork Knowledge Base at the Use Case Site. The deliverable encompasses the results of Task T5.1 “Modelling FAIRWork for Production Processes” and Task T5.2 “Creating FAIRWork Knowledge Base”. The document needs to be seen in the context of the FAIRWork objective to provide a decision support system that (a) integrates digital twins to optimize the overall production process according to multiple parameters, and (b) democratizes decision making granting human worker and machines a say during decision making. The project combines (a) model-based approaches to transparently design, simulate and improve decision making, (b) a co-creation laboratory using models and physical experiments as communication media to all actors and, (c) reliability indication of data and AI algorithms.
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| DAI-DSS Infrastucture and Setup Report at Use Case Site – D5.2 | 2024 | FAIRWork Project | |
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Abstract. The purpose of the document, "D5.2 – DAI-DSS INFRASTRUCTURE AND SETUP REPORT AT USE CASE SITE" is to provide an update on the progression and current state of implementation on use case sites of the Democratic AI-based Decision Support System (DAI-DSS) Architecture as part of the FAIRWork project. Section 2 of the deliverable describes the overall infrastructure setup process at the use case partner side. It also describes the setup of the isolated computing system for the DAI-DSS tool to avoid risks to the corporate network. Section 3 then details the technical preparation tasks such as data collection, human expert training, user selection and implantation of the current DAI-DSS prototype as a use case site and integration with the legacy systems. Section 4 describes the overall testing procedure. This includes a brief description of the user evaluation and the corresponding KPIs for testing the use cases in general. In summary, this deliverable provides a brief update on the deployment of the first iteration of the FAIRWork DAI DSS. The first iteration has clearly shown that the DAI-DSS is a useful tool for future decision making in Flex and CRF.
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| FAIRWork Exploitation Tools (Website, Social Media, Flyer) – D8.1 | 2023 | FAIRWork Project | |
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Abstract. This report is the accompanying document for deliverable 8.1 (D8.1), in which communication and exploitation tools were created and instantiated for the FAIRWork project. They will be used to communicate information during the project runtime and support exploitation of created artefacts within and after the project runtime. Additionally, the document discusses the FAIRWork innovation shop, which is not yet available, but will be established in D8.2. The following list provides an overview of the tools, which are discussed in this document and includes important links to where they can be found:
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