IoT-enabled planning, control, and execution in ETO manufacturing: dynamics, requirements, and system architecture: a case study of Brunvoll AS

Confidential until 18. May 202

Simulation and the Fourth Industrial Revolution

Advancements in systems simulation over the past decade have propelled simulationinto a new position as a decision-making tool in Industry 4.0 applications. This paperaddresses the specific benefits of simulation which can be utilized to enable greaterflexibility in decision making in the Industry 4.0 environment. It is stressed thatboth discrete event simulation (DES) and agent-based simulation (ABS) can be usedto represent complex interactions in a fully integrated set of virtual and physicalsystems

Training of Crisis Mappers and Map Production from Multi-sensor Data: Vernazza Case Study (Cinque Terre National Park, Italy)

This aim of paper is to presents the development of a multidisciplinary project carried out by the cooperation between Politecnico di Torino and ITHACA (Information Technology for Humanitarian Assistance, Cooperation and Action). The goal of the project was the training in geospatial data acquiring and processing for students attending Architecture and Engineering Courses, in order to start up a team of "volunteer mappers". Indeed, the project is aimed to document the environmental and built heritage subject to disaster; the purpose is to improve the capabilities of the actors involved in the activities connected in geospatial data collection, integration and sharing. The proposed area for testing the training activities is the Cinque Terre National Park, registered in the World Heritage List since 1997. The area was affected by flood on the 25th of October 2011. According to other international experiences, the group is expected to be active after emergencies in order to upgrade maps, using data acquired by typical geomatic methods and techniques such as terrestrial and aerial Lidar, close-range and aerial photogrammetry, topographic and GNSS instruments etc.; or by non conventional systems and instruments such us UAV, mobile mapping etc. The ultimate goal is to implement a WebGIS platform to share all the data collected with local authorities and the Civil Protectio

Foresighted digital twin for situational agent selection in production control

As intelligent Data Acquisition and Analysis in Manufacturing nears its apex, a new era of Digital Twins is dawning. Foresighted Digital Twins enable short- to medium-term system behavior predictions to infer optimal production operation strategies. Creating up-to-the-minute Digital Twins requires both the availability of real-time data and its incorporation and serve as a stepping-stone into developing unprecedented forms of production control. Consequently, we regard a new concept of Digital Twins that includes foresight, thereby enabling situational selection of production control agents. One critical element for adequate system predictions is human behavior as it is neither rule-based nor deterministic, which we therefore model applying Reinforcement Learning. Owing to these ever-changing circumstances, rigid operation strategies crucially restrain reactions, as opposed to circumstantial control strategies that hence can outperform traditional approaches. Building on enhanced foresights we show the superiority of this approach and present strategies for improved situational agent selection

Enabling the human in the loop: Linked data and knowledge in industrial cyber-physical systems

Industrial Cyber-Physical Systems have benefitted substantially from the introduction of a range of technology enablers. These include web-based and semantic computing, ubiquitous sensing, internet of things (IoT) with multi-connectivity, advanced computing architectures and digital platforms, coupled with edge or cloud side data management and analytics, and have contributed to shaping up enhanced or new data value chains in manufacturing. While parts of such data flows are increasingly automated, there is now a greater demand for more effectively integrating, rather than eliminating, human cognitive capabilities in the loop of production related processes. Human integration in Cyber-Physical environments can already be digitally supported in various ways. However, incorporating human skills and tangible knowledge requires approaches and technological solutions that facilitate the engagement of personnel within technical systems in ways that take advantage or amplify their cognitive capabilities to achieve more effective sociotechnical systems. After analysing related research, this paper introduces a novel viewpoint for enabling human in the loop engagement linked to cognitive capabilities and highlighting the role of context information management in industrial systems. Furthermore, it presents examples of technology enablers for placing the human in the loop at selected application cases relevant to production environments. Such placement benefits from the joint management of linked maintenance data and knowledge, expands the power of machine learning for asset awareness with embedded event detection, and facilitates IoT-driven analytics for product lifecycle management

Approaches to the use of sensor data to improve classroom experience

quipping classrooms with inexpensive sensors can enable students and teachers with the opportunity to interact with the classroom in a smart way. In this paper an approach to acquiring contextual data from a classroom environment, using inexpensive sensors, is presented. We present our approach to formalising the usage data. Further we demonstrate how the data was used to model specific room usage situation as cases in a Case-based reasoning (CBR) system. The room usage data was than integrated in a room recommendations system, reasoning on the formalised usage data. We also detail on our on-going work to integrating the systems presented in this paper into our Smart University vision

Simulation-Based Countermeasures Towards Accident Prevention : Virtual Reality Utilization in Industrial Processes and Activities

Despite growing industrial interests in fully immersive virtual reality (VR) applications for safety countermeasures, there is scanty research on the subject in the context of accident prevention during manufacturing processes and plant maintenance activities. This dissertation aims to explore and experiment with VR for accident prevention by targeting three workplace safety countermeasures: fire evacuation drills, hazard identification and risk assessments (HIRA), and emergency preparedness and response (EPR) procedures. Drawing on the virtual reality accident causation model (VR-ACM) (i.e., 3D modelling and simulation, accident causation, and safety drills) and the fire evacuation training model, two industrial 3D simulation models were utilized for the immersive assessment and training. These were a lithium-ion battery (LIB) manufacturing factory and a gas power plant (GPP). In total, five studies (publications) were designed to demonstrate the potential of VR in accident prevention during the manufacturing processes and maintenance activities at the facility conceptual stages. Two studies were with the LIB factory simulation to identify inherent hazards and assess risks for redesigning the factory to ensure workplace safety compliance. The other three studies constituted fire hazard identifications, emergency evacuations and hazard control/mitigations during the maintenance activity in the GPP simulation. Both study models incorporated several participants individually immersed in the virtual realm to experience the accident phenomena intuitively. These participants provided feedback for assessing the research objectives. Results of the studies indicated that several inherent hazards in the LIB factory were identified and controlled/mitigated. Secondly, the GPP experiment results suggested that although the maintenance activity in the virtual realm increased the perception of presence, a statistically significant delay was recorded at the pre-movement stage due to the lack of situational safety awareness. Overall, the study demonstrates that participants immersed in a VR plant maintenance activity and manufacturing factory process simulation environments can experience real-time emergency scenarios and conditions necessary for implementing the essential safety countermeasures to prevent accidents.Vaikka kiinnostus virtuaalitodellisuuden (VR) käyttöön turvallisuuden varotoimissa teollisuudessa on kasvanut, tutkimuksia ei ole juurikaan tehty onnettomuuksien ehkäisystä valmistus- ja kunnossapitotoiminnassa. Tämän väitöskirjan tavoitteena on tutkia ja kokeilla VR:ää tapaturmien ehkäisyssä kohdistuen kolmeen työpaikan turvallisuuden varotoimeen: paloharjoitukset, riskien arvioinnit sekä hätätilanteiden valmiusmenettelyt ja toimintasuunnitelmat (EPR). Kokemuksellisessa ja uppouttavassa koulutuksessa hyödynnettiin kahta teollisuuden 3D-simulointimallia, jotka nojautuvat virtuaalitodellisuuden onnettomuuksien aiheutumismalliin (VR-ACM) (eli 3D-mallinnus- ja simulointi, onnettomuussyy- ja turvallisuuskoulutus) sekä paloharjoitusmalliin. Nämä 3D-simulointimallit ovat litiuminoniakkuja (LIB) valmistava tehdas, joka rakennettiin Visual Components 3D-simulointiohjelmistolla (versio 4.0) ja kaasuvoimala (GPP) Unrealin reaaliaikaisella pelimoottorilla (versio 4.2). Yhteensä viisi tutkimusta (julkaisua) suunniteltiin havainnollistamaan VR:n potentiaalia tapaturmien ehkäisyssä valmistusprosessin layout-suunnittelun ja tehtaan konseptivaiheissa tehtävän kunnossapidon aikana. Kaksi tutkimusta tehtiin LIB-tehdassimulaatiolla vaarojen tunnistamiseksi sekä riskien arvioimiseksi. Tutkimukset tehtiin tehtaan uudelleensuunnittelua varten, työturvallisuuden noudattamisen varmistamiseksi. Muut kolme tutkimusta käsittelevät palovaaran tunnistamista, hätäevakuointia ja riskien vähentämistä huoltotoiminnan aikana GPP-simulaatiossa. Molemmissa tutkimusmalleissa oli useita virtuaalimaailmaan uppoutuneita osallistujia, jotka saivat kokea onnettomuudet yksilöllisesti ja intuitiivisesti. Osallistujat antoivat palautetta kokeen jälkeisessä kyselyssä. Kyselyn tuloksien avulla LIB-tehtaassa tunnistettiin ja lievennettiin useita vaaroja. GPP-kokeilun tulokset viittasivat siihen, että vaikka ylläpitotoiminta virtuaalimaailmassa lisäsi teleläsnäoloa, tilastollisesti merkittävä viive kirjattiin liikettä edeltävässä vaiheessa turvallisuustietoisuuden puuteen vuoksi. Kaiken kaikkiaan tutkimus osoittaa, että VR-laitoksen kunnossapitotoimintaan ja tuotantotehtaan prosessisimulaatioympäristöihin uppoutuvat osallistujat voivat kokea reaaliaikaisia hätäskenaarioita ja olosuhteita, jotka ovat välttämättömiä olennaisten turvallisuustoimien toteuttamiseksi.fi=vertaisarvioitu|en=peerReviewed

Influences on aircraft target off-block time prediction accuracy

With Airport Collaborative Decision Making (A-CDM) as a generic concept of working together of all airport partners, the main aim of this research project was to increase the understanding of the Influences on the Target Off-Block Time (TOBT) Prediction Accuracy during A-CDM. Predicting the TOBT accurately is important, because all airport partners use it as a reference time for the departure of the flights after the aircraft turn-round. Understanding such influencing factors is therefore not only required for finding measures to counteract inaccurate TOBT predictions, but also for establishing a more efficient A-CDM turn-round process. The research method chosen comprises a number of steps. Firstly, within the framework of a Cognitive Work Analysis, the sub-processes as well as the information requirements during turn-round were analysed. Secondly, a survey approach aimed at finding and describing situations during turn-round that are critical for TOBT adherence was pursued. The problems identified here were then investigated in field observations at different airlines’ operation control rooms. Based on the findings from these previous steps, small-scale human-in-the-loop experiments were designed aimed at testing hypotheses about data/information availability that influence TOBT predictability. A turn-round monitoring tool was developed for the experiments. As a result of this project, the critical chain of turn-round events and the decisions necessary during all stages of the turn-round were identified. It was concluded that information required but not shared among participants can result in TOBT inaccuracy swings. In addition, TOBT predictability was shown to depend on the location of the TOBT turn-round controller who assigns the TOBT: More reliable TOBT predictions were observed when the turn-round controller was physically present at the aircraft. During the experiments, TOBT prediction could be improved by eight minutes, if available information was cooperatively shared ten minutes prior turn-round start between air crews and turn-round controller; TOBT prediction could be improved by 15 minutes, if additional information was provided by ramp agents five minutes after turnround start