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Rajendran, Ajith, and Gautham Asokan. "Real Time Monitoring of Machining Process and Data Gathering for Digital Twin Optimization." Thesis, KTH, Industriell produktion, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-301594.
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In the development stages of a Digital twin of production assets, especially machine tools, real time process monitoring and data gathering proves to be vital. Having a monitoring system that monitors and updates the operators or managers in real time, helps improve productivity in terms of reducing downtime through predictive/preventive analytics and by incorporating in process quality assessment capabilities. When it comes to Real time monitoring of machine tools andprocesses, sensor technologies have proven to be the most effective and widely researched. Years of research and development have paved the way for many smart sensor technologies that come both in built with the machine tools as well as external applications. However, these technologies prove to be expensive and complicated to implement especially for Small and Medium Enterprises. This thesis focuses on evaluating and testing a simple, cost-efficient monitoring system using inexpensive sensor technologies that would help optimize an existing Digital twin setup for machine tools for Small and Medium Enterprises. Experiments with a 5 axis CNC machine tool using different tools and varying operating parameters, materials were performed,and the relevant sensor data were collected, mapped, analysed for accuracy and benchmarking. The thesis also evaluates the integration of this data with the information already collected from other sources, improve existing data reliability, and provides guidelines on this could be transformed usefully to create more value to SME’s.
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Ferdousi, Rahatara. "Digital Twin Disease Diagnosis Using Machine Learning." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/42773.
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COVID-19 has led to a surge in the adoption of digital transformation in almost every sector. Digital health and well-being are no exception. For instance, now people get checkupsvia apps or websites instead of visiting a physician. The pandemic has pushed the health-care sector worldwide to advance the adoption of artificial intelligence (AI) capabilities.Considering the demand for AI in supporting the well-being of an individual, we presentthe real-life diagnosis as a digital twin(DT) diagnosis using machine learning. The MachineLearning (ML) technology enables DT to offer a prediction. Although several attemptsexist for predicting disease using ML and a few attempts through ML of DT frameworks,those do not deal with disease risk prediction. In addition, most of them deal with singledisease prediction after the occurrence and rely only on clinical test data like- ECG report,MRI scan, etc.To predict multiple disease/disease risks, we propose a dynamic machine learning algo-rithm (MLA) selection framework and a dynamic testing method. The proposed frameworkaccepts heterogeneous electronic health records (EHRs) or digital health status as datasetsand selects suitable MLA upon the highest similarity. Then it trains specific classifiers forpredicting a specific disease/disease risk. The dynamic testing method for prediction isused for predicting several diseases.We described three use cases: non-communicable disease(NCD) risk prediction, mentalwell-being prediction, and COVID-19 prediction. We selected diabetes, risk of diabetes,liver disease, thyroid, risk of stroke as NCDs, mental stress as a mental health issue, andCOVID-19. We employed seven datasets, including public and private datasets, with adiverse range of attributes, sizes, types, and formats to evaluate whether the proposedframework is suitable to data heterogeneity. Our experiment found that the proposed methods of dynamic MLA selection could select MLA for each dataset at cosine similarityscores ranging between 0.82-0.89. In addition, we predicted target disease/disease risks atan accuracy ranging from 94.5% to 98%.To verify the performance of the framework-selected predictor, we compared the accuracy measures individually for each of the three cases. We compared them with traditionalML disease prediction work in the literature. We found that the framework-selected algorithms performed with good accuracy compared to existing literature.
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Staněk, Václav. "Návrh digitálního dvojčete CNC obráběcího stroje." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2019. http://www.nusl.cz/ntk/nusl-402643.
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The Master’s thesis deals with design of digital twins of machine tools and application of designed procedure on a case study – digital twin of the machine tool MCV 754 Quick. In the first part are described current roles of digital twins in the field of machine tools and also hardware and software options for creating them. Software and hardware tools by Siemens (Mechatronics Concept Designer and SIMIT) are used for the case study. The complex procedure of creating the digital twin is designed in the second part, starting with preparation of a model, ending with the virtual commissioning of the machine tool MCV 754 Quick. The procedure is described in detail, including preparation of 3D model of the machine tool, assignment of physical properties and joints, preparation of PLC, connection all the elements of the whole system: Sinumerik – SIMIT – Mechatronics Concept Designer and controlling the twin via CNC automation system. Output of the thesis is the virtually commissioned machine tool, capable of being controlled by Sinumerik 840D sl. This is the first step in development of the full-fledged digital twin of machine tool, which can be used for testing the functionality and capability of this new technology in industry.
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Ravi, Rahul. "Digital Twin of an Automatic Machine Using Unity and Prespective Software." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2020.
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Digital Twin is the modern way of prototyping. It is a new layer on top of an existing model, extending the possibilities. This thesis work was carried out and developed at the research laboratory “LIAM LAB”. The main focus was to study the efficacy in developing a Digital Twin of an automatic machine in detail. It is a packaging machine (Technocoil 2200) from “SICA” using PRESPECTIVE, a Digital Twining software based on a game engine UNITY3D. Digital Twin tools and solutions are offered by many major companies, but these have the potential disadvantage of vendor lock-in. Although these brands claim to be open, their tools do not operate very well with third-party software. This makes many users to opt for openness which will help in integrating many features as per their requirement. Another main factor is providing high resolution simulations with an ability to solve complex physical problems which could be handled by Unity.
The process of modelling a Digital Twin is studied extensively in this thesis work. But, in particular the tube guide part of the machine was considered, and its Digital Twin was modelled using Prespective and subsequently the interfacing of the model in Prespective with a PLC was implemented. Finally, the interfacing is validated by forcing values from controller and visualizing the outputs in Unity.
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Smirnova, Tatiana. "Dynamic Analysis and Modeling of Machine Tool Parts." Licentiate thesis, Karlskrona : Department of Signal Processing, School of Engineering, Blekinge Institute of Technology, 2008. http://www.bth.se/fou/Forskinfo.nsf/allfirst2/8628d01b6722765cc12573e70044bfd2?OpenDocument.
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McCoy, Mason Eugene. "A Twitter-Based Prediction Tool for Digital Currency." OpenSIUC, 2018. https://opensiuc.lib.siu.edu/theses/2302.
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Digital currencies (cryptocurrencies) are rapidly becoming commonplace in the global market. Trading is performed similarly to the stock market or commodities, but stock market prediction algorithms are not necessarily well-suited for predicting digital currency prices. In this work, we analyzed tweets with both an existing sentiment analysis package and a manually tailored "objective analysis," resulting in one impact value for each analysis per 15-minute period. We then used evolutionary techniques to select the most appropriate training method and the best subset of the generated features to include, as well as other parameters. This resulted in implementation of predictors which yielded much more profit in four-week simulations than simply holding a digital currency for the same time period--the results ranged from 28% to 122% profit. Unlike stock exchanges, which shut down for several hours or days at a time, digital currency prediction and trading seems to be of a more consistent and predictable nature.
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Viking, Jakob. "Identifying Machine States and Sensor Properties for a Digital Machine Template : Automatically recognize states in a machine using multivariate time series cluster analysis." Thesis, Mittuniversitetet, Institutionen för informationssystem och –teknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:miun:diva-42295.
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Digital twins have become a large part of new cyber-physical systems as they allow for the simulation of a physical object in the digital world. In addition to the new approaches of digital twins, machines have become more intelligent, allowing them to produce more data than ever before. Within the area of digital twins, there is a need for a less complex approach than a fully optimised digital twin. This approach is more like a digital shadow of the physical object. Therefore, the focus of this thesis is to study machine states and statistical distributions for all sensors in a machine. Where as majority of studies in the literature focuses on generating data from a digital twin, this study focuses on what characteristics a digital twin have. The solution is by defining a term named digital machine template that contains the states and statistical properties of each sensor in a given machine. The primary approach is to create a proof of work application that uses traditional data mining technologies and clustering to analyze how many states there are in a machine and how the sensor data is structured. It all results in a digital machine template with all of the information mentioned above. The results contain all the states a machine might have and the possible statistical distributions of each senor in each state. The digital machine template opens the possibility of using it as a basis for creating a digital twins. It allows the time of development to be shorter than that of a regular digital twin. More research still needs to be done as the less complex approach may lead to missing information or information not being interpreted correctly. It still shows promises as a less complex way of looking at digital twins since it may become necessary due to digital twins becoming even more complex by the day.
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Shi, Xun Xun. "Intelligent Differential Ion Mobility Spectrometry (iDMS): A Machine Learning Algorithm that Simplifies Optimization of Lipidomic Differential Ion Mobility Spectrometry Parameters." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/42794.
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Glycosphingolipids such as α- and β-glucosylceramides (GlcCers) and α- and β- galactosylceramides (GalCers) are stereoisomers differentially synthesized by gut bacteria and their mammalian hosts in response to environmental insult. Thus, lipidomic assessment of α- and β-GlcCers and α- and β-GalCers is crucial for inferring biological functions and biomarker discovery. However, simultaneous quantification of these stereoisomeric lipids is difficult due to their virtually identical structures. Differential mobility mass spectrometry (DMS), as an orthogonal separation to high performance liquid chromatography used in electrospray ionization, tandem mass spectrometry (LC-ESI-MS/MS), can be used to separate stereoisomeric lipids. Generating LC-ESI-DMS-MS/MS methods for lipidomic analyses is exceedingly difficult demanding intensive manual optimization of DMS parameters that depend on the availability of synthetic lipid standards. Where synthetic standards do not exist, method development is not possible. To address this challenge, I developed a supervised in silico machine learning approach to accelerate method development for ion mobility-based quantification of lipid stereoisomers. I hypothesized that supervised neural network models could be used to learn the relationships between lipid structural characteristics and optimal DMS machine parameter values thereby reducing the total number of empirical experiments required to develop a DMS method and enabling users to “predict” DMS parameters for analytes that lack synthetic standards. Specifically, this thesis describes a supervised learning approach that learns the relationship between two DMS machine parameter values (separation voltage and compensation voltage) and two lipid structural features (N-Acyl chain length and degree of unsaturation). I describe here, iDMS, an algorithm that was trained on 17 lipid species, and can further simulate results of DMS manual method development and suggest optimal parameter values for 47 lipid species. This approach promises to greatly accelerate the development of assays for the detection of lipid stereoisomers in biological samples.
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Amato, Beatrice. "Virtual comissioning and software developement for an automatic machine prototype." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2021. http://amslaurea.unibo.it/22466/.
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The objective of this work is to realize a prototype of an automatic machine for the pharmaceutical industry. This model aims to produce a new generation of drugs.
The process, that needs to be followed to produce a new type of drug, starts from the medicine in liquid form, then through a drastic lowering of the temperature, it passes to the solid state, and then is freeze-dried, in a sterile environment. The final result is a medicine in beads form.
The machine is mainly composed of three robots and a dosing arm unit.
Starting from a reservoir where the drug is in liquid form, the dosing arm unit sucks the liquid through ninety-six pipettes.
In the initialization phase, the content of each pipette is emptied inside the weighted tubes by a dosing arm unit, then the first robot proceeds to the gross weighing of the test pieces. If all the doses are equal, then the dosing arm unit can proceed with the production of the beads, starting by sucking again the fluid from the reservoir.
For nominal dosing, the dosing arm unit moves above a nitrogen-cooled plate, at a temperature of -110°C and let each pipette discharges a drop of liquid on to the freezing plate.
Trays are handled by a pair of robotic arms.
Since this is a completely new type of machine, the different phases are being studied and under development, so most of them have not yet being manufactured.
For this reason, it has been created a simulation model that forms the basis of the Digital Twin, since it can already be used at a very early stage of the development process to test and compare various concepts.
A 3D graphic model of the machine has been devised and thanks to the virtual commissioning, the physical behavior of the machine has been reproduced in a computer-generated way, through a software simulation applied to the Digital Twin.
This safe virtual environment allowed to test the logic programmed into the PLC, for the single components and the synchronization of the whole machine movements.
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Iftikhar, Rana Faheem, and Sabor Amini. "Digitalising The Smith Machine." Thesis, Högskolan i Halmstad, Akademin för informationsteknologi, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:hh:diva-44815.
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Health and fitness sector is becoming increasingly popular, and technology is being integrated into the fitness industry. This project proposed to digitalise the smith machine by creating a system to generate force through an electric motor to replace free weights. Because the exercise machine no longer needs to be loaded and unloaded with free weights, digitalisation of the smith machine will allow several users to utilise the same training machine. It will also be possible to track users' training information, such as weight lifted and the number of sets and reps performed during a workout. In this thesis, an Electrical speed controller (ESC) called VESC was used to control the BLDC motor. Experiments were conducted to find a method to control the torque. The result was producing a constant torque with a margin of error of 1-1.5 kilograms. Furthermore, two algorithms were developed where the resistance varies during the path of motion, which indicates that it is possible to develop the system to individualise resistance to improve training performance and rehabilitation. The conclusion that could be drawn is that this system can be used to replace free weights with an electric motor.Hälso- och fitness sektorn blir allt populärare ochtekniken integreras alltmer ifitnessbranschen. Detta projekt syftar på att digitaliserasmithmaskin genom att skapa ettsystem för att generera kraft genom en elmotor föratt ersätta fria vikter. Genom att ersättalösa vikter med en elmotor så slipper användaren hanteralösa vikter vilket också underlättarför flera användaren att använda samma träningsmaskin.Det kommer också vara möjligt attspåra användarnas träningsinformation, såsom vikt,antalet set och repetitioner som utförtsunder ett träningspass.I detta projekt användes en motorstyrenhet som heterVESC för att styra en BLDC-motor.Flertalet experiment utfördes för att hitta en metodför att kontrollera vridmomentet. Dettaresulterade till att ett konstant vridmoment med enfelmarginal på 1-1.5 kilogram uppnåddes.Dessutom utvecklades två algoritmer där motståndetvarierar dynamiskt, vilket indikerar attdet är möjligt att i framtiden utveckla systemet föratt individualisera motstånd och därmedförbättra resultatet i träning och rehabilitering.Slutsatsen som kan dras är att detta system kananvändas för att ersätta fria vikter med en elmotor.
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Giudiceandrea, Roberto. "Virtual Commissioning of a crown-caps manufacturing machine through hardware in the loop architecture." Master's thesis, Alma Mater Studiorum - Università di Bologna, 2019.
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Questo progetto di tesi, svolto in collaborazione con l’azienda SACMI S.C. di Imola e sviluppato all’interno del laboratorio industriale di ricerca LIAM Lab, ha come obiettivo la realizzazione di un Digital Twin di una sezione di macchina in fase di costruzione in azienda, attraverso l’ausilio del Software commerciale Virtuos. In particolare, dopo aver studiato le caratteristiche del Software, le possibili configurazioni e le tecnologie di comunicazione con PLC di terze parti, è stata eseguita una modellazione cinematica e logica della macchina. Ottenuto il modello, lo si è messo in comunicazione con il codice di controllo fornito dall’azienda. Questa comunicazione può avvenire in locale, ovvero con il codice di controllo eseguito sulla stessa macchina dove si trova Virtuos («PC Virtuos»), oppure in remoto, dove il codice viene eseguito su un IPC Beckhoff connesso al «PC Virtuos» simulando la configurazione Hardware del progetto reale. Il tutto si concretizza nella visualizzazione delle movimentazioni comandate. A questo livello, il Digital Twin si presta supportare la fase di debug e all’ottimizzazione del codice macchina, presupponendo però un corretto dimensionamento degli azionamenti. Successivamente si è valutata la possibilità di estendere Virtuos a meccanismi di co-simulazione al fine estendere le caratteristiche del modello con proprietà dinamiche, con l’obiettivo di verificare la bontà di Virtuos come strumento per validare le assunzioni fatte nella fase di dimensionamento del sistema. La co-simulazione dinamica viene valutata anche per modellare la flessibilità di alcune parti critiche della macchina oppure l’effetto degli urti tra gli oggetti movimentati durante il ciclo di lavoro, fornendo un intuitivo feedback grafico.
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BLOMKVIST, YLVA, and LOENBOM LEO ULLEMAR. "Improving supply chain visibility within logistics by implementing a Digital Twin : A case study at Scania Logistics." Thesis, KTH, Skolan för industriell teknik och management (ITM), 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-279054.
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As organisations adapt to the rigorous demands set by global markets, the supply chains that constitute their logistics networks become increasingly complex. This often has a detrimental effect on the supply chain visibility within the organisation, which may in turn have a negative impact on the core business of the organisation. This paper aims to determine how organisations can benefit in terms of improving their logistical supply chain visibility by implementing a Digital Twin — an all-encompassing virtual representation of the physical assets that constitute the logistics system. Furthermore, challenges related to implementation and the necessary steps to overcome these challenges were examined. The results of the study are that Digital Twins may prove beneficial to organisations in terms of improving metrics of analytics, diagnostics, predictions and descriptions of physical assets. However, these benefits come with notable challenges — managing implementation and maintenance costs, ensuring proper information modelling, adopting new technology and leading the organisation through the changes that an implementation would entail. In conclusion, a Digital Twin is a powerful tool suitable for organisations where the benefits outweigh the challenges of the initial implementation. Therefore, careful consideration must be taken to ensure that the investment is worthwhile. Further research is required to determine the most efficient way of introducing a Digital Twin to a logistical supply chain.I takt med att organisationer anpassar sig till de hårda krav som ställs av den globala marknaden ökar också komplexiteten i deras logistiknätverk. Detta har ofta en negativ effekt på synligheten inom logistikkedjan i organisationen, vilken i sin tur kan ha en negativ påverkan på organisationens kärnverksamhet. Målet med denna studie är att utröna de fördelar som organisationer kan uppnå vad gäller att förbättra synligheten inom deras logistikkedjor genom att implementera en Digital Tvilling — en allomfattande virtuell representation av de fysiska tillgångar som utgör logistikkedjan. Resultaten av studien är att Digitala Tvillingar kan vara gynnsamma för organisationer när det gäller att förbättra analys, diagnostik, prognoser och beskrivningar av fysiska tillgångar. Implementationen medför dock utmaningar — hantering av implementations- och driftskostnader, utformning av informationsmodellering, anammandet av ny teknik och ledarskap genom förändringsarbetet som en implementering skulle innebära. Sammanfattningsvis är en Digital Tvilling ett verktyg som lämpar sig för organisationer där fördelarna överväger de utmaningar som tillkommer med implementationen. Därmed bör beslutet om en eventuell implementation endast ske efter noggrant övervägande. Vidare forskning behöver genomföras för att utröna den mest effektiva metoden för att introducera en Digital Tvilling till en logistikkedja.
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Edgar, Alexander Montero Vera. "Virtual Commissioning of an industrialwood cutter machine : A software in the loop simulation." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2020. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-77401.
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The methods used today for the commissioning and validation of industrial machines requires theconstruction of physical prototypes. Those prototypes help the engineers to e.g. validate if theprogram code meant to control a machine works as intended. In recent years the development ofnew techniques for the commissioning and validation of industrial machines has changed rapidlythanks to the development of new software. The method used in this thesis is called simulationin the loop. Another method that can be benecial to use is hardware in the loop. Using thosemethods for the commissioning of a machine is called virtual commissioning. The simulation inthe loop method is used to simulate both the machine and the control system that operate thatmachine. This is called a digital twin, a virtual copy of the physical hardware and its control systemthat can be used without the need for a real prototype to be available.The software used in this thesis comes all from the company Siemens and those are TIA Portal,Mechatronics Concept Designer, SIMIT and PLCSim Advanced. By using those programs it waspossible to build a digital twin with rigid body dynamics and its control system of the industrialmodel that was given by the company Renholmen AB. This model contained all the necessarycomponents needed for a virtual commissioning project to be done without the need to be at thefactory oor.The results showed that it was possible to achieve a real time simulation, allowing the possibilityto trim the controller parameters without the need of a physical prototype. Design errors were alsofound thanks to the results of the simulation.This new technique has shown to be a useful tool due to most of the work could be done on a digitalmodel of the machine. Simulations can reduce the time to market for industrial machines and alsohelp engineers to validate and optimize the product at an early stage. This tool that can be usedto validate industrial machines before they are created.
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Únar, Jan. "Posouzení geometrické přesnosti obráběcího centra pomocí digitálních inklinometrů." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2021. http://www.nusl.cz/ntk/nusl-444307.
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This diploma thesis deals with assessment of geometric accuracy of machining center MCV 754 QUICK. BlueSYSTEM digital inclinometers from WYLER AG, XL-80 laser interferometer from RENISHAW, Ballbar QC20-W from RENISHAW and LaserTRACER self-guiding laser interferometer from ETALON AG were used to measure accuracy. Error of the X straightness in the direction of the Z axis was assessed. The first part of the paper describes the geometric accuracy of the machine, currently available instruments for measuring geometric accuracy and an explanation of straightness. The second part consists of the design of measurements, experiment, evaluation and comparison of results and recommendations for teaching.
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Rajdl, Filip. "Virtuální zprovoznění výměníku nástrojů CNC stroje." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2020. http://www.nusl.cz/ntk/nusl-417784.
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The Master’s thesis deals with virtual commissioning of the CNC machine tool changer. First deals with current state of knowledge with a systematic analysis of virtual commissioning. The 3D model is created by physical properties, sensors, actuators and control signals. In the last part of this thesis, a PLC program and visualization is created. The programs needed to create a virtual commissioning are jsou NX 12.0 - Mechatronic concept designer, SIMIT Simulation Platform V10.0 a TwinCAT 3.
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Andreev, Maxim, Artem Kolesnikov, Uwe Grätz, and Julia Gundermann. "Simulation-based system reliability analysis of electrohydraulic actuator with dual modular redundancy." Technische Universität Dresden, 2020. https://tud.qucosa.de/id/qucosa%3A71268.
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This paper describes the failure detection system of an electro-hydraulic actuator with dual modular redundancy based on a hybrid twin TM concept. Hybrid twin TM is a combination of virtual twin that operates in parallel with the actuator and represents its ideal behaviour, and a digital twin that identifies possible failures using the sensor readings residuals. Simulation-based system reliability analysis helps to generate a dataset for training the digital twin using machine learning algorithms. A systematic failure detection approach based on decision trees and the process of analysing the quality of the result is described.
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Badawi, Hawazin Faiz. "DT-DNA: Devising a DNA Paradigm for Modeling Health Digital Twins." Thesis, Université d'Ottawa / University of Ottawa, 2021. http://hdl.handle.net/10393/41906.
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The potential of Digital twin (DT) technology outside of the industrial field has been recognized by researchers who have promoted the vision of applying DTs technology beyond manufacturing, to purposes such as enhancing human well-being and improving quality of life (QoL). The expanded definition of DTs to incorporate living and nonliving physical entities into the definition of DTs was a key motivation behind the model introduced in this thesis for building health digital twins of citizens. In contrast with DTs that have been developed in more industrial fields, this type of digital twins modeling necessitates protecting each citizen's unique identity while also representing features common to all citizens in a unified way. In nature, DNA is an example of a model that is both unified, common to all humans, and unique, distinguishing each human as an individual. DNA’s architecture is what inspired us to propose a digital twin DNA (DT-DNA) model as the basis for building health DTs for citizens. A review of the literature shows that no unified model for citizens’ health has been developed that can act as a base for building digital twins of citizens while also protecting their unique identity thus we aim to fill this gap in this research. Accordingly, in this thesis, we proposed a DT-DNA model, which is specifically designed to protect the unique identity of each citizen’s digital twin, similar to what DNA does for each human. We also proposed a DT-DNA-based framework to build standardized health digital twins of citizens on micro, meso and macro levels using two ISO standards: ISO/IEEE 11073 (X73) and ISO 37120. To achieve our goal, we started by analyzing the biological DNA model and the influencing factors shaping health in smart cities. The purpose of the first is to highlight the DNA model features which provide the building blocks for our DT-DNA model. The purpose of the latter is to determine the main bases of our DT-DNA model of health DTs. Based on the analysis results; we proposed DT-DNA to model health DTs for citizens. In keeping with our DNA analogy, we have identified four bases, A, T, G, and C, for our unified and unique DT-DNA model. The A base in the proposed model represents a citizen’s anthropometric when we build the DT-DNA on an individual level and represents the city’s regulatory authorities when we build the DT-DNA on community and city levels. The T base represents different tasks included in the provided health data that are required to model citizens’ health DT-DNA on different levels. The G base represents the geographic and temporal information of the city, where the citizen exists at the time of data collection. The C base represents the context at the time of data collection. To proof the concept, we present our initial work on building health DTs for citizens in four case studies. The first two case studies are dedicated for health DTs at the micro level, the third case study is dedicated for health DTs at the meso level and the fourth case study is dedicated for health DTs at the macro level. In addition, we developed an algorithm to compare cities in terms of their community fitness and health services status. The four case studies provide promising results in terms of applicability of the proposed DT-DNA model and framework in handling the health data of citizens, communities and cities, collected through various sources, and presenting them in a standardized, unique model.
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Kovacevic, Nedim, Jantje Meinzer, and Rainer Stark. "Nutzerzentrierte Entwicklung einer ortsunabhängigen Maschinenabnahme mittels Augmented Reality." Thelem Universitätsverlag & Buchhandlung GmbH & Co. KG, 2021. https://tud.qucosa.de/id/qucosa%3A75883.
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Die Nutzung von Augmented Reality (AR) stellt eine Vielzahl von Lösungsansätzen für Herausforderungen unterschiedlicher Bereiche, z.B. der Industrie, Medizin, Unterhaltungsmedien und Bildung, zur Verfügung. Speziell werden hier die Möglichkeiten von AR in der Fertigungsindustrie, genauer bei der Abnahme elektrischer Antriebe der Siemens AG, betrachtet. Dabei werden unter anderem messbare Größen wie Drehmoment, Ankerstrom, -spannung, Drehzahl, Schwingungen, Fertigungstoleranzen etc. gemessen, aber auch nicht quantifizierbare Größen wie Sichtprüfungen von Schweißnähten und Lackierung in Betracht gezogen. Angestrebt wird eine Methode, welche es zukünftig ermöglicht, die Inbetriebnahme ortsunabhängig zu verfolgen und Inspektionen aus der Ferne durchzuführen. Die Herausforderung liegt dabei darin, eine zumindest gleichwertige, wenn nicht sogar verbesserte Erfahrung und Prüfergebnisvalidität für die Beteiligten gegenüber der vor Ort Abnahme zu erzeugen. Im Rahmen des Forschungsvorhabens wurde in interdisziplinärer Zusammenarbeit zwischen Ingenieur/-innen und Sozialwissenschaftler/-innen ein Demonstrator-Konzept für eine ortsunabhängige Maschinenabnahme entwickelt.
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Vavrík, Michal. "Návrh a implementace řídícího programu pro CNC obráběcí stroj prostřednictvím B&R Automation." Master's thesis, Vysoké učení technické v Brně. Fakulta strojního inženýrství, 2020. http://www.nusl.cz/ntk/nusl-416642.
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The aim of the diploma thesis is the robotization of a conventional milling machine to a CNC milling machine using a programmable logic controller. The theoretical part of the thesis contains a description of machine tools and industry 4.0, an overview of Optimum Maschinen and B&R Automation companies, including products, and a description of the G code programming language. At the beginning of the practical part, the selected hardware, its connection and tuning of motors are described. Furthermore, the practical part explains the method of motor control and processing of CNC programs in G code. The following chapters discuss the creation of industrial visualizations for machine control and digital twin for testing purposes. The conclusion describes the evaluation of the results and indicates the possibilities for future expansion of the machine and its implementation in an automated cell in the sense of industry 4.0.
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Mravec, Roman. "Návrh mezioperační dopravy ve výrobním podniku podle principů Průmyslu 4.0." Master's thesis, Vysoké učení technické v Brně. Fakulta elektrotechniky a komunikačních technologií, 2021. http://www.nusl.cz/ntk/nusl-449286.
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Based on the description and definition of technology and processes falling within the vision of the fourth industrial revolution with the aim of creating intelligent factories, this diploma thesis deals with the principles of the Industry 4.0 concept in Hilti's production plant with a focus on transport and supply of production equipment. The aim of the work is to create a comprehensive proposal that takes into account all the necessary aspects associated with upgrading the existing state of inter-operational transport in a particular production line to fully automated, flexible and autonomous transport of materials and products in the context of Industry 4.0. A prerequisite for creating a design is the connection of automatically guided vehicles (AGVs) serving individual transport orders. The selection of the vehicle was made taking into account the safety of movement, the method of charging, the system and network integrity of existing and proposed technologies and components. The intention is not only to automate the inter-operational service, but also on the basis of the created automation concept, the ability to autonomously procure the flow of material and products. The mathematical calculation of capacity planning in the production line helped to determine the total load and the number of vehicles needed for continuous procurement of transport requirements. The result of the design part is also the design of specific transport routes and transport conditions that AGV vehicles must comply with in order to maintain a high level of safety. Transparency and a constant overview of transported products is provided by the presented scheme for identification of production batches, Auto-ID system. The financial efficiency of the whole project elaborated in the diploma thesis is evaluated as payable after 4 years from the implementation of the proposal. The financial efficiency of the whole project elaborated in the diploma thesis is evaluated as payable after 4 years from the implementation of the proposal due to high labor costs.
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Cih-JyuanWu and 吳慈娟. "CNC Tool Signal Prediction for Machine Health Monitor with Upper-Lower Boundaries Using Twin-Task Convolutional Neural Networks." Thesis, 2019. http://ndltd.ncl.edu.tw/handle/3z2hhz.
Full textAbstract:
碩士國立成功大學
資訊工程學系
107
In the Machine Health Monitoring System, how to judge whether the mechanical operation is normal is a common and important issue. When machining, the processing signal of the tool or machine is collected by the sensor, and this signal is used to judge whether the processing is abnormal or predict when an anomaly will occur. Traditional physical-based models or machine learning methods have problems such as requiring a large number of manual labels, training or testing for a long time, unsuitable for processing large amounts of data, high cost of labeling, or unable to process the data without fault case. In order to solve the above problems, we propose a framework for predicting CNC tool signal, which consists of three parts. The first part is the signal pre-processing that can accelerate the training networks. The second part is the Twin-Task Convolutional Neural Networks that can accurately predict the tool signals. The third part is to predict the upper and lower bounds, and we use this upper and lower bounds as a warning reference. In this framework, not only does it not require manual labeling, but the time of training networks takes only about 13 minutes. In addition, in the Twin-Task Convolutional Neural Networks, we finally use a two-dimensional convolutional layers, which can effectively improve the accuracy of predictions compared with the one-dimensional convolutional layers.
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Lai, Kuan-Chuan, and 賴冠銓. "A Study on the Digital Model Constructing Technology of Feed Drive System in Machine Tool." Thesis, 2016. http://ndltd.ncl.edu.tw/handle/70819879604716416068.
Full textAbstract:
碩士國立中興大學
機械工程學系所
104
Taiwan’s Machine tool has been to mature, but most of manufactures always depend on experience to develop new product. However, it will spend a lot of costs. In order to reduce development costs that we can be use of CAE technology. Although this technology has matured, but the companies have not effectively useful this technology. In this paper combines ANSYS with RecurDyn and control systems to construct the digital model of feed drive system. This model can be effective analysis moving path and the forces from platform. This paper integrates CAE technology. First constructs the ANSYS finite element model from percussion test with a machine tool, then constructs the dynamic model with RecurDyn and combines with control loop model. Through the finite element model’s frequency error has about 1% to 2%. The single axial current close loop has be useful to show the trend for friction effect. The single axial close loop has show the trend feed drive’s max acceleration within 5%. Through the circular test cans be useful to show the trend for the peak. This digital model system is feasible and it has development in the future. Because we can understand this machine’s sports and the forces, and developed machines that can effectively reduce the development costs.
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Li, Chang-Yi, and 李昶毅. "A Study on the Digital Model Constructing Technology of High Speed Spindle in Machine Tool." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/73798906955418300620.
Full textAbstract:
碩士國立中興大學
機械工程學系所
105
Taiwan’s machine tool industry is flourishing and famous for cost-effective in the world. In the past, developing machine tool often relied on trial and error method or just improving old products. Therefore, it is difficult to control the performance of new products. With the improvement of computer technology, applications of Computer-Aid-Engineering have been used widely. Therefore, the static and dynamic characteristics of the machine tool before it manufactured can be predicted by using the computer simulation technology. Spindle, one of the key components of machine tool, has very strong effect on the processing quality. Therefore, to estimate the static and dynamic characteristics of spindle by digital modeling for machine tool is very important. Parameters which will influence the spindle performance include the stiffness and damping of the bearing, the joint of tool-holder, and between the parts. In this paper, we used high-speed milling spindle as a platform to construct the finite element model and verified by modal testing to establish a reliable digital spindle model. It can predict the static and dynamic characteristics of different design parameters.
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(7046756), Jeff Fiechter. "DEVELOPMENT AND DEPLOYMENT OF A FIELD BASED SOIL MAPPING TOOL USING A COMPARATIVE EVALUATION OF GEOSTATISTICS AND MACHINE LEARNING." Thesis, 2019.
Find full textAbstract:
Soil property variability is a large component of the overall environmental variability that Precision Agriculture practices seek to address. Thus, the creation of accurate field soil maps from field soil samples is of utmost importance to practitioners of Precision Agriculture, as understanding and characterizing variability is the first step in addressing it. Today, growers often interpolate their soil maps in a “black-box” fashion, and there is a need for an easy to use, accurate method of interpolation. In this study, current interpolation practices are examined as a benchmark, a Random Forest (RF) based prediction framework utilizes public data to aid predictions, and the RF framework is exposed via a webtool. A high density (0.20 ha/sample) field soil sample dataset provides 28 training points and 82 validation points to be used as a case study. In the prediction of soil percent organic matter (OM), the grid and ordinary kriging interpolations both had higher Mean Absolute Error (MAE) scores than a field average prediction, though the difference was not statistically significant at a 5\% confidence level. A RF framework interpolation utilizing a high resolution (1.52 m) DEM and distances to known points as the feature set had a significantly lower MAE score than the field average, grid, and ordinary kriging interpolations. The results suggest that for the study site, RF framework performed better compared to a field average, a grid based, and an ordinary kriging interpolation methods.
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CHEN-SHAN, YANG, and 楊金山. "A Study onIntegrating the Concept of Culture and Creativity into Digital Media Marketing - Taking 3D Simulation of Machine Tool as an Example." Thesis, 2017. http://ndltd.ncl.edu.tw/handle/24p9k9.
Full textAbstract:
碩士國立勤益科技大學
文化創意事業系
105
Cultural creativity is a comprehensive new discipline of the current development in Taiwan. Most of the relevant research is focused on sightseeing factories, commodity development, and brand management, etc. There is little research on how to use the concept of cultural innovation in industrial products. Therefore, this special choice of machine tool industry as the research object is according to the current national industrial policy and the trend of global wisdom manufacturing,. This study is toattempt to apply the concept of cultural creativity in the marketing of machine tool product, which can create a new image of the product, so that the machine tool is not only on behalf of low-tech and high labor industrial projects, but to present the new era of technology-based wisdom manufacturing industry. Therefore, this study will discuss the following aspects from the machine tool marketing point of view: First of all, is to sort out the domestic machine tool industrial development process and the marketing methods; secondly, is to discuss the industrial marketing trends and needs; and thirdly, is to discuss how to combine the machine tool products with the media related marketing as well. As the rapid development of cloud communications technology, the current media transmission has also undergone a major innovation. The influence of new media on internet technologyhas gradually increased, which can be seen from the 2016 United States presidential election. Therefore, the part of the study will be focused on the new media, and sort out the relevant characteristics, then import the machine tool products, and ultimately put forward the machine tool marketing method. In the performance of the content, this study will use the way of animation simulation, and planning the following items: (1) processing action simulation; (2) stand-alone introduction; (3) production; (4) production process, and so on.In addition to the 3D simulation of the machine tool, this study will use machine tool as the theme of the design, and try to make the machine tool products and manufacturers have the impression link, and then create a good brand image. Finally, this study will summarize the following advantages of the tooling machine through digital media marketing: (1) Repeatability - digital images can be replayed, can be used with the global exhibition of machine tools;(2) Impression and easy interpretation - through the screen and with the instructions, can clearly understand the content and deepen the impression; (3) High profile and free from time and place restrictions - through the audio and video platform and network connection, to provide content that can be obtained at any time.And its production results can be used for the network community platform and a variety of mobile devices to send, to meet the needs of digital marketing.
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Lourenço, Luís Carlos Guimarães. "Big data analytics for intra-logistics process planning in the automotive sector." Master's thesis, 2020. http://hdl.handle.net/10362/106551.
Full textAbstract:
The manufacturing sector is facing an important stage with Industry 4.0. This paradigm
shift impulses companies to embrace innovative technologies and to pursuit near-zero
fault, near real-time reactivity, better traceability, and more predictability, while working
to achieve cheaper product customization.
The scenario presented addresses multiple intra-logistic processes of the automotive factory
Volkswagen Autoeuropa, where different situations need to be addressed. The main
obstacle is the absence of harmonized and integrated data flows between all stages of the
intra-logistic process which leads to inefficiencies. The existence of data silos is heavily
contributing to this situation, which makes the planning of intra-logistics processes a
challenge.
The objective of the work presented here, is to integrate big data and machine learning
technologies over data generated by the several manufacturing systems present, and
thus support the management and optimisation of warehouse, parts transportation, sequencing
and point-of-fit areas. This will support the creation of a digital twin of the
intra-logistics processes. Still, the end goal is to employ deep learning techniques to
achieve predictive capabilities, all together with simulation, in order to optimize processes
planning and equipment efficiency.
The work presented on this thesis, is aligned with the European project BOOST 4.0, with
the objective to drive big data technologies in manufacturing domain, focusing on the
automotive use-case.