Metall- und Maschinenbauunternehmen müssen im Durchschnitt pro Jahr ca. zwei Prozent ihres Umsatzes für Strom und Erdgas ausgeben und die Unternehmer gehen von weiteren Preissteigerungen aus. Damit rückt das Thema Energieeinsparung stärker denn je in den Fokus und wird zu einem strategischen Faktor. Um Kosten zu sparen und Wettbewerbsvorteile zu sichern, ist es notwendig, zielgenaue Energieeinsparmaßnahmen einzuleiten. Die ersten Maßnahmen, welche die meisten Maschinenbauunternehmen umsetzen, sind die Erneuerung der Beleuchtungs-, Heizungs- und Lüftungsanlage, die Verbesserung der Drucklufterzeugung sowie die thematische Sensibilisierung der Mitarbeiter. Aber auch in Maschinen mit ihren dazugehörigen elektrischen Antrieben, Lüftern und Aggregaten verbirgt sich eine große Menge an Optimierungspotenzial. Allerdings ist es hier notwendig nicht die Verbraucher im Einzelnen, sondern die Maschine und deren Prozesse im Ganzen zu betrachten. Meist fehlen hierfür aber geeignete Schnittstellen, um die Messwerte von Sensoren (bspw. Temperatur-, Drucksensoren, etc.) und Antrieben auslesen zu können, was dazu führt, dass diese Potenziale nicht ausgeschöpft werden.

The average metal and mechanical engineering company must spend around two per cent of its annual turnover on electricity and natural gas, and companies are expecting further price increases. As a result, the issue of energy saving is becoming more of a strategic factor than ever before. In order to save costs and ensure competitive advantages, it is necessary to introduce precise energy-saving measures. The first steps taken by most mechanical engineering companies are to replace lighting, heating, and ventilation systems, improve compressed air generation and raise employee awareness. However, there is also a great potential for optimization in machines with their individual electrical drives, fans, and units. In this case, though, it is necessary to look at the machine and its processes as a whole rather than the individual electrical energy consumers. In most cases, however, there is a lack of suitable interfaces for analyzing the measured values from sensors (e.g. temperature, pressure sensors, etc.) and drives, which concludes that this potential is not fully exploited.

<p dir="ltr">The present work expands the state of the art in the design of soft actuators and flexible sensors manufactured through fused deposition modelling (FDM) and direct ink writing (DIW). The first design consisted of flexible sensors for rehabilitation. Three different designs were tested and compared according to their sensitivity and accuracy. The flexible sensor successfully responded to deformation by changing its resistance. The first design of soft actuator was the Closed Dual Pneumatic Bellow Actuator. The soft actuator was manufactured using FDM and included an inner chamber in which the input air flows through and produces the actuation. The actuator also included dielectric electroactive polymer (DEAP) that showed response to pressure between the actuator and the object to be grasped. The electrodes of the DEAP were manufactured using commercial conductive TPU. A second soft actuator was designed with a circular shape and embedded DEAP. The electrodes in the DEAP consisted of conductive carbon grease. Previous tests were performed to assess the functionality of a DEAP structure using conductive carbon grease. The DEAP showed an increase in capacitance as pressure was applied on one side of the structure parallel to the electrodes and computational simulations validated such response. Future work using the sensors and actuators presented includes the implementation of a closed-loop system to the soft actuators, using the readouts of the sensors to adjust the input pressure and apply precise pressure on objects. The flexible sensor for rehabilitation has the potential to be implemented in each of the fingers of the hand and use the data to characterize the movement of the hand under different configurations providing feedback to patients in task-oriented therapy.</p>

Winter road maintenance is a necessity during the winter in Sweden, since the weather reduce traffic safety and accessibility, which have great impact on people and society in general. Unlike the degradation process of paved road surface and subgrade, that develops slowly over several years, the general state of the winter road can change significantly within a couple of hours, thus demanding more of road maintenance organisations when it comes to planning and initiating maintenance actions. Today there is a wide range of available sensor technology, that can be utilized to monitor the condition of the winter road and provide decision makers with the required information to initiate maintenance activities at the right time. However, it is necessary for the user, e.g. maintenance staff and decision makers, to know how this type of technology can be applied to make the winter road maintenance more efficient. The aim of this thesis is to define the winter road maintenance process, what obstacles and problems are present and the information requirements that are associated with planning, initiating and performing the winter road maintenance activities. The thesis focuses on the maintenance process for municipalities in northern Sweden using the city of Kiruna as a case study. An interview study was performed at Tekniska Verken in Kiruna to collect empirical data, which forms the basis for the process- and flow charts that are presented in the result. Common failure modes, connected to the failures that usually leads to the initiation of a maintenance activity, are identified, based on the interviews and the quality declaration for winter road maintenance. The failure modes were connected to the workflows, to show the phases of the workflow where the information is useful. Based on this, suitable sensor technology is proposed, which partly or fully meet the identified information requirements, and monitors the interesting failure modes of each maintenance activity. The results show that the greatest need for information is found in the stage of assessment and decision-making regarding initiation of maintenance actions, especially when it comes to initiation of snow plowing and de-icing activities. Using vehicle-based sensor technology, the condition of the road can be continuously monitored, and the initiation of maintenance activities can be triggered when reaching a threshold. Having road weather information stations, e.g. monitoring air and road temperature, wind speed, precipitation and road condition, is also an important source of information for municipal winter road maintenance. The use of sensor technology results in maintenance processes with fewer activities and decision steps, and it generates more reliable data that simplifies the decision-making. / Vinterväghållning är en nödvändighet under vinterhalvåret i Sverige, då väderlek har en stor påverkan på trafiksäkerhet och framkomlighet för trafikanter. Till skillnad från nedbrytningen av belagd väg under barmarkssäsongen, som sker stegvis under flera år, kan vintervägens tillstånd försämras avsevärt inom bara ett par timmar. Detta ställer högre krav på vägunderhållsorganisationer vad gäller planering och initiering av underhållsåtgärder. Idag finns ett brett utbud av sensorteknik som kan användas för att övervaka vintervägens tillstånd, och förse beslutsfattare med nödvändig information för att kunna initiera underhållsaktiviteter vid rätt tidpunkt. Det är dock nödvändigt att användaren, dvs. underhållspersonal och beslutsfattare, har kunskap om hur denna teknik kan användas för att effektivisera vinterväghållningen. Syftet med arbetet är att ta reda på hur underhållsprocessen för kommunal vinterväghållning är utformad, vilka hinder och problem som förekommer samt vilket informationsbehov som finns i samband med planering, initiering och utförande av vinterväghållningsaktiviteter. Arbetet är avgränsat till att analysera vinterväghållningen i Kiruna kommun. En intervjustudie utfördes vid Tekniska Verken i Kiruna för insamling av empiriskt material, vilket utgjorde underlaget för de process- och flödeskartor som presenteras i resultatet. Med utgångspunkt ur intervjumaterialet och kommunens kvalitetsdeklaration för vinterväghållning, identifierades vanliga felmoder kopplade till de funktionsfel som leder till initiering av underhållsaktivitet. Felmoderna kopplades sedan till arbetsflödena, genom att visa i vilket skede i arbetet som information om dessa är användbar. Utifrån detta gavs förslag på lämplig sensorteknik som helt eller delvis kan tillgodose informationsbehovet som identifierats, samt övervaka de felmoder som är intressanta för respektive underhållsaktivitet. Resultatet av undersökningen visar att det är vid bedömning och beslut om initiering av underhållsåtgärd som informationsbehovet är störst, framför allt när det handlar om initiering av snöröjning och halkbekämpning. Genom att använda sensorteknik för kontinuerlig övervakning av vägens tillstånd, kan underhållsaktiviteter initieras vid definierade gränsvärden. Egna vägväderstationer som övervakar och mäter exempelvis luft- och vägtemperatur, vindstyrka, nederbördsmängd och typ samt väglag, kan vara till nytta för den kommunala vinterväghållningen oavsett vilken underhållsaktivitet det handlar om. Användningen av denna typ av teknik leder till effektiviserade underhållsprocesser med färre aktiviteter och beslutssteg, samt förenklad beslutsfattning baserat på mer tillförlitliga mätdata.

<div> <div> <div> <p> </p><div> <div> <div> <div> <div> <div> <p> </p><div> <div> <div> <p>Two-dimensional (2D) transition-metal dichalcogenides (TMDCs) and transition metal carbides/nitrides (MXenes), have been recently receiving attention for gas sensing applications due to their high specific area and rich surface functionalities. However, using pristine 2D materials for gas-sensing applications presents some drawbacks, including high operation temperatures, low gas response, and poor selectivity, limiting their practical sensing applications. Moreover, one of the long-standing challenges of MXenes is their poor stability against hydration and oxidation in a humid environment, which negatively influences their long- term storage and applications. Many studies have reported that the sensitivity and selectivity of 2D materials can be improved by surface functionalization and hybridization with other materials.</p><p>In this work, the effects of surface functionalization and/or hybridization of these two materials classes (TMDCs and MXenes) on their gas sensing performance have been investigated. In one of the lines of research, 2D MoS2 nanoflakes were functionalized with Au nanoparticles as a sensing material, providing a performance enhancement towards sensing of volatile organic compounds (VOCs) at room temperature. Next, a nanocomposite film composed of exfoliated MoS2, single-walled carbon nanotubes, and Cu(I)−tris(mercaptoimidazolyl)borate complexes was the sensing material used for the design of a chemiresistive sensor for the selective detection of ethylene (C2H4). Moreover, the hybridization of MXene (Ti3C2Tx) and TMDC (WSe2) as gas-sensing materials was also proposed. The Ti3C2Tx/WSe2 hybrid sensor reveals high sensitivity, good selectivity, low noise level, and ultrafast response/recovery times for the detection of various VOCs. Lastly, we demonstrated a surface functionalization strategy for Ti3C2Tx with fluoroalkylsilane (FOTS) molecules, providing a superhydrophobic surface, mechanical/environmental stability, and excellent sensing performance. The strategies presented here can be an effective solution for not only improving materials' stability, but also enhancing sensor performance, shedding light on the development of next-generation field-deployable sensors.</p> </div> </div> </div><div><div><div><div><div><div> </div> </div> </div> </div> </div> </div></div></div></div> </div> </div> </div></div></div></div><div><div><div> </div> </div> </div>

The rise of batteries in the industry, especially Li-ion, is increasing rapidly. Li-ion battery systems are traditionally composed of a particular type of cell chemistry fit to the system needs. Due to the significant differences between chemistries, different cells have different attributes. The thesis explores the potential of a heterogeneous solution to include different cells to find a suitable compromise between different attributes. An electrified passenger train using a homogenous solution was evaluated against a heterogeneous solution consisting of two cell types, NMC and LTO, which have significant differences in attributes.  Simulation with models covering the train kinematics, track characteristics, and battery behaviour generates the thesis results. Validation of simulation results includes comparing previous simulations and the new effects of the heterogeneous solution, which indicate a good fit. Verification of the results encompasses a small-scale experiment with a custom-made physical circuit to observe the proposed solution's actual behaviour and verify model validity, which implies the correctness of models and implementation. The results indicate that a heterogeneous solution is possible within the scope of electrified trains. Furthermore, several trade-offs exist between NMC and LTO cells, especially regarding rate capability, safety and capacity, which confirms the potential of heterogeneous battery systems.

Sverige har som många länder runt om i världen en åldrande infrastruktur och behovet av underhåll stiger. I en artikel i Svenska Dagbladet från 21/9–2018 redovisar analys- och teknikkonsultföretaget WSP en grov uppskattning att 300 miljarder kronor behöver investeras för att rusta upp existerande infrastruktur. Efter upprustningen skulle det krävas ca 25 miljarder kronor årligen för att utföra löpande tillståndsbedömning och underhåll av Sveriges väg- och järnvägsnät. Idag används inspektioner för att bedöma broars tillstånd. Det finns tre olika inspektionstyper; huvudinspektion, allmäninspektion och särskild inspektion. Structural Health Monitoring (SHM) är en teknik som globalt används mer och mer som en metod vid tillståndsbedömning av broar. SHM siktar mot att i realtid utföra automatisk bedömning av hela konstruktionens och de enskilda skadornas tillstånd. SHM använder sig av sensorer placerade på kritiska positioner för att samla in mätdata som jämförs med i förtid definierade gränsvärden. I Sverige används SHM sparsamt idag där kunskapen ligger på akademisk nivå och det råder en osäkerhet om hur SHM ska implementeras i praktiken. Genom att implementera SHM, kan skador upptäckas i ett tidigt skede och minimeras genom att snabbt utföra reparationer på konstruktionen innan skadorna blivit kritiska. Studien syftar till att producera en rapport som kan användas som en guide för hur SHM kan implementeras samt visa på hur SHM-systemen har implementerats på tidigare projekt. Rapporten skall ge läsaren en helhetsbild över hur tillståndsbedömning går till idag, vilka skador som är vanligt förekommande samt hur SHM kan användas som ett verktyg vid tillståndsbedömning. Rapporten syftar också till att ge en övergripande förklaring på svenska av SHM-tekniken och vad som behövs för implementering. Öppna ostrukturerade intervjuer genomfördes med forskare inom SHM och skador på betongkonstruktioner samt sakkunniga inom tillståndsbedömning. Intervjuerna användes som utgångspunkt för vidare studier av vanligt förekommande skador och SHM-tekniker. I litteraturstudien användes olika vetenskapliga databaser såsom Diva och ScienceDirect, samt KTH:s bibliotek för att få fram tidigare material om betongskador på broar, deras skademekanismer och om SHM-tekniken. Vidare hämtades information från ett antal doktorsavhandlingar, artiklar och tidigare examensarbeten. Genom litteraturstudie och intervjuer med sakkunniga kom studien fram till att armeringskorrosion och sprickor i betongen är skador som är vanligt förekommande i betongbroar. Skadornas skademekanismer beskrivs i rapporten. Studien identifierade tre olika system som kan användas för detektering och övervakning av armeringskorrosion och sprickor, de systemen är akustisk emission, SOFO-system (SOFO är en förkortning för Surveillance d'Ouvrage par Fibers Optics) och MuST-system (MuST är ett kommersiellt namn). Rapporten ger exempel på hur systemen kan användas för detektering och övervakning av skadorna genom att presentera fyra fallstudier där systemen har använts. Två av fallstudierna presenterar hur akustisk emission har implementeras och två av fallstudierna presenterar hur SOFO-systemet har implementerats. Studien kunde inte identifiera någon fallstudie för MuST-systemet och hur systemet har implementerats. Slutsatsen av studien är att SHM kan användas som ett komplement vid tillståndsbedömningar men man kan inte utföra automatiserade tillståndsbedömningar idag. / Like many countries around the world, Sweden has an aging infrastructure and the need for maintenance is increasing. In an article in Svenska Dagbladet from 21 / 9–2018, the analysis and engineering consulting company WSP reports a rough estimate that SEK 300 billion needs to be invested to upgrade existing infrastructure. After the upgrade, it would require approximately SEK 25 billion annually to carry out ongoing condition assessment and maintenance of Sweden's road and railway networks. Today, inspections are used to assess the condition of bridges. There are three types of inspection; main inspection, general inspection and special inspection. Structural Health Monitoring (SHM) is a technology that is globally more used as a method for condition assessment of bridges. SHM aims to perform automatic assessment of the state of the entire construction and individual damages in real time. SHM uses sensors placed at critical positions to collect measurement data compared to pre-defined limit values. In Sweden, SHM is used sparingly today, where knowledge is at an academic level and there is uncertainty about how SHM should be implemented in practice. By implementing SHM, damage can be detected at an early stage and minimized by quickly performing repairs on the design before the damage becomes critical. The study aims to produce a report that can be used as a guide on how SHM can be implemented and show how the SHM systems have been implemented on previous projects. The report should give the reader an overall picture of how condition assessment is performed today, which damages are common and how SHM can be used as a tool when assessing the condition. The report also aims to provide an overall explanation in Swedish of the SHM technology and what is needed for implementation. Open unstructured interviews were conducted with researchers within SHM and damages to concrete structures as well as experts in condition assessment. The interviews were used as a starting point for further studies of commonly occurring damages and SHM techniques. In the literature study, various scientific databases were used, such as Diva and ScienceDirect, as well as KTH's library to obtain earlier material on concrete damage to bridges, its damage mechanisms and about SHM technology. Furthermore, information was obtained from a number of doctoral dissertations, articles and previous degree projects. Through literature study and interviews with experts, the study concluded that reinforcement corrosion and cracks in the concrete are damages that are commonly found in concrete bridges. The damage mechanisms are described in the report. The study identified three different systems that can be used for detection and monitoring of reinforcement corrosion and cracks, those systems are acoustic emission, SOFO system (SOFO is an abbreviation for Surveillance d'Ouvrage pair of Fiber's Optics) and MuST system (MuST is a commercial name). The report gives examples of how the systems can be used for the detection and monitoring of the damages by presenting four case studies where the systems have been used. Two of the case studies present how acoustic emission has been implemented and two of the case studies present how the SOFO-system has been implemented. The study could not identify any case study for the MuST-system and how the system was implemented. The conclusion of the study is that SHM can be used as a supplement to condition assessments but cannot for the time being used for performing automated condition assessments today.

<p>Canines can detect different diseases simply by smelling different biological sample types, including  urine,  breath  and  sweat.  This  has  led  researchers  to  try  and  discovery  unique  volatile  organic compound (VOC) biomarkers. The power of VOC biomarkers lies in the fact that one day they may be able to be utilized for noninvasive, rapid and accurate diagnostics at a point of care using  miniaturized  biosensors.  However,  the  identity  of  the  specific  VOC  biomarkers  must  be  demonstrated before designing and fabricating sensing systems. Through  an  extensive  series  of  experiments,  VOCs  in  urine  are  profiled  by  solid  phase  microextraction (SPME) coupled to gas chromatography-mass spectrometry (GC-MS) to identify biomarkers for breast cancer using murine models. The results from these experiments indicated that  unique  classes  of  urinary  VOCs,  primarily  terpene/terpenoids  and  carbonyls,  are  potential  biomarkers  of  breast  cancer.  Through  implementing  chemometric  approaches,  unique  panels  of  VOCs  were  identified  for  breast  cancer  detection,  identifying  tumor  location,  determining  the  efficacy of dopaminergic antitumor treatments, and tracking cancer progression. Other diseases, including COVID-19 and hypoglycemia (low blood sugar) were also probed to identify volatile biomarkers present in breath samples.  VOC biomarker identification is an important step toward developing portable gas sensors, but  another  hurdle  that  exists  is  that  current  sensors  lack  selectivity  toward  specific  VOCs  of  interest.  Furthermore,  testing  sensors  for  sensitivity  and  selectivity  is  an  extensive  process  as  VOCs  must  be  tested  individually  because  the  sensors  do  not  have  modes  of  chromatographic  separation or compound identification. Another set of experiments is presented to demonstrate that SPME  fibers  can  be  coated  with  materials,  used  to  extract  standard  solutions  of  VOCs,  and  analyzed  by  GC-MS  to  determine  the  performance  of  various  gas  sensing  layers.  In  the  first  of  these  experiments,  polyetherimide  (PEI)  was  coated  onto  a  SPME  fiber  and  compared  to  commercial polyacrylate (PAA) fibers. The second experiment tuned the extraction efficiency of polyvinylidene fluoride (PVDF) - carbon black (CB) composites and showed that they had higher sensitivity  for  urinary  VOC  extraction  relative  to  a  polydimethylsiloxane  (PDMS)  SPME  fiber.  These results demonstrate SPME GC-MS can rapidly characterize and tune the VOC adsorption capabilities of gas sensing layers. </p>

This thesis aims to investigate a digital, emerging business model, which just enjoys the highest attention in many industrial sectors. The industry 4.0 changes how original equipment manufacturers (OEMs) retain their competitiveness and offer innovative solutions to their customers. Therefore, this master thesis investigates the diverse opportunities of usage-based business models – namely Pay-per-X / Equipment-as-a-Service – from the perspective of a sensor-tech start-up. The company, which can act as a technical enabler for Pay-per-X, is located in Germany and has various markets leading machine and component manufacturers as customers. This projects’ goal is to get an in-depth understanding of the business model and how the company (with their technology) can participate in the market, which is estimated to have a size of 131.2m USD in 2025. Therefore, mainly qualitative research methods have been applied – however, quantitative sections enrich the analysis part of the thesis. Nine expert interviews were conducted, and a calculation tool was developed, which aims to easily convince OEMs of the new business models through modeling a business case, by incorporation of the most relevant parameters. Two use cases were analyzed in the fields of production machines and commercial vehicles. This is followed by a short excursus to a required Pay-per-X cloud software, where requirements were defined based on machine users’ needs. Based on these insights, a positioning strategy for the case company within this field is proposed later-on, which puts emphasis on how the firm can act as a technical enabler for Pay-per-X business models. / Syftet med denna avhandling är att undersöka en ny digital affärsmodell som just nu får stor uppmärksamhet inom många industrisektorer. Industri 4.0 förändrar hur tillverkare av originalutrustning behåller sin konkurrenskraft och erbjuder innovativa lösningar till sina kunder. Därför undersöker denna masteruppsats de olika möjligheterna med användningsbaserade affärsmodeller - nämligen Pay-per-X / Equipment-as-a-Service - ur ett startupföretag inom sensorteknik. Företaget, som kan fungera som en teknisk möjliggörare för Pay-per-X, är beläget i Tyskland och har olika marknadsledande maskin- och komponenttillverkare som kunder. Projektets mål är att få en djupgående förståelse för affärsmodellen och hur företaget (med sin teknik) kan delta på marknaden, som beräknas ha en storlek på 131,2 miljoner US-dollar år 2025. Därför har huvudsakligen kvalitativa forskningsmetoder tillämpats - men kvantitativa avsnitt berikar analysdelen av avhandlingen. Nio expertintervjuer genomfördes och ett beräkningsverktyg utvecklades, som syftar till att enkelt övertyga OEMs om de nya affärsmodellerna genom att modellera ett affärscase, genom att införliva de mest relevanta parametrarna. Två användningsfall analyserades inom områdena produktionsmaskiner och kommersiella fordon. Detta följs av en kort utflykt till en nödvändig Pay-per-X-molnmjukvara, där kraven definierades utifrån maskinanvändarnas behov. På grundval av dessa insikter föreslås senare en positioneringsstrategi för fallföretaget inom detta område, som lägger tonvikten på hur företaget kan fungera som en teknisk möjliggörare för Pay-per-X-affärsmodeller.

<p>  This paper explored the application of three machine learning models focused on predictive motor maintenance. Logistic Regression, Sequential Minimal Optimization (SMO), and NaïveBayes models. A comparative analysis of these models illustrated that while each had an accuracy greater than 95% in this study, the Logistic Regression Model exhibited the most reliable operation.</p>