A facilities maintenance management process based on degradation prediction using sensed data

Energy efficiency and user comfort have recently become priorities in the Facility Management (FM) sector. This has resulted in the use of innovative building components, such as thermal solar panels, heat pumps, etc., as they have potential to provide better performance, energy savings and increased user comfort. However, as the complexity of components increases, the requirement for maintenance management also increases. The standard routine for building maintenance is inspection which results in repairs or replacement when a fault is found. This routine leads to unnecessary inspections which have a cost with respect to downtime of a component and work hours. This research proposes an alternative routine: performing building maintenance at the point in time when the component is degrading and requires maintenance, thus reducing the frequency of unnecessary inspections. This thesis demonstrates that statistical techniques can be used as part of a maintenance management methodology to invoke maintenance before failure occurs. The proposed FM process is presented through a scenario utilising current Building Information Modelling (BIM) technology and innovative contractual and organisational models. This FM scenario supports a Degradation based Maintenance (DbM) scheduling methodology, implemented using two statistical techniques, Particle Filters (PFs) and Gaussian Processes (GPs). DbM consists of extracting and tracking a degradation metric for a component. Limits for the degradation metric are identified based on one of a number of proposed processes. These processes determine the limits based on the maturity of the historical information available. DbM is implemented for three case study components: a heat exchanger; a heat pump; and a set of bearings. The identified degradation points for each case study, from a PF, a GP and a hybrid (PF and GP combined) DbM implementation are assessed against known degradation points. The GP implementations are successful for all components. For the PF implementations, the results presented in this thesis find that the extracted metrics and limits identify degradation occurrences accurately for components which are in continuous operation. For components which have seasonal operational periods, the PF may wrongly identify degradation. The GP performs more robustly than the PF, but the PF, on average, results in fewer false positives. The hybrid implementations, which are a combination of GP and PF results, are successful for 2 of 3 case studies and are not affected by seasonal data. Overall, DbM is effectively applied for the three case study components. The accuracy of the implementations is dependant on the relationships modelled by the PF and GP, and on the type and quantity of data available. This novel maintenance process can improve equipment performance and reduce energy wastage from BSCs operation.

A Molecular-scale Programmable Stochastic Process Based On Resonance Energy Transfer Networks: Modeling And Applications

While molecular and cellular processes are often modeled as stochastic processes, such as Brownian motion, chemical reaction networks and gene regulatory networks, there are few attempts to program a molecular-scale process to physically implement stochastic processes. DNA has been used as a substrate for programming molecular interactions, but its applications are restricted to deterministic functions and unfavorable properties such as slow processing, thermal annealing, aqueous solvents and difficult readout limit them to proof-of-concept purposes. To date, whether there exists a molecular process that can be programmed to implement stochastic processes for practical applications remains unknown.

In this dissertation, a fully specified Resonance Energy Transfer (RET) network between chromophores is accurately fabricated via DNA self-assembly, and the exciton dynamics in the RET network physically implement a stochastic process, specifically a continuous-time Markov chain (CTMC), which has a direct mapping to the physical geometry of the chromophore network. Excited by a light source, a RET network generates random samples in the temporal domain in the form of fluorescence photons which can be detected by a photon detector. The intrinsic sampling distribution of a RET network is derived as a phase-type distribution configured by its CTMC model. The conclusion is that the exciton dynamics in a RET network implement a general and important class of stochastic processes that can be directly and accurately programmed and used for practical applications of photonics and optoelectronics. Different approaches to using RET networks exist with vast potential applications. As an entropy source that can directly generate samples from virtually arbitrary distributions, RET networks can benefit applications that rely on generating random samples such as 1) fluorescent taggants and 2) stochastic computing.

By using RET networks between chromophores to implement fluorescent taggants with temporally coded signatures, the taggant design is not constrained by resolvable dyes and has a significantly larger coding capacity than spectrally or lifetime coded fluorescent taggants. Meanwhile, the taggant detection process becomes highly efficient, and the Maximum Likelihood Estimation (MLE) based taggant identification guarantees high accuracy even with only a few hundred detected photons.

Meanwhile, RET-based sampling units (RSU) can be constructed to accelerate probabilistic algorithms for wide applications in machine learning and data analytics. Because probabilistic algorithms often rely on iteratively sampling from parameterized distributions, they can be inefficient in practice on the deterministic hardware traditional computers use, especially for high-dimensional and complex problems. As an efficient universal sampling unit, the proposed RSU can be integrated into a processor / GPU as specialized functional units or organized as a discrete accelerator to bring substantial speedups and power savings.

Delivering enhanced efficiency in the synthesis of α-diazosulfoxides by exploiting the process control enabled in flow

Continuous-flow generation of α-diazosulfoxides results in a two- to three-fold increase in yields and decreased reaction times compared to standard batch synthesis methods. These high yielding reactions are enabled by flowing through a bed of polystyrene-supported base (PS-DBU or PS-NMe2) with highly controlled residence times. This engineered solution allows the α-diazosulfoxides to be rapidly synthesized while limiting exposure of the products to basic reaction conditions, which have been found to cause rapid decomposition. In addition to improved yields, this work has the added advantage of ease of processing, increased safety profile, and scale-up potential.

Development of a multivariable online monitoring system for the thermoforming process

The thermoforming industry has been relatively slow to embrace modern measurement technologies. As a result researchers have struggled to develop accurate thermoforming simulations as some of the key aspects of the process remain poorly understood. For the first time, this work reports the development of a prototype multivariable instrumentation system for use in thermoforming. The system contains sensors for plug force, plug displacement, air pressure and temperature, plug temperature, and sheet temperature. Initially, it was developed to fit the tooling on a laboratory thermoforming machine, but later its performance was validated by installing it on a similar industrial tool. Throughout its development, providing access for the various sensors and their cabling was the most challenging task. In testing, all of the sensors performed well and the data collected has given a powerful insight into the operation of the process. In particular, it has shown that both the air and plug temperatures stabilize at more than 80C during the continuous thermoforming of amorphous polyethylene terephthalate (aPET) sheet at 110C. The work also highlighted significant differences in the timing and magnitude of the cavity pressures reached in the two thermoforming machines. The prototype system has considerable potential for further development. 

Bayesian Dependence Tests for Continuous, Binary and Mixed Continuous-Binary Variables

Tests for dependence of continuous, discrete and mixed continuous-discrete variables are ubiquitous in science. The goal of this paper is to derive Bayesian alternatives to frequentist null hypothesis significance tests for dependence. In particular, we will present three Bayesian tests for dependence of binary, continuous and mixed variables. These tests are nonparametric and based on the Dirichlet Process, which allows us to use the same prior model for all of them. Therefore, the tests are “consistent” among each other, in the sense that the probabilities that variables are dependent computed with these tests are commensurable across the different types of variables being tested. By means of simulations with artificial data, we show the effectiveness of the new tests.

Continuous flow gas phase photoreforming of methanol at elevated reaction temperatures sensitised by Pt/TiO2

Gas phase photoreforming of methanol using a Pt/TiO2 photocatalyst has been performed under flow conditions at elevated temperatures. Comparing the activity of the reforming process as a function of temperature under dark and irradiated conditions shows a significant enhancement in the rate of H2 production using the photo-assisted conditions at temperatures between 100-140 °C. At higher temperatures, the effect of irradiation is small with the process dominated by the thermal process. Deactivation of the catalyst was observed under irradiation but the catalyst was easily regenerated using an oxygen treatment at 120 °C. Diffuse Reflectance Infra-red Fourier Transform Spectroscopy (DRIFTS) showed that the activity of the catalyst could be correlated with the presence of the photogenerated trapped electrons. In addition, lower amounts of CO adsorbed on Pt, compared to those observed in the dark reaction, were found for the UV-irradiated systems. It is proposed that CO and adsorbed intermediates, such as formate, can act as inhibitors in the photoreforming process and this is further supported by the observation that, before and after the regeneration process in O2, the CO and surface adsorbed organic intermediate products are removed and the activity is recovered.

Madeira wine vinification process: analysis and control

The present study was done in collaboration with J. Faria e Filhos company, a Madeira wine producer, and its main goal was to fully characterize three wines produced during 2014 harvest and identify possible improving points in the winemaking process. The winemaking process was followed during 4 weeks, being registered the amounts of grapes received, the fermentation temperatures, the time at which fermentation was stopped and evolution of must densities until the fortification time. The characterization of musts and wines was done in terms of density, total and volatile acidity, alcohol content, pH, total of polyphenol, organic acids composition, sugars concentration and the volatile profile. Also, it was developed and validated an analytical methodology to quantify the volatile fatty acids, namely using SPME-GC-MS. Briefly, the following key features were obtained for the latter methodology: linearity (R2=0.999) e high sensitivity (LOD =0.026-0.068 mg/L), suitable precision (repeatability and reproducibility lower than 8,5%) and good recoveries (103,11-119,46%). The results reveal that fermentation temperatures should be controlled in a more strictly manner, in order to ensure a better balance in proportion of some volatile compounds, namely the esters and higher alcohols and to minimize the concentration of some volatiles, namely hexanoic, octanoic and decanoic acids, that when above their odours threshold are not positive for the wine aroma. Also, regarding the moment to stop the fermentation, it was verified that it can be introduced changes which can also be benefit to guarantee the tipicity of Madeira wine bouquet.

Continuous Delivery : Utmaningar ett förvaltningsuppdrag kan stå inför vid en övergång till Continuous Delivery

Continuous delivery (CD) is a software engineering approach where the focus lays on creating a short delivery cycle by automating parts of the deployment pipeline which includes build, deploy-, test and release process. CD is based on that during development should be possible to always automatically generate a release based on the source code in its current state. One of CD's many advantages is that through continuous releases it allows you to get a quick feedback loop leading to faster and more efficient implementation of new functions, at the same time fixing errors. Although CD has many advantages, there are also several challenges a maintenance management project must manage in the transition to CD. These challenges may differ depending on the maturity level for a maintenance management project and what strengths and weaknesses the project has. Our research question was: "What challenges can a maintenance management project face in transition to Continuous delivery?" The purpose of this study is to describe Continuous delivery and the challenges a maintenance management project may face during a transition to Continuous delivery. A descriptive case study has been carried out with the data collection methods of interviews and documents. A situation analysis was created based on the collected data in a shape of a process model that represent the maintenance management projects release process. The processmodel was used as the basis of SWOT analysis and analysis by Rehn et al's Maturity Model. From these analyzes we found challenges of a maintenance management project may face in the transition to CD. The challenges are about customers and the management's attitude towards a transition to CD. But the biggest challenge is about automation of the deployment pipeline steps.

The implementation of mini-enterprise business process management.

Obviously, it is important for the mini-enterprise to acknowledgement that how to win the customers and markets, because the products must be continuously evolved so as to satisfy the customer, otherwise it will be disused by the market, that is a major problems for nowadays mini-enterprise business process management. In fact, in order to satisfy the customers, the overall business processes for mini-enterprises are mostly based on integrated business process, optimization on the integrated business process is vital for a successful min-enterprise. this paper explores how to optimize the business process of mini-enterprises based on the general principle of enterprise business process management and the main feature of the mini-enterprise, so as to instruct the mini-enterprise to control, enhance and optimize the business process in order to meet the inner requirements from the development of the enterprise and adapt itself with the continuous changes of the outside environment, most vitally it can enhance the process or re-design the process so as to meet business demands from customers.

Hydrometallurgical process modeling using advanced mathematical tools

Hydrometallurgical process modeling is the main objective of this Master’s thesis work. Three different leaching processes namely, high pressure pyrite oxidation, direct oxidation zinc concentrate (sphalerite) leaching and gold chloride leaching using rotating disc electrode (RDE) are modeled and simulated using gPROMS process simulation program in order to evaluate its model building capabilities. The leaching mechanism in each case is described in terms of a shrinking core model. The mathematical modeling carried out included process model development based on available literature, estimation of reaction kinetic parameters and assessment of the model reliability by checking the goodness fit and checking the cross correlation between the estimated parameters through the use of correlation matrices. The estimated parameter values in each case were compared with those obtained using the Modest simulation program. Further, based on the estimated reaction kinetic parameters, reactor simulation and modeling for direct oxidation zinc concentrate (sphalerite) leaching is carried out in Aspen Plus V8.6. The zinc leaching autoclave is based on Cominco reactor configuration and is modeled as a series of continuous stirred reactors (CSTRs). The sphalerite conversion is calculated and a sensitivity analysis is carried out so to determine the optimum reactor operation temperature and optimum oxygen mass flow rate. In this way, the implementation of reaction kinetic models into the process flowsheet simulation environment has been demonstrated.

Studies of turbulent flows in continuous casting of steel with and without magnetic field

This thesis develops and tests various transient and steady-state computational models such as direct numerical simulation (DNS), large eddy simulation (LES), filtered unsteady Reynolds-averaged Navier-Stokes (URANS) and steady Reynolds-averaged Navier-Stokes (RANS) with and without magnetic field to investigate turbulent flows in canonical as well as in the nozzle and mold geometries of the continuous casting process. The direct numerical simulations are first performed in channel, square and 2:1 aspect rectangular ducts to investigate the effect of magnetic field on turbulent flows. The rectangular duct is a more practical geometry for continuous casting nozzle and mold and has the option of applying magnetic field either perpendicular to broader side or shorter side. This work forms the part of a graphic processing unit (GPU) based CFD code (CU-FLOW) development for magnetohydrodynamic (MHD) turbulent flows. The DNS results revealed interesting effects of the magnetic field and its orientation on primary, secondary flows (instantaneous and mean), Reynolds stresses, turbulent kinetic energy (TKE) budgets, momentum budgets and frictional losses, besides providing DNS database for two-wall bounded square and rectangular duct MHD turbulent flows. Further, the low- and high-Reynolds number RANS models (k-ε and Reynolds stress models) are developed and tested with DNS databases for channel and square duct flows with and without magnetic field. The MHD sink terms in k- and ε-equations are implemented as proposed by Kenjereš and Hanjalić using a user defined function (UDF) in FLUENT. This work revealed varying accuracies of different RANS models at different levels. This work is useful for industry to understand the accuracies of these models, including continuous casting. After realizing the accuracy and computational cost of RANS models, the steady-state k-ε model is then combined with the particle image velocimetry (PIV) and impeller probe velocity measurements in a 1/3rd scale water model to study the flow quality coming out of the well- and mountain-bottom nozzles and the effect of stopper-rod misalignment on fluid flow. The mountain-bottom nozzle was found more prone to the longtime asymmetries and higher surface velocities. The left misalignment of stopper gave higher surface velocity on the right leading to significantly large number of vortices forming behind the nozzle on the left. Later, the transient and steady-state models such as LES, filtered URANS and steady RANS models are combined with ultrasonic Doppler velocimetry (UDV) measurements in a GaInSn model of typical continuous casting process. LES-CU-LOW is the fastest and the most accurate model owing to much finer mesh and a smaller timestep. This work provided a good understanding on the performance of these models. The behavior of instantaneous flows, Reynolds stresses and proper orthogonal decomposition (POD) analysis quantified the nozzle bottom swirl and its importance on the turbulent flow in the mold. Afterwards, the aforementioned work in GaInSn model is extended with electromagnetic braking (EMBr) to help optimize a ruler-type brake and its location for the continuous casting process. The magnetic field suppressed turbulence and promoted vortical structures with their axis aligned with the magnetic field suggesting tendency towards 2-d turbulence. The stronger magnetic field at the nozzle well and around the jet region created large scale and lower frequency flow behavior by suppressing nozzle bottom swirl and its front-back alternation. Based on this work, it is advised to avoid stronger magnetic field around jet and nozzle bottom to get more stable and less defect prone flow.

Madeira wine vinification process: analysis and control

The present study was done in collaboration with J. Faria e Filhos company, a Madeira wine producer, and its main goal was to fully characterize three wines produced during 2014 harvest and identify possible improving points in the winemaking process. The winemaking process was followed during 4 weeks, being registered the amounts of grapes received, the fermentation temperatures, the time at which fermentation was stopped and evolution of must densities until the fortification time. The characterization of musts and wines was done in terms of density, total and volatile acidity, alcohol content, pH, total of polyphenol, organic acids composition, sugars concentration and the volatile profile. Also, it was developed and validated an analytical methodology to quantify the volatile fatty acids, namely using SPME-GC-MS. Briefly, the following key features were obtained for the latter methodology: linearity (R2=0.999) e high sensitivity (LOD =0.026-0.068 mg/L), suitable precision (repeatability and reproducibility lower than 8,5%) and good recoveries (103,11-119,46%). The results reveal that fermentation temperatures should be controlled in a more strictly manner, in order to ensure a better balance in proportion of some volatile compounds, namely the esters and higher alcohols and to minimize the concentration of some volatiles, namely hexanoic, octanoic and decanoic acids, that when above their odours threshold are not positive for the wine aroma. Also, regarding the moment to stop the fermentation, it was verified that it can be introduced changes which can also be benefit to guarantee the tipicity of Madeira wine bouquet.

Thermotolerant fermenting yeasts for simultaneous saccharification fermentation of lignocellulosic biomass

Lignocellulosic biomass is the most abundant renewable source of energy that has been widely explored as second-generation biofuel feedstock. Despite more than four decades of research, the process of ethanol production from lignocellulosic (LC) biomass remains economically unfeasible. This is due to the high cost of enzymes, end-product inhibition of enzymes, and the need for cost-intensive inputs associated with a separate hydrolysis and fermentation (SHF) process. Thermotolerant yeast strains that can undergo fermentation at temperatures above 40°C are suitable alternatives for developing the simultaneous saccharification and fermentation (SSF) process to overcome the limitations of SHF. This review describes the various approaches to screen and develop thermotolerant yeasts via genetic and metabolic engineering. The advantages and limitations of SSF at high temperatures are also discussed. A critical insight into the effect of high temperatures on yeast morphology and physiology is also included. This can improve our understanding of the development of thermotolerant yeast amenable to the SSF process to make LC ethanol production commercially viable.

Analysis of competitiveness level in an industrial company using a continuous improvement based approach

International audience

Effect of nitrogen nutrition on yeast ecology and alcoholic fermentation

Mestrado Vinifera Euromaster - Instituto Superior de Agronomia - UL