Statistical process control (SPC) is a toolbox to detect changes in the output of a process distribution. It can serve as a valuable resource to maintain high quality in a manufacturing process. This report is based on the work on evaluating and implementing methods for SPC in the process of chromatography instrument manufacturing at GE Healthcare, Umeå. To handle low volume and non-normally distributed process output data, non-parametric methods are considered. Eight control charts, three for for Phase I analysis, and five for Phase II analysis, are evaluated in this study. The usability of the charts are assessed based on ease of interpretation and the performance to detect distributional changes. The later is evaluated with simulations. The result of the project is the implementation of the RS/P-chart, suggested by Capizzi et al (2013), for Phase I analysis. Of the considered Phase I methods (and simulation scenarios), the RS/P-chart has the highest overall probability, of detecting a variety of distributional changes. Further, the RS/P-chart is easily interpreted, facilitating the analysis. For Phase II analysis, the use of two control charts, one based on the Mann-Whitney U statistic, suggested by Chakraborti et al (2008), and one on the Mood test statistic for dispersion, suggested by Ghute et al (2014), have been implemented. These are chosen mainly based on the ease of interpretation. To reduce the detection time for changes in the process distribution, the change-point chart based on the Cramer Von Mises statistic, suggested by Ross et al (2012), could be used instead. Using single observations, instead of larger samples, this chart is updated more frequently. However, this efficiently increases the false alarm rate and the chart is also considered much more difficult to interpret for the SPC practitioner. / Statistisk processkontroll (SPC) är en samling verktyg för att upptäcka förändringar, i fördelningen, hos utfallen i en process. Det kan fungera som en värdefull resurs för att upprätthålla en hög kvalitet i en tillverkningsprocess. Denna rapport är baserad på arbetet med att utvärdera och implementera metoder för SPC i en monteringsprocess av kromatografiinstrument på GE Healthcare, Umeå. Åtta styrdiagram, tre för för fas I analys, och fem för fas II analys, studeras i denna rapport. Användbarheten hos styrdiagrammen bedöms efter hur enkla de är att tolka och förmågan att upptäcka fördelningsförändringar. Den senare utvärderas med simuleringar. Resultatet av projektet är införandet av RS/P-metod, utvecklad av Capizzi et al (2013), för analysen i fas I. Av de utvärderade metoderna, (och simuleringsscenarier), har RS/P-diagrammet den högsta övergripande sannolikheten, för att upptäcka en mängd olika fördelningsförändringar. Vidare är metodens grafiska diagram lätt att tolka, vilket underlättar analysen. För fas II analys, har två styrdiagram, ett baserat på Mann-Whitney's U teststatistika, som föreslagits av Chakraborti et al (2008), och ett på Mood's teststatistika för spridning, som föreslagits av Ghute et al (2014), implementerats. Styrkan i dessa styrdiagram ligger främst i dess enkla tolkning. För snabbare identifiering av processförändringar kan styrdiagrammet baserat på Cramer von Mises teststatistika, som föreslagits av Ross et al (2012), användas. Baserat på enskilda observationer, istället för stickprov, har styrdiagrammet en högre uppdateringsfrekvens. Detta leder dock till ett ökat antal falska larm och styrdiagrammet anses dessutom vara avsevärt mycket svårare att tolka för SPC-utövaren.

Large-scale processes that are modeled using differential algebraic equations based on mass and energy balance calculations at times require excessive computation time to simulate. Depending on the complexity of the model, these simulations may require many iterations to converge and in some cases they may not converge at all. Application of a storage and retrieval technique, named in situ adaptive tabulation or ISAT is proposed for faster convergence of process simulation models. Comparison with neural networks is performed, and better performance using ISAT for extrapolation is shown. In particular, the requirement of real-time dynamic simulation is discussed for operating training simulators (OTS). Integration of ISAT to a process simulator (CHEMCAD®) using the input-output data only is shown. A regression technique based on partial least squares (PLS) is suggested to approximate the sensitivity without accessing the first-principles model. Different record distribution strategies to build an ISAT database are proposed and better performance using the suggested techniques is shown for different case studies. A modified ISAT algorithm (mISAT) is described to improve the retrieval rate, and its performance is compared with the original approach in a case study. State estimation is a key requirement of many process control and monitoring strategies. Different nonlinear state estimation techniques studied in the past are discussed with their relative advantages/disadvantages. A robust state estimation technique like moving horizon estimation (MHE) has a trade-off between accuracy of state estimates and the computational cost. Implementation of MHE based ISAT is shown for faster state estimation, with an accuracy same as that of MHE. Flowsheet optimization aims to optimize an objective or cost function by changing various independent process variables, subject to design and model constraints. Depending on the nonlinearity of the process units, an optimization routine can make a number of calls for flowsheet (simulation) convergence, thereby making the computation time prohibitive. Storage and retrieval of the simulation trajectories can speed-up process optimization, which is shown using a CHEMCAD® flowsheet. Online integration of an ISAT database to solve the simulation problem along with an outer-loop consisting of the optimization routine is shown using the sequential-modular approach. / text

UAB „Baltoji juosta“ yra didžiausia kasos juostų gamybos įmonė Lietuvoje. Šiuolaikiniame verslo pasaulyje siekiant įgyti ar išlaikyti konkurencinį pranašumą yra būtina kaip įmanoma efektyviau valdyti visus įmonėje vykstančius procesus. Įmonėje esantys vėluojantys užsakymai yra veiklos neefektyvumo rodiklis, todėl jį būtina likviduoti. Pirmoje darbo dalyje buvo atlikta išorinė ir vidinė įmonės aplinkos analizė. Buvo identifikuota rinka ir aprašytos jos tendencijos. Rinkos tendencijoms nustatyti buvo naudojama Lietuvos statistikos departamento (2006) pateikta mažmeninės prekybos įmonių apyvarta (2003-2006) ir nagrinėjamos rinkos ekspertų vertinimai. Nustatyta, kad rinka yra auganti, tačiau augimo tempai mažėja. Šioje dalyje taip pat buvo atliktas rinkos segmentų išskyrimas, kuris atskleidė įmonei prioritetinius segmentus. Įmonės vidinės situacijos analizės metu buvo atlikta SWOT analizė, kuri padėjo identifikuoti vėluojančių užsakymų problemą. Antroje dalyje buvo atliekama įmonės dokumentų analizė, kurios metu buvo identifikuotos pagrindinės vėluojančių užsakymų atsiradimo priežastys – netinkamas skubių užsakymų valdymo būdas, o taip pat operatyvinės veiklos ir atsargų valdymo proceso problemos. Analizuojant duomenis buvo nustatytos atsargų valdymo proceso neefektyvumo sritys. Taip pat nustatyta, kad net 43% visų įmonės užsakymų vėluoja. Interpretuojant duomenų analizės metu gautus rezultatus buvo apibrėžtos sritys, kurioms reikalingas patobulinimas siekiant sumažinti... [toliau žr. visą tekstą] / JSC „Baltoji juosta“ is the biggest cash register rolls producer in Lithuania. In nowadays business world to gain and sustain competitive advantage you should control all company‘s processes with a highest degree of efficiency. Late orders in a company represent inefficiency and therefore they need to be vanished. In the first part of the paper company‘s internal and external environmental analysis have been done. Under external analysis the market has been identified and tendencies have been overlooked. For this analysis data from Lithuanian department of statistics about retailer‘s sales (2003-2006) was used. Together with field expert‘s comments this data leaded to findings that the market sizes of cash register rolls in Lithuania is growing, however the growth is slowing down. Also segmentation of the market was done and SWOT analysis performed. SWOT analysis helped to identify the importance of late order‘s problem. In the second part company‘s documents were analyzed. Analysis helped to identify main reasons that lead to late order‘s appearance – inappropriate management of urgent orders in the company as well as operational problems and weak inventory management system. Analyzing company‘s data weak areas of inventory system were found. Also there were calculated that overall company‘s late orders rate is 43% which is a lot. By interpreting findings of data analysis areas that require revision and improvement in order to reduce the number of late orders were identified... [to full text]

Powder mixing is an essential operation in various industrial fields, such as pharmaceuticals, agro-food, cements, etc. Continuous powder mixing, as an alternative to conventional batch mixing, has attracted a lot of interest mainly due to its capacity in handling high volume manufacturing. This work aims at the contribution to the implementation of process control applications for powder mixing in a pilot-scale continuous mixer. Prior to developing process control strategies, new developments have been presented for better understanding continuous mixing of two components. Hold-up weight and relative hold-up weight distribution of each component in the whole mixer have been experimentally investigated under different operating conditions. An improved Markov chain model has been finally presented to predict the mean concentration of the mixtures obtained at the mixer's outlet. The implementation of a proportional-integral-derivative (PID) controller has been experimentally performed as an initial attempt to real-time control the homogeneity of the mixture produced. The rotational speed of the stirrer, identified as an important deciding factor towards the mixer's efficiency, has been considered as the manipulated variable. The closed-loop control is based on either the mean concentration or the relative standard deviation. The performances of the proposed closed-loops have been evaluated for continuous mixing subjected to step changes in feed rates of the mixer. Four case studies have been defined and presented. The main challenge in the process control system is the tuning of PID parameters. The performance of closed-loop control of either the mean concentration or the relative standard deviation has been compared to open-loop operation.

Studying clathrate hydrates is, ideally, a simple task: one just have to keep water under a gas pressure. However, when trying to collect measurements in an accurate and repeatable way, things mess up. When, in particular, kinetic characterizations are required, not only pressure and temperature have to be measured: also particular parameters such as gas evolved/trapped during time, heat released/adsorbed during time, critical phenomena related to additive addition, etc, should be collected in a finer way. In the last years a growing interest has been devoted to investigations on the effects of a wide range of compounds capable to affect the thermodynamics and, in particular, kinetics of clathrate hydrate formation. The study of the effects of these compounds, called conditioners, requires an improvement of the performances of usual lab facilities by introducing a new strategy for the measurement of further characterizing parameters. Presently no standardization of the apparatus designed for clathrate hydrate studies exists, nor any commercial instrumentations are available. Generally, apparatus used are custom-made by the same research team according with the peculiar research requirements To do this we have designed, built, calibrated and tested a novel apparatus that, in addition to the ability of measuring usually unexplored parameters, is based on the idea of obtaining as many parameters as possible in a single formation batch. This in order to solve the problem of collecting a dataset that can be processed homogeneously, thus minimizing errors due stochastic behaviours. Using such an apparatus, several kinds of measurement are presented here, which are related directly to the clathrate hydrate investigation fields, but also more generally related to the study of equilibrium phases involving gaseous components.

This thesis is concerned with the sampled-data control of non-linear continuous-time systems. Sampled-data systems are present in all computer controlled, hybrid or embedded systems. The design and computation of suitable digital controllers represent unavoidable tasks since both continuous and discrete-time components interact. The basic framework of this work takes part of a wide research activity performed by S. Monaco and D. Normand-Cyrot regarding non-linear sampled-data systems. The underlying idea is to design digital controllers that recover certain continuous-time properties that are usually degraded through sampling as it is the case when continuous-time controllers are implemented by means of zero-order holder devices (emulated control). This thesis brings contributions into three different directions. The first one regards theoretical developments: a new digital backstepping-like strategy design for strict-feedback systems is proposed. This method is compared with other strategies proposed in the literature. The second contribution is the development of a control designer and of a simulation toolbox (in Matlab) for non-linear sampled-data systems. This toolbox includes different digital design strategies such as: multi-rate control, input-output/Lyapunov matching, digital backstepping design, etc. The third contribution concerns several case studies conducted to highlight the performances of the sampled-data controller designs, computed by the means of the software toolbox. Experimental and simulation results are described for various real examples especially in the area of electrical and mechanical processes.

The aeration process is often the single largest consumer of electricity in a wastewater treatment plant. Aeration in biological reactors provides microorganisms with oxygen which is required to convert ammonium to nitrate. Ammonium is toxic for aqueous ecosystems and contributes to eutrophication. The importance of aeration for the treatment results in combination with the high costs motivates automatic control of the aeration process. This thesis is devoted to ammonium feedback control in municipal wastewater treatment plants. With ammonium feedback control, the aeration intensity is changed based on a measurement of the outlet ammonium concentration. The main focus of the thesis is design, implementation, evaluation and improvement of ammonium PI (proportional-integral) controllers. The benefits of ammonium feedback control are established through long-term experiments at three large wastewater treatment plants in Stockholm, Sweden. With ammonium feedback control, energy savings up to around 10 % were achieved compared to keeping the dissolved oxygen concentration constant. The experiments generated several lessons learned with regard to implementation and evaluation of controllers in full-scale operation. The thesis has established guidelines on how to design ammonium feedback controllers for situations when cost-effective operation is the overall aim. Simulations have demonstrated the importance to limit the dissolved oxygen concentration in the process and under what conditions the energy saving with ammonium feedback control is large. The final part of the thesis treats improvements of ammonium PI control through minor modifications to the control structure or controller. Three strategies were studied: gain scheduling control, repetitive control, and a strategy reacting to oxygen peaks in the last aerobic zone. The strategies all had their benefits but the ammonium feedback controller was the key factor to improved aeration control.

Η παρούσα διατριβή αφορά στην ολοκλήρωση των μεθόδων Στατιστικού Ελέγχου Ποιότητας με τεχνικές Μηχανικής Μάθησης, για την καλύτερη εξυπηρέτηση των αναγκών των σύγχρονων επιχειρήσεων. Προς αυτή την κατεύθυνση, έγινε αρχικά μια λεπτομερής ανασκόπηση της σχετικής βιβλιογραφίας για τον εντοπισμό και την αναγνώριση των σημαντικότερων ελλείψεων του Στατιστικού Ελέγχου Ποιότητας. Στη συνέχεια, χρησιμοποιήθηκαν τεχνικές Μηχανικής Μάθησης για την αντιμετώπιση των παραπάνω ελλείψεων. Πιο συγκεκριμένα, προτάθηκε μια μεθοδολογία για αναγνώριση μέσων μετατοπίσεων σε αυτοσυσχετιζόμενα δεδομένα πολυμεταβλητών διεργασιών, τα οποία συναντώνται πολύ συχνά σε πραγματικές διεργασίες. Η προτεινόμενη μεθοδολογία δοκιμάζεται και ελέγχεται ως προς την απόδοσή της και την ικανότητά της για εφαρμογή σε δεδομένα διαφορετικής φύσεως σε δυο μελέτες περίπτωσης. Τα αποτελέσματα από τις μελέτες αυτές είναι ενθαρρυντικά καθώς επιτεύχθηκαν αρκετά υψηλά ποσοστά επιτυχών αναγνωρίσεων μέσων μετατοπίσεων. Η διατριβή ολοκληρώνεται με παράθεση μιας σειράς συμπερασμάτων, ανάδειξη της συμβολής της προτεινόμενης μεθοδολογίας και υπόδειξη μελλοντικών ερευνητικών κατευθύνσεων για την επέκτασή της. / This thesis concerns the integration of Statistical Quality Control methods with Machine Learning techniques for covering contemporary business needs. The proposed approach took into account a thorough review of the literature, which identified the major shortcomings of Statistical Quality Control. A consideration of Machine Learning techniques with respect to the above shortcomings was then performed. More specifically, a methodology was proposed for identifying mean shifts in auto-correlated multivariate data processes, which occurs very often in real processes. The proposed approach was tested through two different case studies for its performance and ability to implement data of different type. The results of these case studies were encouraging as quite high rates were achieved for the successful recognition of mean shifts. The thesis concludes by listing a series of findings, highlighting the contribution of the proposed approach and suggesting a series of future research directions.

Submitted by Claudia Rocha (claudia.rocha@udesc.br) on 2017-12-11T15:50:46Z No. of bitstreams: 1 PGEF17MA072.pdf: 1540009 bytes, checksum: 0a6a0c91bcb17bc18be105a058020b75 (MD5) / Made available in DSpace on 2017-12-11T15:50:46Z (GMT). No. of bitstreams: 1 PGEF17MA072.pdf: 1540009 bytes, checksum: 0a6a0c91bcb17bc18be105a058020b75 (MD5) Previous issue date: 2017-02-20 / Some organizations in the Brazilian forestry industry do not follow the development pace of other industries, or the adoption rate of management and quality methodologies and tools. As result, the low quality and high instability of processes create a lot of waste in the sector. This is intensified when it happens during the harvesting, one of the activities that most contributes to the production costs of a forestry business. This study aimed to evaluate the predictability of timber harvesting process based on critical points identified in the thinning and harvest operations. For this, research was divided in three stages. The first one was mapping the harvesting process and the elaboration of fluxograms. The second stage was the identification, through interviews, and assessment of critical points using the Failure Mode and Effect Analysis (FMEA) and Pareto chart. The third stage was the evaluation of the process using Statistical Process Control (SPC) through attributes and variable in the main failures. In the interviews conducted with workers, seven critical points were identified: damage to the remaining trees, sorting, stump height, dirt in load, knot on the second log, tree left in the field and safety. The evaluation with Pareto chart showed that 80% of the failures identified during harvest are attributed to three causes: damage to the remaining trees, sorting and stump height. The FMEA analysis showed that the failure with highest risk index was knots on the second log, followed by safety. For evaluation with the SPC, damage to remaining trees, sorting and stump height were selected. In general, control charts showed that the forest harvest process was considered unstable and unpredictable, even though it is within the limits defined by the company / No setor florestal brasileiro, algumas organizações não acompanham o ritmo do desenvolvimento de outros setores e da adoção de ferramentas e metodologias de gestão da qualidade. Em função deste atraso, a baixa qualidade e alta instabilidade dos processos, geram grandes desperdícios nas organizações. O fato se agrava quando ocorre na operação de colheita da madeira, uma das atividades que mais contribui nos custos de produção da empresa florestal. Este trabalho objetivou avaliar o processo de colheita florestal de uma empresa quanto a sua previsibilidade com base nos pontos críticos identificados nas operações de desbaste e corte raso. Para isso, a pesquisa foi dividida em três etapas, a primeira foi o mapeamento do processo de colheita e elaboração de fluxogramas. A segunda etapa foi a identificação, por meio de entrevistas, e avaliação dos pontos críticos utilizando a metodologia Failure Mode and Effect Analysis – FMEA e gráfico de Pareto. A terceira fase foi a avaliação do processo empregando o Controle Estatístico do Processo (CEP) por atributos e variáveis nas principais falhas. Nas entrevistas realizadas com os colaboradores, sete pontos críticos foram apontados: danos às árvores remanescentes, sortimento, altura de toco, sujeira na carga, nó na 2ª tora, árvores deixadas no talhão e segurança. Na avaliação com o gráfico de Pareto, observou-se que cerca de 80% dos problemas identificados na colheita da empresa são atribuídos às três primeiras causas supracitadas. A análise com o FMEA indicou que a falha com maior índice de risco foi o nó na 2ª tora, seguido da segurança. Para a avaliação com o CEP, selecionou-se os pontos críticos: danos às árvores remanescentes, sortimento e altura de toco. De maneira geral, os gráficos de controle indicaram que o processo da colheita florestal, apesar de estar dentro dos limites especificados pela empresa, foi considerado instável e não previsível

abstract: Many products undergo several stages of testing ranging from tests on individual components to end-item tests. Additionally, these products may be further "tested" via customer or field use. The later failure of a delivered product may in some cases be due to circumstances that have no correlation with the product's inherent quality. However, at times, there may be cues in the upstream test data that, if detected, could serve to predict the likelihood of downstream failure or performance degradation induced by product use or environmental stresses. This study explores the use of downstream factory test data or product field reliability data to infer data mining or pattern recognition criteria onto manufacturing process or upstream test data by means of support vector machines (SVM) in order to provide reliability prediction models. In concert with a risk/benefit analysis, these models can be utilized to drive improvement of the product or, at least, via screening to improve the reliability of the product delivered to the customer. Such models can be used to aid in reliability risk assessment based on detectable correlations between the product test performance and the sources of supply, test stands, or other factors related to product manufacture. As an enhancement to the usefulness of the SVM or hyperplane classifier within this context, L-moments and the Western Electric Company (WECO) Rules are used to augment or replace the native process or test data used as inputs to the classifier. As part of this research, a generalizable binary classification methodology was developed that can be used to design and implement predictors of end-item field failure or downstream product performance based on upstream test data that may be composed of single-parameter, time-series, or multivariate real-valued data. Additionally, the methodology provides input parameter weighting factors that have proved useful in failure analysis and root cause investigations as indicators of which of several upstream product parameters have the greater influence on the downstream failure outcomes. / Dissertation/Thesis / Ph.D. Electrical Engineering 2011