Operational risk has become an increasingly important topic within financial institutions of late, resulting in an increased spend by financial service organisations on operational risk management solutions. While this move is positive, evidence has shown that information technology implementations have tended to have low rates of success. Research highlighted that a series of defined critical success factors could reduce the risk of implementation failure. Investigations into the literature revealed that no critical success factors had been defined for the implementation of an operational risk management system. Through a literature study, a list of 29 critical success factors was identified. To confirm these factors, a questionnaire was developed. The questionnaire was distributed to an identified target audience within the South African financial services community. Reponses to the questionnaire revealed that 27 of the 29 critical success factors were deemed important and critical to the implementation of an operational risk management system. / Business Management / M. Com. (Business Management)

[pt] A maioria dos trabalhos que propõem esquemas de Controle Estatístico de Processos Multivariados (CEPM) e que analisam o desempenho desses esquemas considera alterações nas variáveis observadas. Alguns autores mostraram que, quando alterações no vetor de médias de um processo multivariado ocorrem tipicamente em direções previsíveis, a estatística mais eficaz para o monitoramento do processo é o valor da projeção do vetor de observações (ou de sua média amostral) em cada uma dessas direções. Este trabalho propõe um método para o monitoramento de processos multivariados nos quais alterações nos parâmetros do processo são devidas a causas especiais que afetam variáveis não observáveis e ocorrem em direções conhecidas (ortogonais), e compara seu desempenho com o de gráficos de Shewhart nas variáveis observadas, nas componentes principais, e com o de gráficos de T2 no vetor de variáveis observadas. Além disso, é proposto um esquema complementar de monitoramento para detectar alterações em novas direções fora do hiperplano formado pelas direções conhecidas. Resultados obtidos por simulação mostram que o esquema proposto, de gráficos de controle em variáveis transformadas (projeções do vetor de variáveis observadas nas direções conhecidas), tem melhor desempenho na maior parte dos casos analisados. A análise de desempenho é feita supondo deslocamentos da média nas direções conhecidas (já que estes é que são as alterações conhecidas, ocasionadas pelas causas especiais) e/ou aumentos da variância nessas mesmas direções. A comparação é baseada nas probabilidades de alarme falso e de alarme verdadeiro. / [en] Most of the works that propose schemes of Multivariate Statistical Process Control (MSPC) and that analyze the performance of these schemes consider changes in the observed variables. Previous authors have shown that when the shifts in the mean vector of a multivariate process typically occur in predictable directions, the most effective statistics for process monitoring are the values of the projections of the vector of observations (or of the sample average vector) in each of these directions. This paper proposes a method for the monitoring of multivariate processes in which changes in the process parameters are due to special causes that affect non-observable variables and occur in (orthogonal) known directions, and compares its performance with that of Shewharts charts on the observed variables, on the principal components, and with that of T2 charts on the vector of observed variables. In addition, it is proposed a supplementary scheme of monitoring to detect changes in new directions outside of the hyperplane formed by known directions. Results obtained by simulation show that the proposed scheme, consisting of control charts on the transformed variables (projections of the vector of observed variables on the known directions), has better performance in most of the cases analyzed. The analysis of performance is done assuming shifts in the mean of the known directions (since these are the known changes associated to special causes) and/or increases of the variance in these same directions. The comparisons are based on the in-control and out-of-control probabilities of signal.

Le mélange de poudres est une opération essentielle dans divers domaines industriels, tels que les produits pharmaceutiques, agro-alimentaires, ciments, etc. Le mélange de poudres en continu, comme alternative intéressante au mélange conventionnel en batch, suscite beaucoup d'intérêt surtout en raison de sa capacité à gérer de grands volumes de production. Ce travail vise à contribuer à l'implémentation des applications de contrôle-commande. Avant de développer des stratégies de contrôle-commande, de nouveaux développements ont été présentés pour mieux comprendre le mélange continu de deux composants. La masse retenue et la répartition relative de la masse retenue de chaque composant dans le mélangeur ont été étudiées et prédites sous les différentes conditions opératoires. L'amélioration d'un modèle basé sur les chaînes de Markov a été finalement présentée pour prédire la concentration moyenne des mélanges obtenus à la sortie du mélangeur. L'implémentation d'un contrôleur PID a été expérimentalement réalisée comme une première tentative pour contrôler en temps réel l'homogénéité du mélange produit. La vitesse de rotation du mobile d'agitation, identifiée comme un facteur important influençant l'efficacité du mixer, a été considérée comme la variable manipulée. La commande en boucle fermée est basée, soit sur la concentration moyenne, soit sur le coefficient de variation. Les performances des boucles fermées proposées ont été évaluées pour le mélange continu subi à des changements d'échelon dans les débits d'alimentation du mélangeur. Quatre études de cas ont été définies et présentées. Le défi principal dans le système de contrôle-commande est le réglage des paramètres PID. La performance de commande en boucle fermée soit de la concentration moyenne, soit du coefficient de variation a été comparée à l'opération en boucle ouverte. / 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.

This study develops a heuristic procedure for specifying parameters for a neural network configuration (learning rate, momentum, and the number of neurons in a single hidden layer) in Shewhart X-bar control chart applications. Also, this study examines the replicability of the neural network solution when the neural network is retrained several times with different initial weights.

<div>In the past two decades, the pharmaceutical industry has been engaged in modernization of its drug development and manufacturing strategies, spurred onward by changing market pressures, regulatory encouragement, and technological advancement. Concomitant with these changes has been a shift toward new modalities of manufacturing in support of patient-centric medicine and on-demand production. To achieve these objectives requires manufacturing platforms which are both flexible and scalable, hence the interest in development of small-scale, continuous processes for synthesis, purification and drug product production. Traditionally, the downstream steps begin with a crystalline drug powder – the effluent of the final purification steps – and convert this to tablets or capsules through a series of batch unit operations reliant on powder processing. As an alternative, additive manufacturing technologies provide the means to circumvent difficulties associated with dry powder rheology, while being inherently capable of flexible production.</div><div>Through the combination of physical knowledge, experimental work, and data-driven methods, a framework was developed for ink formulation and process operation in drop-on-demand manufacturing with non-Brownian suspensions. Motivated by the challenges at hand, application of novel computational image analysis techniques yielded insight into the effects of non-Brownian particles and fluid properties on rheology. Furthermore, the extraction of modal and statistical information provided insight into the stochastic events which appear to play a notable role in drop formation from such suspensions. These computer vision algorithms can readily be applied by other researchers interested in the physics of drop coalescence and breakup in order to further modeling efforts.</div><div>Returning to the realm of process development to deal with challenges of monitoring and quality control initiated by suspension-based manufacturing, these machine vision algorithms were combined with Bayesian modeling to enact a probabilistic control strategy at the level of each dosage unit by utilizing the real-time image data acquired by an online process image sensor. Drawing upon a large historical database which spanned a wide range of conditions, a hierarchical modeling approach was used to incorporate the various sources of uncertainty inherent to the manufacturing process and monitoring technology, therefore providing more reliable predictions for future data at in-sample and out-of-sample conditions.</div><div>This thesis thus contributes advances in three closely linked areas: additive manufacturing of solid oral drug products, computer vision methods for event recognition in drop formation, and Bayesian hierarchical modeling to predict the probability that each dosage unit produced is within specifications.</div><div><br></div>

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The project covers the substitution of a stamping shut height measurement at the chainsaw chain factory Husqvarna Edge, with a new sensor-based processmonitoring system, set to increase productivity and decrease running costs. The workflow covers the span from external and needs analysis to development and testing of both hardware and software, in conjunction with communication with external suppliers to find the most usable and profitable solution going forward. Regarding hardware was inductive / eddy-current distance measurement sensors the most suitable for the stamping press environment, providing high sample rate and repeatability to a micrometre level, while subjected to oil andvibration. Husqvarna’s state of the art stamping setup is not yet fully supported by process monitoring suppliers, which resulted in the creation of the new program called Live Height, which was successfully used for sensor evaluation and serves as an example for suppliers to expand upon. This work provides several options in different price ranges for Husqvarna’s management to make decisions upon.

To minimize the complexity of existing process control valves, the authors derived a new control valve design by functional separation and functional integration of functions. One key element of this new valve design is the functional integration of teh actuator into the valve´s throttle. A hydraulic swivel motor is operated with the process fluid, in this case water. The pressure difference to operate the motor comes from the valve itself. Within this paper we present the control valve design and show in detail how we used the Fail-Early design method to develop the hydraulic swivel motor. The construction is discussed using the experience from manufacturing the prototype and the first exp erimental results are shown. The experiments yield, that the swivel motor principle is promising. Finally, the next development issues are discussed.

Rechargeable lithium-ion batteries (LIBs) have generated a shift in the automotive industry towards electric vehicles (EVs) instead of vehicles powered by fossil fuels. As a result, the demand for LIBs is only expected to grow in the future due to an increased demand for passenger EVs. Consequently, LIB manufacturers have to increase their production to meet the increasing demand. Northvolt is a Swedish LIB manufacturer founded in 2016, aiming to start the production of LIBs at the Northvolt Ett factory in Skellefteå during 2021. The Northvolt Ett factory will be one of the largest battery plants in Europe, supplying battery cells for both commercial and domestic use. Poorly manufactured battery cells can potentially cause hazardous events, such as fires or explosions, further supporting the need for high quality batteries. Consequently, requirements from customers and industry standards are high in terms of product quality control through e.g. measurement system analysis (MSA), statistical process control (SPC), and capability analysis. Furthermore, previous research has highlighted issues during commissioning and ramp-up of production, potentially occurring at Northvolt Ett.  The purpose of this study has been to describe how high-quality production can be ensured and maintained during and after commissioning. The study has been conducted as a qualitative case study at Northvolt Ett, focusing on qualification of the coating process. The basis for the study was to examine previous research on quality assurance from other industries, analyze automotive standards, and gather learnings from the pilot production at Northvolt Labs in Västerås. Unstructured interviews were conducted with Northvolt staff to understand what had previously been done related to quality assurance for Coating.  The learnings from Northvolt Labs highlighted a clear focus on preventive actions, such as establishing a Design-FMEA, Process-FMEA, and a Control Plan for the coating process. However, room for improvement was identified in terms of process improvement and control, since the lack of SPC has yielded unreliable results from the performed capability analysis. In addition, previous research has shown that preventive actions should be combined with actions for process improvement to reach full-scale production quickly. Thus, recommendations have been made for Northvolt to implement a clear strategy for product qualification through SPC and capability analysis, as a complement to the preventive actions. The recommendations include specific propositions for validation of the coating process and a general framework for process validation through MSA, SPC, and capability analysis. The presented recommendations can help Northvolt perform successful commissioning of the processes at Northvolt Ett and can also be useful for process validation in other manufacturing industries. / Laddningsbara litium-jon-batterier (LIB:s) har skapat en omställning i bilindustrin mot eldrivna fordon istället för fordon som drivs av fossila bränslen. Som en konsekvens väntas efterfrågan av LIB:s bara att öka i framtiden på grund av en ökad efterfrågan på eldrivna passagerarfordon. LIB-tillverkare måste därför öka sin produktion för att möta den växande efterfrågan. Northvolt är en svensk LIB-tillverkare som grundades 2016, med sikte på att starta produktionen av LIB:s vid fabriken Northvolt Ett i Skellefteå under 2021. Fabriken Northvolt Ett kommer att vara en av de största batterifabrikerna i Europa och leverera battericeller för både kommersiell och privat användning. Dåligt tillverkade battericeller kan potentiellt orsaka allvarliga händelser som bränder eller explosioner, vilket vidare stödjer behovet av batterier med hög kvalitet. Till följd av detta är kraven från standarder och tillverkare inom bilindustrin höga i termer av kvalitetskontroll av produkter genom t.ex. mätsystemanalys (MSA), statistisk processtyrning (SPS), och duglighetsanalys. Vidare visar tidigare forskning på problem som kan uppstå under driftsättning och upprampning av produktion, vilka potentiellt kan uppstå för Northvolt Ett.  Syftet med denna studie har varit att beskriva hur högkvalitativ produktion kan säkerställas och upprätthållas under och efter driftsättning. Studien har genomförts som en kvalitativ fallstudie vid Northvolt Ett med fokus på kvalifikation av coating-processen. Utgångspunkten för studien har varit att undersöka tidigare forskning inom kvalitetssäkring från andra industrier, analysera standarder från bilindustrin, och hämta in lärdomar från pilotproduktionen vid Northvolt Labs i Västerås. Ostrukturerade intervjuer genomfördes med anställda på Northvolt för att öka förståelsen för vad som tidigare gjorts relaterat till kvalitetssäkring för Coating.  Lärdomarna från Northvolt Labs visade ett tydligt fokus på förebyggande åtgärder, som upprättande av en Design-FMEA, Process-FMEA, och en kontrollplan för coating-processen. Dock identifierades ett förbättringsområde inom åtgärder för processförbättring och kontroll, då avsaknaden av SPS har genererat opålitliga resultat från den genomförda duglighetsanalysen. Vidare har tidigare forskning visat att förebyggande åtgärder borde kombineras med åtgärder för processförbättring för att snabbt uppnå fullskalig produktion. Rekommendationer har därför tagits fram till Northvolt för att implementera en tydlig strategi för produktkvalifikation genom SPS och duglighetsanalys, som ett komplement till de förebyggande åtgärderna. Dessa rekommendationer inkluderar specifika förslag för validering av coating-processen samt ett generellt ramverk för processvalidering genom MSA, SPS, och duglighetsanalys. De presenterade rekommendationerna kan hjälpa Northvolt att genomföra en framgångsrik driftsättning av processerna på Northvolt Ett och kan även vara användbara för processvalidering i andra tillverkningsindustrier.

In recent years there has been an increasing interest in understanding how organizations can utilize big data in their process management to create value and improve their processes. This is due to new challenges for process management which have arisen from increasing competition and the complexity of large data sets due to technological advancements. These large data sets have been described by scholars as big data which involves data that are so complex traditional data analysis software are not sufficient in managing or analyzing them. Because of the complexity of handling such great volumes of data there is a big gap in practical examples where organizations have incorporated big data in their process management. Therefore, in order to fill relevant gaps and contribute to advancements in this field, this thesis will explore how big data can contribute to improved process management. Hence, the aim of this thesis entailed investigating how, why and to what extent big data is used in process management. As well as to outline the purpose and challenges of using big data in process management. This was accomplished through a literature review and a survey, respectively, in order to understand how big data had previously been used to create value and improve processes in organizations. From the extensive literature review, an analysis matrix of how big data is used in process management is provided through the intersections between big data and process management dimensions. The analysis matrix showed that most of the instances in which big data was used in process management were in process analysis &amp; improvement and process control &amp; agility. Simply put, organizations used big data in specific activities involved in process management but not in a holistic manner. Furthermore, the limited findings from the survey indicate that the main challenges and purposes of big data use in Swedish organizations are the complexity of handling data and making statistically better decisions, respectively.