Cell culture media used in the manufacture of biopharmaceuticals conventionally contain many animal derived components. These components can harbor adventitious agents which can be transmitted through biotherapeutics, employed in the medical treatment of immunocompromised patients. An ADCF (animal derived component free) medium formulation obviates this concern. A rational method for the rapid and efficient screening and optimization of ADCF media while preserving, if not enhancing, cellular growth and protein productivity is needed. CHO (Chinese Hamster Ovary) cells, widely used as a production platform in industry, expressing a recombinant protein, were employed as a model system. Design of Experiment (DOE) and statistical analysis were employed to assess the impact of media formulation on cellular physiology. Metabolic flux, cellular growth, and protein productivity were evaluated as the measures of ADCF media formulation success. Measurements of extracellular metabolites were determined by HPLC and enzymatic methods. Recombinant protein production was measured by HPLC. This research demonstrates the successful screening and optimization of four plant hydrolysate mixtures (2 soy and 2 wheat) as a replacement for animal derived components. / NSERC, ABIN, MABNET

This master thesis covers the subject of Design of Experiment which is a method of executing experiments or simulations in designed and well planned approaches. The method has been investigated and implemented at a Radar shelter at the Giraffe A4 Radar truck developed by SAAB AB. The thesis was offered by SAAB Surveillance in Gothenburg, Sweden, during the spring of 2018. Design of Experiment was found to be a very powerful method for reducing the number of factors in a large system by executing a number of simulations and evaluating their influence on the studied response. The study of the Radar shelter was done by modelling of a surrogate model of the shelter, parameterization of it and execution of modal and static analyses with designed experiments. The factors studied were dimension of beam components and thicknesses of sheet components. Attempts were made to implement a higher parameterization of the design, involving concept variables and other design changing parameters, but without success. The most demanding and important step to consider during implementation of this method is how the factors of the studied system should be chosen. The factors should be easily adjustable and concrete to enable a parameterisation of these and performing the experiments. The most important responses of the system should be well defined along with other fundamentally important responses to guarantee a robust and reliable outcome from the experimentation. The experimenter should carefully revise the conclusions drawn from the results with respect to the defined experimental setup with boundary conditions and load cases. The results are just as good as the inputs to the experiment.

Oxidative coupling of methane (OCM) is a promising route for converting abundant natural gas resources into more useful chemicals like paraffins and olefins (primarily C2). However, to date, there is no current OCM production plant due to low overall conversion and selectivity to the desired product(s). In this work, different operating factors are studied experimentally and through simulation with respect mainly to three responses: CH4 conversion, C2 main product selectivity, and COx side product selectivity. The aim is to identify the best operating condition for maximum ethylene production combined with COx production. Design of experiments (DoE) method was used to analyze the experimental results by applying the full factorial approach. Simulation results were studied by finding the correlation strength between input factors and responses. It was found that the performance of an OCM reactor could be greatly improved under optimal operating conditions. Operating temperature and CH4/O2 ratio have the highest influence while catalyst weight and flow rate have the lowest influence on the OCM responses and mainly depend on rector dimensions.

Design of experiment (DOE) is a statistical method for testing effects of input factors into a process based on its responses or outputs. Since the influence of these factors and their interactions are studied from the process outputs, then quality of these outputs or the measurements play a significant role in a correct statistical conclusion about the significance of factors and their interactions. Linear regression is a method, which can be applied for the DOE purpose, the parameters of such a regression model are estimated by the ordinary least-squares (OLS) method. This method is sensitive to the presence of any blunder in measurements, meaning that blunders significantly affect the result of a regression using OLS method. This research aims to perform a robustness analysis for some full factorial DOEs by different robust estimators as well as the Taguchi methodology. A full factorial DOE with three factors at three levels, two replicants, and three replicants are performed is studied. Taguchi's approach is conducted by computing the signal-to-noise ratio (S/N) from three replicants, where the lower noise factor means the stronger signal. Robust estimators of Andrews, Cauchy, Fair, Huber, Logistic, Talwar, and Welsch are applied to the DOE in different setups and adding different types and percentages of blunders or gross errors to the data to assess the success rate of each. Number and size of the blunders in the measurements are two important factors influencing the success rate of a robust estimator. For evaluation, our measurements are infected by blunders up to different percentages of data. Our study showed the Talwar robust estimator is the best amongst the rest of estimators and resists well against up to 80% of presence of blunders. Consequently, the use of this estimator instated of the OLS is recommended for DOE purposes. The comparison between Taguchi’s method and robust estimators showed that blunders affect the signal-to-noise ratio as the signal is significantly changed by them, whilst robust estimators suppress the blunders well and the same conclusion as that with the OLS with no blunder can be drawn from them.

No description available.

End-of-life lithium-ion batteries retired from portable electronics, electric vehicles (EVs), and power grids need to be properly recycled to save rare earth metals and avoid any hazardous threats to the environment. The recycling process of a Lithium-ion Battery Cell/Module includes storage, transportation, deactivation, disassembly, and material recovery. This study focused on the disassembly step and proposed a systematic method to recover cathode active coating, which is considered the most valuable component of a LIB, from end-of-life LIB pouch cells. A semi-destructive disassembly sequence is developed according to the internal structure of the LIB cell. A fully automated disassembly line aiming at extracting cathode electrodes is designed, modeled, prototyped, and demonstrated based on the disassembly sequence. In order to further obtain the coating material, the extracted cathode electrodes are treated with the organic solvent method and the relationship between process parameters and cathode coating separation yield is numerically studied with the help of Design of Experiment (DOE). Regression models are then fitted from the DOE result to predict the cathode coating separation yield according to combinations of the process parameters. The single cell material separation methodology developed in this study plays an important role in the industrial application of the direct recycling method that may dominate the battery recycling market due to its environmental friendly technology and high recovery rate regardless of element type in the short future. / Doctor of Philosophy / The bursting demand of lithium-ion batteries from portable electronics, electric vehicles, and power grids in the past few years not only facilitate the booming of the lithium-ion battery market, but also put forward serious global concerns: Where should these batteries go at their end-of life and how should they be treated in a safe and harmless manner. As a metal enriched "city mine", end-of-life LIBs are expected to be properly stored, transported, deactivated, disassembled, and recovered with sufficient safety precautions to prevent fire, explosion or any hazardous emissions. This study focuses on the disassembly procedure and emphasized automated battery disassembly techniques and the improving of material separation efficiency. A disassembly sequence of the pouch cell is scheduled and optimized for the first time. To realize the scheduled sequence, a fully automated pouch cell disassembly system is designed to achieve semi-destructive disassembly of z-folded pouch cells. Fixtures, transporters and end-effectors were prototyped and assembled into the modularized disassembly line which extracts cathode electrodes as final product. Cathode electrodes as the most valuable component in a LIB then need to go through multiple chemical-mechanical treatments to future separate cathode coating and Al current collector. This study utilized DOEs to optimize the operating parameters of the material separation process for Lithium cobalt oxide (LCO) coating and Lithium iron phosphate (LFP) coating. Regression models are successfully established for yield prediction with certain levels of control factors.

The idea underlying the present study was to apply twisting in order to introduce different levels of transverse pressure. The modified structure affected both the bonding level and the evolution of the damage in the yarn. In order to isolate this effect in a broader context, additional parameters were included in the experiment design, namely effects of loading rate, specimen length and filament diameter (directly linked to the fineness of the yarn). These factors have been studied in various contexts by several authors. Some related studies on involved factors will be briefly reviewed.

The usage of statistical methods in the production industry has resulted in quality improvements for several organisations during the last decade. However, advanced statistical methods are still underutilised and underappreciated in quality improvement programs and projects in many companies. Therefore it is of interest to investigate how these methods can be used for quality improvements in the production industry. A case study was conducted at Teufelberger’s wire rope production plant in Wels, Austria. Wire rope type BS 909 was studied by utilising the arsenal of tools and methods that Six Sigma provides, with an emphasis on statistical methods -- especially Design of Experiments. Teufelberger is currently (2016) experiencing diameter issues along the rope and it has been found through customer reclamations and quality controls in the production that the variation in a production lot can be substantial. Furthermore, there is no master setting of process parameters and each operator has their own way of setting and adjusting them, as there are different ways to achieve a product which is within given tolerances. The purpose of this study is to investigate how statistical tools can be applied to minimise variance in a Teufelberger rope manufacturing process, by conducting a case study utilising the quality improvement methodology DMAIC. Experiments were conducted in the following four sub processes which produce input components used during the manufacturing of BS909: KL-A, KL-B, IL and Al. In KL-A the following main effects were identified as significant: Postformers Spin and Postformers Diameter. In KL-B the main effect Postformers Spin was significant. In IL the following main effects were identified as significant: Compacting device, Postformers Spin and Postformers Diameter. In AL the main effect Compacting device was significant. Based on the conclusion derived from analysing these experiments theoretical master setups were created in order to address the variance issue and standardise process parameters. Further verification testing must be conducted in order to verify and tune the proposed master setups before they can be utilised. / Det senaste årtiondet har användningen av statistiska metoder inom tillverkningsindustrin resulterat i kvalitetsförbättringar för flera organisationer men dessa metoder är fortfarande undervärderade och utnyttjas ej till fullo inom program och projekt för kvalitetsförbättringar. Därför är det av intresse att undersöka hur dessa metoder kan användas för kvalitetsförbättringar inom tillverkningsindustrin. Vid en av Teufelbergers produktionsanläggningar av stålvajrar i Wels, Österrike, har en fallstudie med kvalitetsförbättringsmetodiken DMAIC genomförts. Stålvajer typ BS 909 har studerats genom att använda den arsenal av verktyg och metoder som Six Sigma innefattar, med betoning på statistiska metoder och särskilt försöksplanering. Teufelberger hade för tillfället problem med främst diametern av stålvajern. Det har visat sig genom kundreklamationer och kvalitetskontroller i produktionen att variationen i en produktionsserie kan vara betydande. Dessutom finns det ej några dokumenterade optimala inställningar av processparametrar så varje maskinoperatör har sitt eget sätt att ställa in och justera processparametrarna. Detta är möjligt då det finns olika kombinationer av  parameterinställningar som kan ge en produkt som är inom givna toleranser. Syftet med denna studie är att undersöka hur statistikverktyg kan användas för att minimera variansen i en tillverkningsprocess av stålvajer hos företaget Teufelberger, detta genom att utföra en fallstudie med kvalitetsförbättringsmetodiken DMAIC Experiment utfördes i följande fyra processer som producerar ingående komponenter som används vid tillverkningen av BS909: KL-A, KL-B, IL och Al. I processen för KL-A identifierades följande huvudeffekter som aktiva;  Postformers-Spin och Postformers-Diameter. Den enda huvudeffekt som identifierades vara aktiv för KL-B var Postformers-Spin. För IL var följande huvudeffekter aktiva: Compacting device, Postformers-Spin och Postformers-Diameter. I processen AL var endast huvudeffekten Compacting device aktiv. Baserat på det resultat som framkom vid analysen av dessa experiment har nya teoretiskt optimala inställningar beräknats, som förväntas minska variationen i responsvariabeln diameter. De nya rekommenderade inställningarna bör tills vidare kunna fungera som ny standard för produktionen, men verifieringsförsök bör ändå utföras för att bekräfta och finjustera  inställningarna.

The work presented in this thesis is dedicated to the study of vehicle rollover and the tyre and suspension characteristics influencing it. Recent data shows that 35.4% of recorded fatal crashes in Sports Utility Vehicles (SUVs) included vehicle rollover. The effect of rollover on an SUV tends to be more severe than for other types of passenger vehicle. Additionally, the number of SUVs on the roads is rising. Therefore, a thorough understanding of factors affecting the rollover resistance of SUVs is needed. The majority of previous research work on rollover dynamics has been based on low fidelity models. However, vehicle rollover is a highly non-linear event due to the large angles in vehicle body motion, extreme suspension travel, tyre non-linearities and large forces acting on the wheel, resulting in suspension spring-aids, rebound stops and bushings operating in the non-linear region. This work investigates vehicle rollover using a complex and highly non-linear multi-body validated model with 165 degrees of freedom. The vehicle model is complemented by a Magic Formula tyre model. Design of experiment methodology is used to identify tyre properties affecting vehicle rollover. A novel, statistical approach is used to systematically identify the sensitivity of rollover propensity to suspension kinematic and compliance characteristics. In this process, several rollover metrics are examined together with stability considerations and an appropriate rollover metric is devised. Research so far reveals that the tyre properties having the greatest influence on vehicle rollover are friction coefficient, friction variation with load, camber stiffness, and tyre vertical stiffness. Key kinematic and compliance characteristics affecting rollover propensity are front and rear suspension rate, front roll stiffness, front camber gain, front and rear camber compliance and rear jacking force. The study of suspension and tyre parameters affecting rollover is supplemented by an investigation of a novel anti-rollover control scheme based on a reaction wheel actuator. The simulations performed so far show promising results. Even with a very simple and conservative control scheme the reaction wheel, with actuator torque limited to 100Nm, power limited to 5kW and total energy consumption of less than 3kJ, increases the critical manoeuvre velocity by over 9%. The main advantage of the proposed control scheme, as opposed to other known anti-rollover control schemes, is that it prevents rollover whilst allowing the driver to maintain the desired vehicle path.

Lean Six Sigma is a method used to improve the quality and efficiency of processes by reducing variation and eliminating wastes (non-value added activities) in an organisation. The concept of combining the principles and tools of Lean Enterprise and Six Sigma has been discussed in the literature. The majority of Lean Six Sigma applications in private industry have focused primarily on manufacturing applications. The literature has not provided a framework for implementing Lean Six Sigma programmes in non-manufacturing or transactional processes like those in the Entertainment Media industry. The Saudi Broadcasting Corporation (SBC), like many other industries in Saudi Arabia, has high occupational safety risks, such as electric, fire and fall hazards which often occur in the media workplace. These risks are considered very costly and affect productivity and employee morale in general. The main objective of this research is to provide a synergistic approach to integrating occupational health and safety programmes and Lean Six Sigma tools using the DMAIC (Define-Measure-Analyse-Improve-Control) problem-solving method to strengthen and assure the success of safety programmes in the Saudi Broadcasting Corporation (SBC). This research identifies the roadmap (i.e. activities, principles, tools, and important component factors) for applying Lean Six Sigma tools in the media industry. A case study addressing the safety issues that affect employees’ performance within the Saudi Broadcasting Corporation (SBC) TV studio is used to validate work outlined in this research. Furthermore, the Bayesian Belief Networks (BBN) method is used to understand the probability occurrence of safety hazards. The application of the Taguchi Experimental Design method and other Lean Six Sigma tools, such as Cause and Effect diagrams, Pareto principles, 5S, Value Stream map, and Poka-Yoke have been incorporated in to this research. The application of Lean Six Sigma DMAIC problem-solving tools resulted in significant improvement in safety within SBC. The average electrical hazard incident decreased from 2.08 to 0.33, the average fire hazard incident decreased from 1.25 to 0.08, and the average fall hazard incident decreased from 3.42 to 0.17. The research has important implications for the company and its employees, with positive outcomes and feedback reported by top management, the senior technicians, and experts. The research improved the safety by reducing electrical, fire and fall risks. The Safety training sessions are one of the most significant factors that improve their safety awareness. It is observed that Lean Six Sigma problem-solving tools and methods are effective in the Saudi Broadcasting Corporation (SBC).