Fraunhofer Chalmers Research Centre for Industrial Mathematics
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Identifiability of parameters in PBPK models
No full textInthefieldofpharmacologics,physiologically-basedpharmacokinetic(PBPK)models can be used for predicting the pharmacokinetics of a drug compound in the body. These models are often a system of ordinary differential equations (ODEs) that describe the transport of a drug between different compartments of the body. The models depend on several parameters, some of which cannot be measured experimentally and instead these parameters are often estimated from experimental data using maximum likelihood. However, in many applications in systems biology, estimates will suffer from unidentifiability issues, meaning that well-determined estimates cannot be inferred from the data [17]. Thisproblemcomesintwoforms,structuralunidentifiabilityandpracticalunidentifiability,bothofwhichcanbeanalyzedwiththeprofilelikelihoodmethoddeveloped by Raue et.al [14]. The profile likelihood method is a numerical method for calculating likelihood-based confidence intervals of the parameters, which are then used to assess identifiability. In this project the profile likelihood method is implemented in MATLAB and used to perform identifiability analysis on key model parameters for three PBPK models using simulated data. Thus, the results of this project are both a showcase of the profilelikelihoodmethodandananalysisoftheidentifiabilityofparametersinsome specific models used for pulmonary drug delivery. The results indicate that if very precise measurements could be taken then all parameters considered would be identifiable. When a reasonable measurement error is applied on the simulated data the same is not true. Some parameters, such as the in-vivo pulmonary permeability and deposition fraction will remain identifiable, but most other parameters will suffer from practical unidentifiability. With a reasonable measurement error the identifiability of most model parameters will also be dependent on the particular error realization. To address these issues, additional dataisconsideredbyobservinghowtheuncertaintyinparameterestimatesimpacts observables. Bythismethod(alsosuggestedbyRaue[14])additionalmeasurements are introduced in an effective manner to potentially resolve unidentifiabilities.
Keywords: structural unidentifiability, practical unidentifiability, pulmonary drug delivery, maximum likelihood estimation
Micromechanical modeling of Dual-Phase steels
No full textDual-phase (DP) steel is a high strength steel, much used by the automotive industry due to its characteristic combination of low initial yield stress, high tensile stress and easy cold working and weldability. These advantageous features are related to the microstructure of soft ferrite and hard martensite. The total mechanical behavior of such a material is primarily
derived from the volume fraction of each phase, grain sizes, distribution of the phases and alloying elements. However, to be able to benet from the prominent features of the material to an even greater extent than today, more knowledge on how the microstructural parameters
are correlated to its end-properties is needed.
In this thesis the mechanical behavior of DP steel in uniaxial tension is studied with regard to microstructure. A micromechanical modeling framework utilizing an axisymmetric representative volume element (RVE) is implemented in Abaqus. The RVE consists of a sphere representing the martensite, in a cylinder of ferrite. A single-phase material model describing
the plastic ow is applied to each respective phase, but with different material parameters. This constitutive description is developed from a dislocation density theory where microstructural parameters control the plastic flow. More knowledge about the behavior of the DP steel, the microstructure, correlations between different parameters, modeling techniques and constitutive
models suitable for DP steels were retrieved from a literature review.
Microstructural characterization and mechanical testing in tensile response and hardness have previously been performed on four DP steels in varying strength classes at the Norwegian University of Science and Technology. The retrieved microstructural data was applied to the
micromechanical model and the results from the mechanical testing were used to validate the predictions on tensile response from numerical simulations of the micromechanical model. Despite the simplicity of the micromechanical modelling framework it in general produces results that are in good agreement with the corresponding mechanical tests. However, deviations
are seen in the modeling of the strongest steel, which has the highest volume fraction of martensite. This may indicate that the ferrite is more accurately represented than the martensitic phase. It was also shown that when the geometry of the martensitic sphere was changed in such a way that the ferrite in certain areas got more constrained, an undesired strengthening effect was obtained. This indicates that the specic RVE used in the study has geometrical limitations and that it is more suitable for lower volume fractions of martensite.
The thesis has been conducted through a collaboration between Chalmers University of Technology and Norwegian University of Science and Technology
Improving the Industrialisation Process at an Engineer-to-Order Company An Analysis of the Interface between Design and Manufacturing
No full textEngineer-to-order companies face demand for rapid development of complex products due to a dynamic market. Thus, short lead times and flow efficiency are important to ensure competitiveness. In order to ensure an efficient product development process, a smooth transition between design and manufacturing is required. Therefore the industrialisation process, which is the interface between these two, is of paramount importance. This master thesis studies the industrialisation process at a Defence and Security Company, which includes describing and analysing the product flow from the end of the design phase, via the industrialisation function, to manufactured product. The aim is to improve the performance of the product flow in terms of reduced lead times, without compromising on quality. A current state description with a visualization over the product flow was created based mainly on observations and interviews, including both the product flow of new products as well as previously produced products. This showed that the product flow was iterative and complex due to issues which arise. Parallel to this, an empirical study was conducted on two other companies, as well as the creation of a theoretical framework covering areas such as concurrent engineering, lean production within engineer-to-order environments and social sustainability.
Several areas of friction with a negative impact on the performance were identified based on the current status description, such as non-standardized working procedures, non-value adding activities and low collaboration between the involved functions of the product flow. The areas of friction result in negative effects such as unwanted variation, delays and low motivation, which in turn have a negative impact on the performance of the product flow in terms of increased lead times and inadequate social sustainability. Subsequently, a set of suggested improvements were identified in order to increase collaboration, standardization and transparency, which are three key principles to consider for an improved performance. Some of the suggested improvements are cross-functional teams and meetings, standardized processes, synchronized planning, common goals and utilization of visual management. These positively affect the performance of the product flow in terms of shorter lead times and higher employee motivation. In conclusion, the theoretical contribution of this thesis is an investigation of how the industrialisation process in an ETO environment can be improved utilizing academic principles
