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This dissertation focuses on the mathematical design of a unified shape kernel for geometric computing, with possible applications to computer aided design (CAM) and manufacturing (CAM), solid geometric modelling, free-form modelling of curves and surfaces, feature-based modelling, finite element meshing, computer animation, etc. The generality of such a unified shape kernel grounds on a shape theory for objects in some Euclidean space. Shape does not mean herein only geometry as usual in geometric modelling, but has been extended to other contexts, e. g. topology, homotopy, convexity theory, etc. This shape theory has enabled to make a shape analysis of the current geometric kernels. Significant deficiencies have been then identified in how these geometric kernels represent shapes from different applications. This thesis concludes that it is possible to construct a general shape kernel capable of representing and manipulating general specifications of shape for objects even in higher-dimensional Euclidean spaces, regardless whether such objects are implicitly or parametrically defined, they have ‘incomplete boundaries’ or not, they are structured with more or less detail or subcomplexes, which design sequence has been followed in a modelling session, etc. For this end, the basic constituents of such a general geometric kernel, say a combinatorial data structure and respective Euler operators for n-dimensional regular stratified objects, have been introduced and discussed.

The implicit and low-level part definition data, provided by geometric modeling cannot be used by downstream applications. Therefore, feature based modeling concept has been introduced to integrate CAD and downstream applications. However, due to the lack of implicit and explicit standard representations for features and unmanageable number of possible predefined features without standardization, feature based modeling approach has proved to be inadequate. STEP AP224 provides a standard for both implicit and explicit representations for manufacturing features. This thesis presents STEP AP224 features based modeling for rotational parts. The thesis covers features extracted from STEP AP224 for rotational parts and their definitions, classifications, attributes, generation techniques, attachment methods and geometrical constraints. In this thesis a feature modeler for rotational parts has been developed. STEP AP224 features generated are used as the basic entities for part design. The architecture of the proposed system consists of two three phases: (1) feature library, (2) feature modeler and (3) preprocessor. Preprocessor responsible from STEP-XML data file creation. The data file created can be used in the integration CAPP/CAM systems without using a complex feature recognition process. An object-oriented design approach is used in developing the feature modeler to provide incremental system development and reusability.

This dissertation aims to advance the field of structural optimization by creating and demonstrating new methodologies for the explicit inclusion of manufacturing issues. The case of composite aerospace structures was a main focus of this work as that field provides some of the greatest complexities in manufacturing yet also provides the greatest incentives to optimize structural performance. Firstly, the possibilities for modifying existing FEA based structural optimization methods to better capture manufacturing constraints are investigated. Examples of brick-based topology optimization, shell-based topology optimization, parametric sizing optimization and manufacturing process optimization are given. From these examples, a number of fundamental limitations to these methods were observed and are discussed. The key limitation that was uncovered related to a dichotomy between analytical methods (such as FEA) and CAD-type methods. Based on these observations, a new Knowledge-Based framework for structural optimization was suggested whereby manufacturing issues are integrally linked to the more conventional structural issues. A prototype system to implement this new framework was developed and is discussed. Finally, the validity of the framework was demonstrated by application to a generic composite rib design problem.

Context. Software product planning involves product lifecycle management, roadmapping, release planning and requirements engineering. Requirements are collected and used together with criteria to define short-term plans, release plans and long-term plans, roadmaps. The different stages of the product lifecycle determine whether a product is mainly evolved, extended, or simply maintained. When eliciting requirements and identifying criteria for software product planning, the product manager is confronted with statements about customer interests that do not correspond to their needs. Analytics summarize, filter, and transform measurements to obtain insights about what happened, how it happened, and why it happened. Analytics have been used for improving usability of software solutions, monitoring reliability of networks and for performance engineering. However, the concept of using analytics to determine the evolution of a software solution is unexplored. In a context where a misunderstanding of users’ need can easily lead the effective product design to failure, the support of analytics for software product planning can contribute to fostering the realization of which features of the product are useful for the users or customers. Objective. In observation of a lack of primary studies, the first step is to apply analytics of software product planning concept in the evolution of software solutions by having an understanding of the product usage measurement. For this reason, this research aims to understand relevant analytics of users’ interaction with SaaS applications. In addition, to identify an effective way to collect right analytics and measure feature usage with respect to page-based analytics and feature-based analytics to provide decision-support for software product planning. Methods. This research combines a literature review of the state-of-the-art to understand the research gap, related works and to find out relevant analytics for software product planning. A market research is conducted to compare the features of different analytics tools to identify an effective way to collect relevant analytics. Hence, a prototype analytics tool is developed to explore the way of measuring feature usage of a SaaS website to provide decision-support for software product planning. Finally, a software simulation is performed to understand the impact of page clutter, erroneous page presentation and feature spread with respect to page-based analytics and feature-based analytics. Results. The literature review reveals the studies which describe the related work on relevant categories of software analytics that are important for measuring software usage. A software-supported approach, developed from the feature comparison results of different analytics tools, ensures an effective way of collecting analytics for product planners. Moreover, the study results can be used to understand the impact of page clutter, erroneous page representation and feature spread with respect to page-based analytics and feature-based analytics. The study reveals that the page clutter, erroneous page presentation and feature spread exaggerate feature usage measurement with the page-based analytics, but not with the feature-based analytics. Conclusions. The research provided a wide set of evidence fostering the understanding of relevant analytics for software product planning. The results revealed the way of measuring the feature usage to SaaS product managers. Furthermore, feature usage measurement of SaaS websites can be recognized, which helps product managers to understand the impact of page clutter, erroneous page presentation and feature spread between page-based and feature-based analytics. Further case study can be performed to evaluate the solution proposals by tailoring the company needs. / +46739480254

Shipping companies have a lot of difficulties to control and screen packages such as mail or different types of cargo that may contain dangerous or illegal goods. This project has the goal to enhance the supply chain security by elaborating a way to automatically detect manipulated packages. Based on image comparison, an algorithm can say whether a package shows significant doubts to be put aside for more inspection. After being coded, this algorithm is explained in this thesis. It uses an image registration method as well as a differentiation technique to detect tampered patterns from one image of package at one point of the supply chain to another image of the same package at a later stage. Results show that re-sealed packages, ripped packages or blacked labels can be detected and minor manipulations such as modifications on the barcode can be detected with a close-up of the local region. The principal goal of this project is to give recommendations on what is possible to detect and how to implement this algorithm. This work is a first step toward the use of image processing in future work for package screening.

Manufacturing companies are faced with challenges associated with the fluctuating demand in consumer purchases. As a result, broader families of varyingly manufactured products are on the rise, which poses a significant workload problem for production engineers involved with process planning. The aim of this paper is therefore to introduce Feature-based Machining, as an endorsed CAM-based method to alleviate such workload involved when planning for machining processes. Feature-based Machining does this by eliminating conventional work steps associated with Computer-aided Manufacturing, such as defining cutting parameters, tool associations, feeds and speeds, tool-path generation, and more. By recognizing features over a given workpiece, several pre-taught operations can be automatically generated in response, following an established library of machining knowledge. The methodology of preparing Feature-based Machining is an extensive process that is to be detailed comprehensively in this project, so that future projects and industries may adopt it as a resolute method towards process planning. Moreover, relevant subjects such as sustainability, ethical concerns and innovation are also to be reflected on from the perspective of Feature-based Machining, to provide for fruitful discussion surrounding strategies and implementation.Furthermore, it is also relevant to discuss the intuitiveness and transparency of computer[1]aided software, as it relates to any issues or hurdles that may be encountered during the process of applying Feature-based Machining. Despite such challenges, this project has resulted in a visual framework of recognizing features and applying processes across a family of crankshaft workpieces, where the utility of Feature-based Machining has proven significantly promising for industries of the future, as a result. Future work is also encouraged to follow up on the significance of Virtual Commissioning to this part, as well as a thorough review of Feature-based Machining as a modern subject.

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