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1	Economic aspects of additive manufacturing : benefits, costs and energy consumption Baumers, Martin January 2012 (has links) Additive Manufacturing (AM) refers to the use of a group of technologies capable of combining material layer-by-layer to manufacture geometrically complex products in a single digitally controlled process step, entirely without moulds, dies or other tooling. AM is a parallel manufacturing approach, allowing the contemporaneous production of multiple, potentially unrelated, components or products. This thesis contributes to the understanding of the economic aspects of additive technology usage through an analysis of the effect of AM s parallel nature on economic and environmental performance measurement. Further, this work assesses AM s ability to efficiently create complex components or products. To do so, this thesis applies a methodology for the quantitative analysis of the shape complexity of AM output. Moreover, this thesis develops and applies a methodology for the combined estimation of build time, process energy flows and financial costs. A key challenge met by this estimation technique is that results are derived on the basis of technically efficient AM operation. Results indicate that, at least for the technology variant Electron Beam Melting, shape complexity may be realised at zero marginal energy consumption and cost. Further, the combined estimator of build time, energy consumption and cost suggests t AM process efficiency is independent of production volume. Rather, this thesis argues that the key to efficient AM operation lies in the user s ability to exhaust the available build space. 641.3
2	A Quantitative Approach to the Identification and Prediction of Supply Chain Agility Sheffield, David A. 01 June 2016 (has links) As the product-release cycle in the tech industry speeds up, there is more pressure on manufacturers to bring new products to market faster than ever. This puts a great deal of pressure on the suppliers of capital equipment used to manufacture these tech products. The supply chain agility of these suppliers is increasingly important. The purpose of this study is three-fold (1) to develop a methodology that can be used by any firm for measuring and ranking the agility of suppliers and finding the root causes of supplier agility, (2) to develop the first-ever fully quantitative measure of supply chain agility, and (3) to test if the supply chain management practices that are associated with agility in the academic literature are truly correlated with supply chain agility. Using the outlined methodology in this paper, the data suggest that the customer's current system and processes adequately met the need for short-notice, expedited build times. However, many processes and communications between the suppliers and customer have a lot of room for improvement that may positively impact the supply chain agility of suppliers. Since most every firm captures this same data, such as PO create dates and supplier ship dates, any firm can and should replicate this analysis to discover their suppliers' unique drivers of supply chain agility. Each supplier's historical agility was measured and ranked using historical order performance data. This agility score is the first of its kind to measure agility without the use of qualitative factors or self-reported measures of agility. Only three of the supply chain survey questions developed from or borrowed from the academic literature were correlated with supply chain agility in this study. Survey responses regarding the frequency of communication and information sharing are two examples of variables that were not associated with supplier supply chain agility. The only survey question response that was found to be positively correlated with supply chain agility involves the agile practice of delayed product differentiation. Contrary to the literature, two questions involving supplier-customer communication and the linking of order management system were found to be negatively correlated with supply chain agility. In regards to the non-survey, historical data, the independent variables that were correlated with agility highlighted the need for improved systems and processes between the suppliers and customer. Two examples of processes and systems that need improvement are expedited build time requests and PO swaps. agility supply chain agile manufacturing supply chain management agility assessment build time Industrial Engineering
3	Optimum Part Build Orientation in Additive Manufacturing for Minimizing Part Errors and Build Time Das, Paramita 12 September 2016 (has links) No description available. Mechanical Engineering Additive Manufacturing Part Build Orientation Build Time Geometric Tolerances Optimization Siemens PLM NX API
4	Selection for Rapid Manufacturing under Epistemic Uncertainty Wilson, Jamal Omari 17 April 2006 (has links) Rapid Prototyping (RP) is the process of building three-dimensional objects, in layers, using additive manufacturing. Rapid Manufacturing (RM) is the use of RP technologies to manufacture end-use, or finished, products. At small lot sizes, such as with customized products, traditional manufacturing technologies become infeasible due to the high costs of tooling and setup. RM offers the opportunity to produce these customized products economically. Coupled with the customization opportunities afforded by RM is a certain degree of uncertainty. This uncertainty is mainly attributed to the lack of information known about what the customers specific requirements and preferences are at the time of production. In this thesis, the author presents an overall method for selection of a RM technology, as an investment decision, under the geometric uncertainty inherent to mass customization. Specifically, the author defines the types of uncertainty inherent to RM (epistemic), proposes a method to account for this uncertainty in a selection process (interval analysis), and proposes a method to select a technology under uncertainty (Decision Theory under strict uncertainty). The author illustrates the method with examples on the selection of an RM technology to produce custom caster wheels and custom hearing aid shells. In addition to the selection methodology, the author also develops universal build time and part cost models for the RM technologies. These models are universal in the sense that they depend explicitly on the parameters that characterize each technology and the overall part characteristics. Part cost Build time Epistemic uncertainty Selection Rapid prototyping Rapid manufacturing Manufacturing processes Uncertainty (Information theory) Rapid prototyping Decision making
5	Analyzing and Reducing Compilation Times for C++ Programs Mivelli, Dennis January 2022 (has links) Software companies often choose to develop in C++ because of the high performance that the language offers. Facilitated by static compilation and powerful optimization options, runtime performance is paid for with compilation time. Although the trade-off is inevitable to some extent, building very large C++ programs from scratch can take up to several hours if extra care is not taken during development. This thesis analyzes compilation times for C++ programs and shows how they can be reduced with the help of design patterns, implementation hiding, and framework related fixes. The results presented prove that compilation times can be decreased significantly with no drawbacks to the maintainability of a program. An in-depth analysis of compilation times and dependencies has been conducted for two large software modules from a representative company. Both modules take over an hour of CPU time each to compile. The time consumption for different compiler activities, such as parsing, preprocessing, and runtime optimization tasks have been measured for the modules. The compilation times for unit tests and mocks which use the GoogleTest framework have been analyzed. A simple method that may reduce compilation times by up to 50% for programs that use GoogleTest is presented. A dependency metric has been created, based on the number of include statements found recursively throughout a program. The dependency metric was found to be connected to compilation time for the two analyzed modules. Other factors that can influence compilation times are also shown, such as runtime optimization options, and the use of templates. Experiments which show how a typical usage of templates can drastically increase compilation times are presented. In addition, a solution which allows templates to be used while avoiding code bloat across translation units is reviewed. The solution effectively rivals non-template code in terms of compilation time. The Pointer to Implementation (PImpl) and Dependency Injection design patterns have been used to refactor a small program. Both design patterns performed well, reducing the total compilation time and total compiler memory usage by 70%. A program that detects dependency cycles has been created, but no cycles were found in any of two modules from the representative company. C++ Compilation Build Dependencies File Dependencies File inclusions Time Speed Compilation time Build time Design patterns PImpl Bridge Dependency injection Pointer to implementation Mocking GoogleTest gMock large large-scale Reduce Reduce compilation times Reduce build times C++ Kompilering Byggtid Beroenden Filberoenden Filinkluderingar Tid Hastighet Kompileringstid Designmönster PImpl Bridge Dependency injection Pointer to implementation Mockning Mocking GoogleTest gMock Storskalig Minska kompileringstid Minska Computer Sciences Datavetenskap (datalogi)

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