A FRAMEWORK FOR FUNCTION SPECIFICATIONS-TO-CONCEPTUAL FORM TRANSLATION TOOL IN FUNCTION-ORIENTED MECHANICAL DESIGN SYSTEMS

Design is functionality driven. All products and parts have some intended reason behind their existence. Although computer aided systems have made considerable advances in capturing and representing geometrical shape, not much progress has been made in capturing and modeling product functionality and its physical realization. This research proposes a methodology to assist designers during the first stages of design. This methodology provides a framework to help the designer translate functional specifications into conceptual forms. This research develops a translation tool to model functionality and to carry out conceptual design with the aid of the computer. This tool serves as a bridge between the conceptual design phase and the detailed design phase of a product. The translation tool developed in this research supports the conceptual design phase by providing a functional data model, a function server model, and a conceptual product model. The functional model includes the use of operands and relations to define and capture product functionality. The function server model represents the physical realization of the specified functions. The conceptual product model organizes and documents the product information in both the functional and the physical domains. The knowledge base for the function servers is stored in a function driven database. This database allows the designer to view design possibilities that may never have occurred to them.Models provided in this work have been implemented as a relational database system by using MySQL. A web-based graphic user interface is developed with PHP to provide an interactive environment for modeling and for searching the function driven database. Propagation of functional and physical information to downstream design activities has been enabled by the use of the XML data format. The models and concepts developed in this research are validated through a case study of a realistic mechanical device

The impact of CAAD on design methodology and visual thinking in architectural education.

This thesis aims to explore the potential impact of Computer Aided Architectural Design (CAAD) as a conceptual design tool on the design methodology of final year students. Many design studies have focused on sketching and its relationship with creative thinking to validate CAAD programs as a design tool. On the contrary, this study argues that the continued primacy of traditional tools as the predominant conceptual tools needs more evidence in the contemporary design practices. That is to say, the relative importance of CAAD alongside other media, such as sketching, model making and verbalisation must be recognised before the forthcoming leap in CAAD programs development. To illustrate these ideas, the Scott Sutherland School of Architecture and Built Environment was used as a case study to explore CAADs role in the educational context, the studio in general and the final year studio in particular. A mixed methods approach was employed to carry out two studies: a case study and a protocol study. A case study approach was utilised to understand the modern context whereby CAAD is used by the students despite CAAD not being an integrated part of the project model. The case study was also used to document the reasons behind students tendency of using CAAD at the conceptual phases of the design process. Mixed methods were used to collect data at three different intervals of the two semesters; before starting the studio project, while working on the project and after submitting the final project. The methods used include a questionnaire survey, structured reflection interviews, and a focus group. A protocol study was conducted to understand the impact of CAAD on selfcommunication using the think aloud method under the same experimental conditions using CAAD program(s) as the only external representation. The case study findings clarified the effects of the traditional context of the studio and the project model on CAADs utility within students design processes and identified the lack of CAAD professional skills, and the integration of CAAD as a knowledge base. The protocol study findings provided a greater understanding of the cognitive processes in designing and design performance while using CAAD, as well as acknowledging the possibility of a cyclic conceptual process. The potential impact of CAAD on the design process was further categorised. The empirical exploration provides CAAD research with new insights, instigating more useful ways of teaching and learning by an appropriate integration of CAAD programs and design methods in a situated manner where students can enhance their design processes creatively. It is proposed that a more measured and disinterested approach is now required to investigate CAAD and their implications for education

A rule-based method for scalable and traceable evaluation of system architectures

Despite the development of a variety of decision-aid tools for assessing the value of a conceptual design, humans continue to play a dominant role in this process. Researchers have identified two major challenges to automation, namely the subjectivity of value and the existence of multiple and conflicting customer needs. A third challenge is however arising as the amount of data (e.g., expert judgment, requirements, and engineering models) required to assess value increases. This brings two challenges. First, it becomes harder to modify existing knowledge or add new knowledge into the knowledge base. Second, it becomes harder to trace the results provided by the tool back to the design variables and model parameters. Current tools lack the scalability and traceability required to tackle these knowledge-intensive design evaluation problems. This work proposes a traceable and scalable rule-based architecture evaluation tool called VASSAR that is especially tailored to tackle knowledge-intensive problems that can be formulated as configuration design problems, which is demonstrated using the conceptual design task for a laptop. The methodology has three main steps. First, facts containing the capabilities and performance of different architectures are computed using rules containing physical and logical models. Second, capabilities are compared with requirements to assess satisfaction of each requirement. Third, requirement satisfaction is aggregated to yield a manageable number of metrics. An explanation facility keeps track of the value chain all along this process. This paper describes the methodology in detail and discusses in particular different implementations of preference functions as logical rules. A full-scale example around the design of Earth observing satellites is presented

Innovative Conceptual Design of Manual-Concrete-Block-Making-Machine

One of the basic human needs is having a proper shelter. Due to the rapid population and urbanization growth, there is an escalating demand for affordable housing in Kenya. This necessitates looking for ways to reduce construction costs, particularly for low-income housing group. Concrete-block construction has recently gained significance, however most of the commercially-available block-making-machines are imported and also expensive. Locally-made affordable block-making-machine would render useful in lowering the cost of construction. This project, therefore, was aimed to complete a conceptual design of an innovative undemanding stationary manually-operated concrete-block-machine that molds concrete-blocks at a fraction of a cost in comparison with power-operated options. The target specifications were derived from the customers’ needs data collected during the local workshops’ visits and from the secondary sources, mainly patents. Three design alternatives were developed; alternative design #3 was chosen by the engineering design decision-weighted-matrix and by the drop and re-vote (D&R) method. The originality of this design is essentially in the ejection system: as opposed to many block-making-machines available which ejects blocks instead of the mould, this machine ejects the mould leaving the blocks on the base plate. Mild steel was a material of choice for the machine. A static simulation study on the frame model, which was fixed at the bottom mounting and an overall normal force of 981N or 100 Kg applied at the base plate was done using Engineering Design Software: SolidWorks, 2013 (design and simulation tool). The study included Stress, Displacement, and Strain analysis. Conceptual design of manual-concrete block-making-machine was optimized according to results of simulations, calculations and fundamental engineering design principles. Cost estimation shows that this simple and economical piece of equipment could have a potential in lowering the cost of construction. To ascertain a potential, however, the authors propose further work on prototyping and testing to be carried out. Keywords: block-making, concrete, design, machine

Hybrid Low-Order Modeling for Conceptual Vehicle Design

Design freedom, and particularly the freedom to incorporate innovative designs and strategies, is greatest at the very beginning of vehicle conceptual design. Conversely, this is when the least knowledge of the product exists. As product content decisions are made the level of freedom in the design decreases and the design becomes locked in. The majority of vehicle lifecycle cost is also set by the end of vehicle conceptual design. This makes it critical to make well-informed and validated decisions in the concept design phase to avoid expensive iterations and redesign in the detailed design phase. Parametric vehicle modeling permits rapid iteration and optimization of vehicles in the conceptual design phase. A significant portion of vehicle design can be optimized parametrically without knowing specific Computer Aided Design (CAD) based details. Many overall vehicle characteristics such as curb mass, center of gravity location, key dimensions, occupant packaging and cargo volume can all be assessed and improved at the parametric level. Key vehicle performance measures can also be determined to a high level of confidence. In developing vehicle dimensions for a parametric model it is recommended to build up a vehicle using an inside-out approach centered on effective, knowledge-based occupant packaging. This work develops a continuum of dimensional parameters which tie vehicle internal and external dimensions together; it employs a combination of industry standard and author-defined component dimensions which make up overall vehicle outside dimensions. An effective continuum of functional parameters is also developed. In order to develop and optimize models for a desired vehicle type and size class, a knowledge base of vehicle typical values for key dimensional parameters has been compiled using a combination of data sources and field measurements. These values provide a useful starting point for the vehicle design optimization process. They also increase optimization effectiveness and ensure that the optimization begins within a valid design space. This work also develops a parametric modeling, scenario builder and optimization software framework which provides a design and optimization tool for vehicle design with trade-off evaluation tools. These parametric design methods improve design maturity prior to beginning vehicle detailed design

A Conceptual Design Framework based on TRIZ Scientific Effects and Patent Mining

Conceptual design represents a critical initial design stage that involves both technical and creative thinking to develop and derive concept solutions to meet design requirements. TRIZ Scientific Effects (TRIZSE) is one of the TRIZ tools that utilize a database on functional, transformation, parameterization of scientific effects to provide conceptual solutions to engineering and design problems. Although TRIZSE has been introduced to help engineers solve design problems in the conceptual design phase, the current TRIZSE database presents general scientific concept solutions with a few examples of solutions from patents which are very abstract and not updated since its introduction. This research work explores the derivation of a novel framework that integrates TRIZ scientific effects to the current patent information (USPTO) using data mining techniques to develop a better design support tool to assist engineers in deriving innovative design concept solutions. This novel framework will provide better, updated, relevant and specific examples of conceptual design ideas from patents to engineers. The research used Python as the base programming platform to develop a conceptual design software prototype based on this new framework where both the TRIZSE Database and Patents Database (USPTO) are searched and processed in order to build a Doc2Vec similarity model. A case study on the corrosion of copper pipelines by seawater is presented to validate this novel framework and results of the novel TRIZSE Database and patents examples are presented and further discussed in this paper. The results of the case study indicated that the Doc2Vec model is able to perform its intended similarity queries. The patent examples from results of the case study warrant further consideration in conceptual design activities

Metamodeling for the quantitative assessment of conceptual designs in an immersive virtual reality environment

The engineering design process has undergone extensive research in the area of detailed design. Many computer aided design (CAD) software packages have been developed from this research to provide an integral analysis tool for companies in the detailed design phase. However with the development of more complex technologies and systems, decisions made earlier in the design process have been crucial to product success. To help provide valuable information to assist these earlier decisions, tools have also been developed for conceptual design such as lightened CAD packages, concept elimination methods, and image processing software. Unfortunately, these tools have been proven ineffective based on the inability to provide a lower fidelity real-time analysis of each and every concept. By providing real-time analysis, engineers could spend more time evaluating every concept mathematically and base decisions on factual information instead of personal opinion. On a different note, companies continually undergo next generation development of their products. This continuous cycle of design iterations generates a stockpile of high fidelity analysis which we refer to as legacy data. Legacy data contains thousands of geometrical properties and analytical data used to assess the validity of previous designs. This data creates a vast amount of analytical engineering knowledge which can be harnessed to help evaluate the validity of future designs. Statistical approximations known as metamodels can be applied to summarize the general trends of the inputs and outputs of legacy dataset, and eliminate the need for recreating CAD analysis models for each concept. Metamodeling techniques cannot produce 100% accuracy, but at the conceptual design stage, 100% accuracy is not a necessity. This thesis presents an implementation scheme for incorporating Polynomial Response Surface (PRS) methods, Kriging Approximations, and Radial Basis Function Neural Networks (RBFNN) into conceptual design. A conceptual design software application, the Advanced Systems Design Suite (ASDS), has also been developed to incorporate these metamodeling techniques into assessment tools to evaluate conceptual design concepts in both a desktop and immersive virtual reality (VR) environment. The goal of the implementation scheme was to develop a strategy for constructing metamodels upon conceptual design datasets based upon their ability to perform under several conditions including various sample sizes, dataset linearity, interpolation within a domain, and extrapolation outside a domain. In order to develop the implementation scheme, two conceptual design datasets, wheel loading and stress analysis, were constructed due to a lack of available legacy data. The two datasets were setup using a design of experiments (DOE) to generate accurate sample points for the datasets. Once the DOE was formulated, digital prototypes were created in CAD software and the FEA test runs generated the responses of the DOE input parameters. The results of these FEA simulations generated the necessary conceptual design datasets required analyze the three metamodeling techniques. The performance results revealed that each metamodeling technique outperformed the others when tested again the various parameters. For instance, PRS metamodels performed very well when extrapolating outside its domain and with datasets consisting of more than 40 sample points. PRS metamodels require very setup and can be generated very quickly. If speed is the key consideration for metamodel construction, then PRS is the best option. Kriging metamodels showed the best performance with any non-linear dataset and large design space datasets exhibiting linear or non-linear behavior. Kriging metamodels are a very robust metamodeling technique especially when using a first-order global model on non-linear datasets. On the downside, Kriging metamodels require slightly more time to setup and construct than PRS metamodels. RBFNN metamodels performed well when interpolating within a large design space and on any sample size of linear datasets. However to reach performance levels of either PRS or Kriging, the ideal radius value must be determined prior to constructing the final model which took hours on small datasets. If the datasets consisted of thousands of design variables, constructing a RBFNN metamodel would take days to weeks to generate. However if construction time is not an issue, RBFNN metamodels outperform both PRS and Kriging techniques on linear datasets. This implementation scheme for incorporating metamodels into conceptual design provides a method for generating rapid assessment capabilities as an alternative to high fidelity analysis. Future work includes evaluating additional conceptual design datasets to create a more robust implementation scheme. More research will also be done in implementing additional types and varying setup parameters of both Kriging Approximations and Radial Basis Function Neural Networks

Methodology for Including Base Infrastructure in Conceptual System Analysis

The 2018 National Defense Strategy defines a transition to agile basing, where the logistics footprint of new conceptual systems can be distributed across a set of airfields, instead of one main operating base. Currently, there is no capability to assess early concepts using airfield data. This research develops a methodology and a tool that assesses system concepts using world-wide civil and military airfield infrastructure, such as runway parameters, parking, munitions, fuel and warehouse storage, and distance to areas of interest. Specifically, the focus of the thesis is on concepts for the Intelligence, Surveillance, and Reconnaissance (ISR) Strike mission. Four concepts were assessed, a Medium-Altitude Long Endurance (MALE) ISR vehicle similar to a MQ-9 Reaper, a light attack aircraft, a light attack jet, and a low-cost attritable aircraft similar to a BQM-167A aerial drone. The tool incorporates Value Focused Thinking, with the value model conditioned by selected design parameters. The system that values a set of airfields the highest would be advantageous in an adaptive basing environment. The MALE ISR platform resulted in a statistically significant difference (nearly 10%) in median value determined by the Wilcoxon signed rank test, then the other systems across a sampled set of 1,197 CONUS airfields

Design and Implementation of a Method Base Management System for a Situational CASE Environment

Situational method engineering focuses on configuration of system development methods (SDMs) tuned to the situation of a project at hand. Situational methods are assembled from parts of existing SDMs, so called method fragments, that are selected to match the project situation. The complex task of selecting appropriate method fragments and assembling them into a method requires effective automated support. The paper describes the architecture of a tool prototype offering such support. We present the structure of its central repository, a method base containing method fragments. The functions to store, select and assemble these method fragments are offered by a stratified method base management system tool component, which is described as wel