The design of manufacturing systems in hazardous environments is complex, requiring interdisciplinary knowledge to determine which components and operators (human or robotic) are feasible. When conceptualizing designs, some options may be overlooked or unknowingly infeasible due to the design engineers' lack of knowledge in a particular field or ineffective communication of requirements between disciplines. To alleviate many of these design issues, we develop a computational design tool to automate the synthesis of conceptual manufacturing system designs and optimization of preliminary layouts. To generate workcell concepts for manufacturing processes, we create a knowledge-based system (KBS) that performs functional modeling using a common language, a generic component database, and a rule set. The KBS produces high-level task plans for specific manufacturing processes and allocates needed material handling tasks between compatible human and/or robotic labor. We develop an extended pattern search (EPS) algorithm to optimize system layouts based on worker dose and cycle time minimization using the functions and sequencing of generated task plans. The KBS and EPS algorithm were applied to the design of glovebox processing systems at Los Alamos National Laboratory (LANL). Our computational design tool successfully generates design concepts with varied task allocation and processing sub-tasks and layouts with favorable manipulation workspaces. This work establishes a framework for automated conceptual design while providing designers with a beneficial tool for designing manufacturing systems in an interdisciplinary and highly constrained domain. / text

One of two Project Reports / <p> This report describes the basic physical properties of surface wave devices and design procedures necessary to realize filter functions from such devices. The mathematical form of the surface wave is presented. Filter models based on this wave are reviewed and the strong relationship between device geometry and resultant transfer functions is developed. </p> <p> Design and experimental procedures adopted for the synthesis of a surface-wave filter used for colour T.V. I.F. strips are given. Two such filters are actually made in the laboratory and experimental-theoretical results are compared. Results obtained indicate good agreement between theory and experiment, and clearly demonstrate the superiority of surface wave filters over conventional L-C filters in high frequency applications. </p> / Thesis / Master of Engineering (ME)

Conceptual design synthesis is part of the conceptual phase of the design process, which focuses on creating alternative, candidate solutions. Conceptual design phase has the greatest influence on the cost and characteristics of the final product; an excellent detailed design based on a poor and inappropriate concept can never compensate for the inadequacy of the concept. Conceptual design is difficult, which currently relies on the designer’s intuition and experience to guide the process. A major issue in conceptual design is that often not many alternative candidate solutions are explored by the designer during the design process. The major reasons for this are the tendency to delimit a design problem area too narrowly and thus not being able to diversify the possible set of design solutions, possible bias towards a limited set of ideas, and time constraints. Many researchers recommended a thorough search of the design space for developing a good solution; this requires generation of a large solution space. Mechanical devices (mechanisms and machines) have fascinated the mankind throughout recorded history. Conceptual design synthesis of mechanical devices is difficult even for humans, and is also difficult to completely automate. In a single state design task, the relation between an input and output are fixed, but in a multiple state design task, the relation is not fixed. Much of the current research has been focused on supporting synthesis of single state devices, in particular where the device has to convert an input motion into an output motion. Synthesis of multiple state device is in contrast rather poorly understood and supported. Complete automation is unlikely to be possible; developing support taking into account the strength of computer and and human is important mechanical device is not adequate the biggest source for understanding of this process, and for its subsequent support, is human designers. The concept of state for a mechanical device is explained in detail by analyzing the existing multiple state mechanical devices. An operating state described by elemental functions (defined by efforts- motions of input and output components) and their associated Understanding and Supporting Conceptual Design Synthesis of Multiple State Mechanical Devices configurations and configuration changes. However, study of current literature indicates that little has been known about the actual processes carried out by designers in synthesizing multiple state devices. The main objectives of this thesis, therefore, are as follows: (1) understand the multiple state device design synthesis process carried out by designers, and (2) develop methods for supporting synthesis of multiple state mechanical devices to enhance the number of solution alternatives generated. Empirical studies are conducted to understand how designers currently carry out multiple state design tasks. Ten designers are given a multiple state design task and asked to generate as many solutions as possible. The designers are asked to think aloud while carrying out their synthesis processes. All these synthesis processes are video recorded, and analyzed to identify what activities are involved in the multiple state design synthesis, what the inputs are to each activity, and what the outcomes are from each activity. It has been found from these studies that design fixation is quite common, and the majority of the designers pursued developing a single solution to the given design task. A generic descriptive model of the multiple state mechanical device design synthesis process, explaining how this is carried by the designers, is developed. Based on this model, a prescriptive model of multiple state design synthesis process, explaining how the multiple state synthesis process should be carried by designers in order to develop a large solution space, is also developed. The prescriptive support, for synthesizing a large solution space for a given multiple state design task, has been evaluated. Eight engineering designers participated in the evaluation procedure, where each designer had to synthesize solutions for two, given multiple state design tasks. Results indicate that use of the prescriptive support, even without the power of a computational implementation, may have been beneficial in helping designers develop feasible solutions in a greater number of cases in a more efficient manner (that is, by considering fewer solution proposals and in similar amounts of time). All the designers who participated in this exercise gave a positive feedback regarding the prescriptive support. However, in none of the design sessions did the designers develop more than one feasible solution. This, along with various other comments from designers, indicates that a faster and more proactive support – implemented on computer – might be more useful in supporting the tasks. The various aspects for a potential computer support are discussed.

A new design synthesis method for articulated heavy vehicles (AHVs) with an active trailer steering (ATS) system is examined and evaluated. Due to their heavy weights, large sizes, and complex configurations, AHVs have poor maneuverability at low speeds, and low lateral stability at high speeds. Various passive trailer steering and ATS systems have been developed for improving the low-speed maneuverability. However, they often have detrimental effects on the high-speed stability. To date, no systematic design synthesis method has been developed to coordinate the opposing design goals of AHVs. In this thesis, a new automated design synthesis approach, called a Single Design Loop (SDL) method, is proposed and investigated. The SDL method has the following distinguished features: 1) the optimal active design variables of ATS systems and the optimal passive vehicle design variables are searched in a single design loop; 2) in the design process, to evaluate the vehicle performance measures, a driver model is developed and it „drives‟ the vehicle model based on the well-defined testing specifications; and 3) the ATS controller derived from this method has two operational modes: one for improving the lateral stability at high speeds and the other for enhancing path-following at low speeds. To demonstrate the effectiveness of the new SDL method, it is applied to the design of an ATS system for an AHV with a tractor/full-trailer. In comparison to a conventional design approach, the SDL method can search through solutions in a much larger design space, and consequently it provides a more comprehensive set of optimal designs.. / UOIT

Rapid prototyping (RP) can be used to make complex shapes with very little or even no constraint on the form of the parts. New design methods are needed for parts that can take advantage of the unique capabilities of RP. Although current synthesis methods can successfully solve simple design problems, practical applications with thousands to millions elements are prohibitive to generate solution for. Two factors are considered. One is the number of design variables; the other is the optimization method. To reduce the number of design variables, parametric approach is introduced. Control diameters are used to control all strut size across the entire structure by utilizing a concept similar to control vertices and Bezier surface. This operation allows the number of design variables to change from the number of elements to a small set of coefficients. In lattice structure design, global optimization methods are popular and widely used. These methods use heuristic strategies to search the design space and thus perform, as oppose to traditional mathematical programming (MP) methods, a better global search. This work propose that although traditional MP methods find local optimum near starting point, given a quick convergence rate, it will be more efficient to perform such method multiple times to integrate global search than using a global optimization method. Particle Swarm Optimization and Levenburg-Marquardt are chosen to perform the experiments.

The HVAC system configuration is a conceptual design of the HVAC system, including the employed components, the topology of the airflow network, and the control strategy with set points. Selection of HVAC system configuration is normally done in the early stage of the design process. The configuration design, however, has significant impacts on the performance of the final system. This thesis describes the development of the design synthesis of optimal HVAC system configurations by Evolutionary Algorithm. In this research, the HVAC system configuration design synthesis has been formulated as an optimisation problem, in which, the component set of the configuration, the topology of the airflow network, and the control set points for the assumed supervisory control strategy, are the optimisation variables. Psychrometrics-based configuration model has been developed in order to evaluate the optimisation objective of minimising the annual energy consumption of the HVAC system. The optimisation is also subjected to a number of design constraints, including the connectivity of the topology, the performance limitations of the components, and the design requirements for the air-conditioned zones. The configuration synthesis problem is a multi-level optimisation problem. The topology depends on the set of selected components, whereas the search space of the control set points changes with the different components and topology. On the other hand, the performance of the configuration is assessed with its optimum operation; therefore the control set points have to be optimised for each configuration solution, before the optimum configuration can be identified. In this research, a simultaneous evolutionary approach has been developed. All optimisation variables of the configuration have been enwded into an integrated genotypic data structure. Evolutionary operators have also been developed to search the topological space (for the optimum topology) and parametric space (for the optimal control set points) at the same time. The performance of the developed approach has been validated with example optimisation problems. It is concluded that the implemented evolutionary algorithm has been able to find (near) optimum solutions for various design problems, though multiple trials may be required. The limitations of this approach and the direction of future development have been discussed.

Cellular structures are present from the atomic level all the way up to patterns found in human skeleton. They are prevailing structures in the nature and known for their excellent mechanical, thermal, and acoustic properties. Two typical types of cellular structures, lightweight structures and compliant mechanisms, are investigated. Lightweight structures are rigid and designed to reduce weight, while increasing strength and stiffness. Compliant mechanisms are designed to transform motions and forces. Most available artificial lightweight structures are patterns of primitives. However, the performance of lightweight structures can be enhanced by using adaptive cellular structures with conformal strut orientations and sizes, like the trabeculae in femoral bone. Bending, torsion, and nonlinear behaviors of compliant mechanisms have not been sufficiently studied. In order to design adaptive cellular structures, a new unit cell, the unit truss is proposed. The unit truss approach facilitates the design of adaptive cellular structures for enhanced mechanical properties via geometric modeling, finite element analysis, shape optimization, and additive fabrication. Four research questions, which address representation, structural analysis, design synthesis, and manufacturing respectively, are raised and answered. Unit truss enables representation and mechanics analysis for adaptive cellular structures. A synthesis method using engineering optimization algorithms is developed to systematically design adaptive cellular structure. Two examples, graded cellular structure for prosthesis and compliant mechanism for morphing wings, are studied to test the unit truss approach.

This research is focused on helping engineers design better systems by supporting their decision making. When engineers design a system, they have an almost unlimited number of possible system alternatives to consider. Modern systems are difficult to design because of a need to satisfy many different stakeholder concerns from a number of domains which requires a large amount of expert knowledge. Current systems engineering practices try to simplify the design process by providing practical approaches to managing the large amount of knowledge and information needed during the process. Although these methods make designing a system more practical, they do not support a structured decision making process, especially at early stages when designers are selecting the appropriate system architecture, and instead rely on designers using ad hoc frameworks that are often self-contradictory. In this dissertation, a framework for performing architecture exploration at early stages of the design process is presented. The goal is to support more rational and self-consistent decision making by allowing designers to explicitly represent their architecture exploration problem and then use computational tools to perform this exploration. To represent the architecture exploration problem, a modeling language is presented which explicitly models the problem as an architecture selection decision. This language is based on the principles of decision-based design and decision theory, where decisions are made by picking the alternative that results in the most preferred expected outcome. The language is designed to capture potential alternatives in a compact form, analysis knowledge used to predict the quality of a particular alternative, and evaluation criteria to differentiate and rank outcomes. This language is based on the Object Management Group's System Modeling Language (SysML). Where possible, existing SysML constructs are used; when additional constructs are needed, SysML's profile mechanism is used to extend the language. Simply modeling the selection decision explicitly is not sufficient, computational tools are also needed to explore the space of possible solutions and inform designers about the selection of the appropriate alternative. In this investigation, computational tools from the mathematical programming domain are considered for this purpose. A framework for modeling an architecture selection decision in mixed-integer linear programming (MIP) is presented. MIP solvers can then solve the MIP problem to identify promising candidate architectures at early stages of the design process. Mathematical programming is a common optimization domain, but it is rarely used in this context because of the difficulty of manually formulating an architecture selection or exploration problem as a mathematical programming optimization problem. The formulation is presented in a modular fashion; this enables the definition of a model transformation that can be applied to transform the more compact SysML representation into the mathematical programming problem, which is also presented. A modular superstructure representation is used to model the design space; in a superstructure a union of all potential architectures is represented as a set of discrete and continuous variables. Algebraic constraints are added to describe both acceptable variable combinations and system behavior to allow the solver to eliminate clearly poor alternatives and identify promising alternatives. The overall framework is demonstrated on the selection of an actuation subsystem for a hydraulic excavator. This example is chosen because of the variety of potential architecture embodiments and also a plethora of well-known configurations which can be used to verify the results.

This thesis presents an automated software design synthesis framework known as Project Calliope. This framework aligns with Harel's automated software development process as it addresses the aspect of automating design and implementation. Project Calliope is based on a Statecharts synthesis approach in the literature. The main goal of Project Calliope is to automatically generate testable Unified Modeling Language (UML) Statecharts that are deterministic, visually manageable and UML compliant. In order to minimise design errors in the generated UML Statecharts, Project Calliope supports model checking through Statecharts execution. In addition, executable code is automatically generated based on the synthesised UML Statecharts. This framework seeks to provide a pragmatic design framework that can be readily incorporated into software development methodologies that leverage UML. In this thesis, Project Calliope is applied to three simple applications from Whittle and Schumann's examples and a case study based on a commercial application. They are automatic teller machine, coffee dispenser, an agent application, and a groupware application respectively.

National Programme on Micro and Smart Materials and Systems (NPMASS) / A computer-aided technique is developed in this thesis to systematically generate concepts for sensors of a wide variety. A database of building blocks, based on physical laws and effects that capture the transduction rules underlying the working principles of sensors, has been developed to synthesize concepts. The proposed method uses the database to first create a concept-space graph and then selects concepts that correspond to paths in the graph. This is in contrast to and more efficient than existing methods, such as, compositional synthesis and graph-grammar synthesis, where solution paths are laid out first and then a concept-space graph is generated. The research also explores an approach for synthesis of concepts for closed-loop sensors, where a quantity is sensed indirectly after nullifying its effect by using negative feedback. These sensors use negative feedback to increase the dynamic range of operation without compromising the sensitivity and resolution. According to the literature, generation of un-interesting solutions is a major drawback of the building block-based synthesis approaches. In the proposed approach, this shortcoming is mitigated substantially by using some rules. For a number of the concepts generated, in the sensor problems attempted, we found that those concepts were already implemented in existing patents; thus emphasising the usefulness of the concepts produced. The synthesis approach proposed new, feasible sensor concepts, thereby indicating its potential as a stimulator for enhancing creativity of designers. Another important problem is to improve the robustness of designs. Robustness can be achieved by minimizing the side effects. Side effects are defined as unwanted effects that affect the intended working of the sensor. The research presents an algorithm that (a) predicts the potential side effects for the synthesized concepts of sensors; (b) aids in quantifying the magnitude of the side effects, thus helping the designer to predict the significant side effects; and (c) suggests ways to improve the robustness of the design.