Generation and Mapping of Minimally-Restrictive Manufacturability Constraints for Mechanical Design Problems

2019 ◽  
Author(s):  
Albert E. Patterson ◽  
James T. Allison
Keyword(s):  
Design Space ◽  
Mechanical Design ◽  
Problem Formulation ◽  
Design Problems ◽  
Manufacturing Knowledge ◽  
Problem Formulations ◽  
Manufacturing Technologies ◽  
Design Options ◽  
Mechanical Design Problem ◽  
General Method

Abstract Traditional design-for-manufacturing (DFM) strategies focus on efficiency and design simplification and tend to be too restrictive for optimization-based design methods; recent advances in manufacturing technologies have opened up many new and exciting design options, but it is necessary to have a wide design space in order to take advantage of these benefits. What is needed is a simple but effective approach for restricting the design space to designs which are guaranteed to be manufacturable, but which leave intact as much of the design space as possible. Work has been done in this area for some specific domains, but a general method for accomplishing this has not yet been refined. This article presents an exploration of this problem and developed a framework for mapping practical manufacturing knowledge into mathematical manufacturability constraints in mechanical design problem formulations. The steps for completing this mapping and the enforcing the constraints are discussed and demonstrated. Three case studies (a milled heat exchanger fin, a 3-D printed topologically-optimized beam, and a pulley requiring a hybrid additive-subtractive process for production) were completed to demonstrate the concepts; these concepts include problem formulation, the generation and enforcement of the manufacturability constraints, and fabrication of the resulting designs with and without constraints.

scholarly journals Identification of Roughness with Optimal Contact Response with respect to Real Contact Area and Normal Stiffness

2019 ◽  
Vol 2019 ◽  
pp. 1-11 ◽  
Author(s):  
Paolo Cinat ◽  
Marco Paggi ◽  
Giorgio Gnecco
Keyword(s):  
Mechanical Design ◽  
Optimization Methods ◽  
Real Contact Area ◽  
Mechanical Contact ◽  
Mechanical Responses ◽  
Real Contact ◽  
Manufacturing Technologies ◽  
Contact Response ◽  
Mechanical Design Problem

Additive manufacturing technologies are a key point of the current era of Industry 4.0, promoting the production of mechanical components via the addition of subsequent layers of material. Then, they may be also used to produce surfaces tailored to achieve a desired mechanical contact response. In this work, we develop a method to prototype profiles optimizing a suitable trade-off between two different target mechanical responses. The mechanical design problem is solved relying on both physical assumptions and optimization methods. An algorithm is proposed, exploiting an analogy between genetics and the multiscale characterization of roughness, where various length-scales are described in terms of rough profiles, named chromosomes. Finally, the proposed algorithm is tested on a representative example, and the topological and spectral features of roughness of the optimized profiles are discussed.

ROM Based Problem Formulation in Conceptual Design: Algorithm and Case Study

2014 ◽  
Author(s):  
Ronaldo Gutierrez ◽  
Yong Zeng ◽  
Xuan Sun ◽  
Suo Tan ◽  
Xiaoguang Deng ◽  
...  
Keyword(s):  
Natural Language ◽  
Conceptual Design ◽  
Design Problem ◽  
Quality Management System ◽  
Problem Formulation ◽  
Total Quality ◽  
Design Problems ◽  
Design Algorithm ◽  
Problem Formulations

Problem formulations in natural language imply imprecision, ambiguity, incompleteness, conflict and inconsistency between requirements in a design problem. Recursive Object Model (ROM) based problem formulation in conceptual design extracts complete product requirement from design problems structured initially in natural language. Since ROM carries certain semantic and syntactic information implied in natural language, it is used to formulate a design problem through a question asking approach. The scope of this paper is to present an updated algorithm, question templates, rules and detailed procedures to ask generic questions based on ROM representations. Generic questions are needed for the clarification and extension of the meaning of a design problem in order to overcome the imprecisions, ambiguities, conflicts and inconsistencies of problem descriptions in natural language. The updated algorithm, question templates, rules and detailed procedures for asking generic questions are used in a case study to formulate the development of a Total Quality Management system (TQMS).

Multi-Objective Optimization of an Autonomous Underwater Vehicle

2009 ◽  
Vol 43 (2) ◽  
pp. 48-60 ◽  
Author(s):  
M. Martz ◽  
W. L. Neu
Keyword(s):  
Design Space ◽  
Autonomous Underwater Vehicle ◽  
Underwater Vehicle ◽  
Design Problems ◽  
Single Measure ◽  
Design Variables ◽  
Complex Design ◽  
Final Design ◽  
Undersea Vehicle ◽  
Hierarchy Process

AbstractThe design of complex systems involves a number of choices, the implications of which are interrelated. If these choices are made sequentially, each choice may limit the options available in subsequent choices. Early choices may unknowingly limit the effectiveness of a final design in this way. Only a formal process that considers all possible choices (and combinations of choices) can insure that the best option has been selected. Complex design problems may easily present a number of choices to evaluate that is prohibitive. Modern optimization algorithms attempt to navigate a multidimensional design space in search of an optimal combination of design variables. A design optimization process for an autonomous underwater vehicle is developed using a multiple objective genetic optimization algorithm that searches the design space, evaluating designs based on three measures of performance: cost, effectiveness, and risk. A synthesis model evaluates the characteristics of a design having any chosen combination of design variable values. The effectiveness determined by the synthesis model is based on nine attributes identified in the U.S. Navy’s Unmanned Undersea Vehicle Master Plan and four performance-based attributes calculated by the synthesis model. The analytical hierarchy process is used to synthesize these attributes into a single measure of effectiveness. The genetic algorithm generates a set of Pareto optimal, feasible designs from which a decision maker(s) can choose designs for further analysis.

Proving the Labeled Interval Calculus for Inferences on Catalogs

1990 ◽  
Author(s):  
Walid Habib ◽  
Allen C. Ward
Keyword(s):  
Mechanical Design ◽  
Formal System ◽  
Constraint Propagation ◽  
Operating Conditions ◽  
Manufacturing Processes ◽  
Entire System ◽  
High Level Language ◽  
Design Problems ◽  
High Level ◽  
Interval Constraint

Abstract The “labeled interval calculus” is a formal system that performs quantitative inferences about sets of artifacts under sets of operating conditions. It refines and extends the idea of interval constraint propagation, and has been used as the basis of a program called a “mechanical design compiler,” which provides the user with a “high level language” in which design problems for systems to be built of cataloged components can be quickly and easily formulated. The compiler then selects optimal combinations of catalog numbers. Previous work has tested the calculus empirically, but only parts of the calculus have been proven mathematically. This paper presents a new version of the calculus and shows how to extend the earlier proofs to prove the entire system. It formalizes the effects of toleranced manufacturing processes through the concept of a “selectable subset” of the artifacts under consideration. It demonstrates the utility of distinguishing between statements which are true for all artifacts under consideration, and statements which are merely true for some artifact in each selectable subset.

Discovering Sequenced Origami Folding Through Nonlinear Mechanics and Topology Optimization

2019 ◽  
Vol 141 (4) ◽  
Author(s):  
Andrew S. Gillman ◽  
Kazuko Fuchi ◽  
Philip R. Buskohl
Keyword(s):  
Topology Optimization ◽  
Design Space ◽  
Optimization Algorithms ◽  
Element Model ◽  
Evolutionary Optimization ◽  
Nonlinear Mechanics ◽  
Design Problems ◽  
Mechanics Model ◽  
Highly Nonlinear ◽  
Evolutionary Optimization Algorithms

Origami folding provides a novel method to transform two-dimensional (2D) sheets into complex functional structures. However, the enormity of the foldable design space necessitates development of algorithms to efficiently discover new origami fold patterns with specific performance objectives. To address this challenge, this work combines a recently developed efficient modified truss finite element model with a ground structure-based topology optimization framework. A nonlinear mechanics model is required to model the sequenced motion and large folding common in the actuation of origami structures. These highly nonlinear motions limit the ability to define convex objective functions, and parallelizable evolutionary optimization algorithms for traversing nonconvex origami design problems are developed and considered. The ability of this framework to discover fold topologies that maximize targeted actuation is verified for the well-known “Chomper” and “Square Twist” patterns. A simple twist-based design is also discovered using the verified framework. Through these case studies, the role of critical points and bifurcations emanating from sequenced deformation mechanisms (including interplay of folding, facet bending, and stretching) on design optimization is analyzed. In addition, the performance of both gradient and evolutionary optimization algorithms are explored, and genetic algorithms (GAs) consistently yield solutions with better performance given the apparent nonconvexity of the response-design space.

Design Option Decision Tree: A Method for Schematic Analysis of a Design Problem and Integration of Human Factors Data

1974 ◽  
Vol 18 (3) ◽  
pp. 368-375
Author(s):  
William B. Askren ◽  
Kenneth D. Korkan
Keyword(s):  
Decision Tree ◽  
Human Factors ◽  
Design Problem ◽  
Aircraft Design ◽  
Decision Point ◽  
Specific Design ◽  
Design Problems ◽  
Design Option ◽  
Design Options ◽  
Evaluation Parameters

A Design Option Decision Tree (DODT) is a graphic means of showing the design options available at each decision point in the design process. Several examples of DODTs for aircraft design problems are shown. The procedures for developing a DODT are described. A proposed method for use of the DODT to resolve a design problem is presented. This method includes evaluating the design options in the Tree for impact on the system, and tracing paths through the Tree as dictated by specific design goals. The use of human factors data as one of the evaluation parameters is illustrated. The paper concludes with a discussion of other uses of a DODT.

The Mechanical Design of Large Turbogenerators

1987 ◽  
Vol 201 (2) ◽  
pp. 91-103
Author(s):  
B A Marlow
Keyword(s):  
High Speed ◽  
Mechanical Design ◽  
Rotating Machinery ◽  
Design Problems ◽  
Detail Design ◽  
Insight Into

Experience shows that the reliability of large turbogenerators depends substantially on the quality of detail design, particularly the quality of the mechanical design. In addition to the design problems common to all high-speed rotating machinery, the mechanical design of generators must take account of certain electrical requirements. This paper gives an insight into the detail mechanical design of large turbogenerators paying particular attention to the interaction of electrical requirements on the mechanical design.

Evaluating the Effectiveness of Problem Formulation and Ideation Skills Learned Throughout an Engineering Design Course

2015 ◽  
Author(s):  
Mahmoud Dinar ◽  
Yong-Seok Park ◽  
Jami J. Shah
Keyword(s):  
Engineering Design ◽  
Objective Assessment ◽  
Problem Formulation ◽  
Engineering Product ◽  
Design Problems ◽  
Web Based ◽  
Final Project ◽  
Design Projects ◽  
Design Skills ◽  
Long Course

Conventional syllabi of engineering design courses either do not pay enough attention to conceptual design skills, or they lack an objective assessment of those skills to show students’ progress. During a semester-long course of advanced engineering product design, we assigned three major design projects to twenty five students. For each project we asked them to formulate the problems in the Problem Formulator web-based testbed. In addition, we collected sketches for all three design problems, feasibility analyses for the last two, and a working prototype for the final project. We report the students’ problem formulation and ideation in terms of a set of nine problem formulation characteristics and ASU’s ideation effectiveness metrics respectively. We discuss the limitations that the choice of the design problems caused, and how the progress of a class of students during a semester-long design course resulted in a convergence in sets of metrics that we have defined to characterize problem formulation and ideation. We also review the results of students of a similar course which we reported last year in order to find common trends.

scholarly journals Performance Comparison of Recent Population-Based Metaheuristic Optimisation Algorithms in Mechanical Design Problems of Machinery Components

Machines ◽  
2021 ◽  
Vol 9 (12) ◽  
pp. 341
Author(s):  
Bugra Alkan ◽  
Malarvizhi Kaniappan Chinnathai
Keyword(s):  
Engineering Design ◽  
Mechanical Design ◽  
Search Algorithm ◽  
Computation Time ◽  
Population Based ◽  
Performance Comparison ◽  
Design Problems ◽  
Component Design ◽  
Engineering Design Problems ◽  
Optimisation Algorithms

The optimisation of complex engineering design problems is highly challenging due to the consideration of various design variables. To obtain acceptable near-optimal solutions within reasonable computation time, metaheuristics can be employed for such problems. However, a plethora of novel metaheuristic algorithms are developed and constantly improved and hence it is important to evaluate the applicability of the novel optimisation strategies and compare their performance using real-world engineering design problems. Therefore, in this paper, eight recent population-based metaheuristic optimisation algorithms—African Vultures Optimisation Algorithm (AVOA), Crystal Structure Algorithm (CryStAl), Human-Behaviour Based Optimisation (HBBO), Gradient-Based Optimiser (GBO), Gorilla Troops Optimiser (GTO), Runge–Kutta optimiser (RUN), Social Network Search (SNS) and Sparrow Search Algorithm (SSA)—are applied to five different mechanical component design problems and their performance on such problems are compared. The results show that the SNS algorithm is consistent, robust and provides better quality solutions at a relatively fast computation time for the considered design problems. GTO and GBO also show comparable performance across the considered problems and AVOA is the most efficient in terms of computation time.

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