Topological Information Content and Expressiveness of Function Models in Mechanical Design

2010 ◽  
Vol 10 (3) ◽  
Author(s):  
Chiradeep Sen ◽  
Joshua D. Summers ◽  
Gregory M. Mocko
Keyword(s):  
Engineering Design ◽  
Information Content ◽  
Model Comparison ◽  
Graphical Representation ◽  
Mechanical Design ◽  
Unconditional Probability ◽  
Function Model ◽  
Topological Information ◽  
Grammar Rules ◽  
Function Models

In this paper, two approaches for computing the topological information content of function models in mechanical engineering design are developed and compared. Previously, a metric for computing information content of functions and flows within function models was proposed. Here, this metric is evolved to include the information contained in the connections between flows and functions in a function model. The first approach is based on uniform unconditional probability of a flow connecting any two functions within the model. The second approach is based on additional knowledge that the functions and flows in a model have limited compatibility, thereby, reducing the choices for origin and destination functions for each flow. This additional knowledge is represented using a new graphical representation supported by syntactic grammar rules. Both approaches are then applied to an example function model. Comparison between the approaches shows that the inclusion of this additional knowledge increases the expressiveness by reducing the uncertainty associated with function models.

Topological Information Content and Expressiveness of Function Models in Mechanical Design

2009 ◽  
Author(s):  
Chiradeep Sen ◽  
Benjamin W. Caldwell ◽  
Joshua D. Summers ◽  
Gregory M. Mocko
Keyword(s):  
Engineering Design ◽  
Information Content ◽  
Model Comparison ◽  
Graphical Representation ◽  
Mechanical Design ◽  
Unconditional Probability ◽  
Function Model ◽  
Topological Information ◽  
Grammar Rules ◽  
Function Models

In this paper, two approaches for computing the topological information content of function models in mechanical engineering design are developed and compared. Previously a metric for computing information content of functions and flows within function models was proposed. Here this metric is adapted to compute the information contained in the resulting connections of flows between functions in a function model. The first approach is based on uniform unconditional probability of a flow connecting any two functions within the model. The second approach is based on additional knowledge that the functions and flows in a model have limited compatibility, thereby reducing the choices for origin and destination functions for each flow. This additional knowledge is represented using a new graphical representation supported by syntactical grammar rules. Both approaches are then applied to an example function model. Comparison between the approaches shows that the inclusion of compatibility knowledge increases the expressiveness of function representations and reduces the uncertainty of function models.

An Approach for Measuring Information Content of Textual Engineering Requirements Using a Form-Neutral Representation

2014 ◽  
Author(s):  
Chiradeep Sen ◽  
Alolika Mukhopadhyay ◽  
John Fields ◽  
Farhad Ameri
Keyword(s):  
Content Analysis ◽  
Natural Language ◽  
Engineering Design ◽  
Information Content ◽  
Mechanical Design ◽  
Ordinal Scale ◽  
Design Engineering ◽  
Design Requirements ◽  
Design Documents ◽  
Representation Formalism

This paper demonstrates a generic approach for measuring the information content of artifacts produced and used in early stages of mechanical design. Engineering design requirements are selected for information content analysis for illustration. In this method, requirements in natural language are translated to an Entity-Relation-Attribute-Value (ERAV) model composed of well-defined elements. A protocol for this translation is proposed and validated. Four different metrics, based on raw element count, count weighted by arbitrary ordinal scale, count weighted by node cardinality, and Shannon’s entropy are then applied to the ERAV model for measuring information content. The method proposed is generic enough to be applied to most design documents that use natural language as the knowledge representation formalism.

The Roles of Features and Abstraction in Mechanical Design

1994 ◽  
Author(s):  
LeRoy E. Taylor ◽  
Mark R. Henderson
Keyword(s):  
Life Cycle ◽  
Engineering Design ◽  
Design Process ◽  
Design Research ◽  
Mechanical Design ◽  
Product Modeling ◽  
Product Models ◽  
Mechanical Products ◽  
Unique Framework ◽  
The Relationship

Abstract This paper describes the roles of features and abstraction mechanisms in the mechanical design process, mechanical designs, and product models of mechanical designs. It also describes the relationship between functions and features in mechanical design. It is our experience that many research efforts exist in the areas of design and product modeling and, further, that these efforts must be cataloged and compared. To this end, this paper culminates with the presentation of a multi-dimensional abstraction space which provides a unique framework for (a) comparing mechanical engineering design research efforts, (b) relating conceptual objects used in the life cycle of mechanical products, and (c) defining a product modeling space.

A Statistical Adaptable Distribution Function Model for Low Probabilities of Failure

1993 ◽  
Author(s):  
Suryaji R. Bhonsle ◽  
Paul Thompson
Keyword(s):  
Experimental Data ◽  
Distribution Function ◽  
Experimental Results ◽  
Function Model ◽  
Log Normal ◽  
Function Models

Abstract Weibull, log normal, and some other Distribution function models (D.F.M.) have a tendency to deviate from experimental results. This deviation, either exceedingly conservative or nonconservative, is amplified at low probabilities of failure. To remedy such problems a new D.F.M. is derived. It is then used to predict low probabilities of failure. The predictions are consistent with experimental data and are not too conservative or too nonconservative.

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.

Team-Roles in Mechanical Design

1996 ◽  
Author(s):  
Ralf Stetter ◽  
David G. Ullman
Keyword(s):  
Design Process ◽  
Collaborative Design ◽  
Team Member ◽  
Graphical Representation ◽  
Mechanical Design ◽  
Physical Activities ◽  
Video Tape ◽  
Team Behavior ◽  
Role Taking ◽  
Role Profile

Abstract This paper presents an approach for identifying team-roles. The proposed approach is based on the interpretation of a design process in terms of the behavior of the members of the team. Behavior is codified in terms of the team member’s process and physical activities. In this study a collaborative design process was recorded on video-tape and analyzed in detail. The process was decomposed into distinct sections called events. In every event each team member was assigned a team-role taking into consideration the activity of the team member, i.e. what the team member does, how activity of the team member, i.e. what the team member does, how the team member does it, and the context of the event. A graphical representation of the results called ‘role-profile’ was developed making it possible to clearly identify a basic team-role for every subject in the observed design process.

A Blackboard Architecture to Support Case-Based Reasoning in Mechanical Design

1992 ◽  
Author(s):  
Theodore Bardsz ◽  
Ibrahim Zeid
Keyword(s):  
Problem Solving ◽  
Engineering Design ◽  
Mechanical Design ◽  
Maximum Amount ◽  
Design Solution ◽  
Case Based Reasoning ◽  
Design Problems ◽  
Engineering Design Problems ◽  
Design Plan ◽  
Case Based

Abstract One of the most significant issues in applying case-based reasoning (CBR) to mechanical design is to integrate previously unrelated design plans towards the solution of a new design problem. The total design solution (the design plan structure) can be composed of both retrieved and dynamically generated design plans. The retrieved design plans must be mapped to fit the new design context, and the entire design plan structure must be evaluated. An architecture utilizing opportunistic problem solving in a blackboard environment is used to map and evaluate the design plan structure effectively and successfuly. The architecture has several assets when integrated into a CBR environment. First, the maximum amount of information related to the design is generated before any of the mapping problems are addressed. Second, mapping is preformed as just another action toward the evaluation of the design plan. Lastly, the architecture supports the inclusion of memory elements from the knowledge base in the design plan structure. The architecture is implemented using the GBB system. The architecture is part of a newly developed CBR System called DEJAVU. The paper describes DEJAVU and the architecture. An example is also included to illustrate the use of DEJAVU to solve engineering design problems.

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