Consideration of sustainable reverse engineering process based on system efficiency and its effectiveness

2021 ◽  
Vol 2021 (0) ◽  
pp. 303
Author(s):  
Katsuhiko Saiga ◽  
AMM Sharif Ullah ◽  
Akihiko Kubo
Keyword(s):  
Reverse Engineering ◽  
System Efficiency ◽  
Engineering Process

Augmenting Tools for Reverse Engineering Methods

2006 ◽  
Author(s):  
Mark Snider ◽  
Sudhakar Teegavarapu ◽  
D. Scott Hesser ◽  
Joshua D. Summers
Keyword(s):  
Reverse Engineering ◽  
Black Box ◽  
House Of Quality ◽  
Engineering Process ◽  
Design Efficiency ◽  
Design For Manufacture ◽  
The Past ◽  
Cad Models ◽  
Product And Process ◽  
A Company

Reverse engineering has gained importance over the past few years due to an intense competitive market aiding in the survivability of a company. This paper examines the reverse engineering process and what, how, and why it can assist in making a better design. Two well known reverse engineering methodologies are explored, the first by Otto and Wood and the second by Ingle. Each methodology is compared and contrasted according to the protocols and tools used. Among some of the reverse engineering tools detailed and illustrated are: Black box, Fishbone, Function Structure, Bill of Material, Exploded CAD models, Morphological Matrix, Subtract and Operate Procedure (SOP), House of Quality matrix, and FMEA. Even though both methodologies have highly valued tools, some of the areas in reverse engineering need additional robust tooling. This paper presents new and expanded tooling to augment the existing methods in hopes of furthering the understanding of the product, and process. Tools like Reverse Failure Mode and Effects Analysis (RFMEA), Connectivity graphs, and inter-relation matrix increase the design efficiency, quality, and the understanding of the reverse engineering process. These tools have been employed in two industry projects and one demonstrative purpose for a Design for Manufacture Class. In both of these scenarios, industry and academic, the users found that the augmented tools were useful in capturing and revealing information not previously realized.

Aspect Mining Based on Object-Oriented Systems’ Dynamic Behavior Models

2010 ◽  
Vol 40-41 ◽  
pp. 873-876
Author(s):  
Hua Chu ◽  
Qing Shan Li ◽  
Shen Ming Hu ◽  
Ping Chen
Keyword(s):  
Reverse Engineering ◽  
Dynamic Behavior ◽  
Object Oriented ◽  
Engineering Process ◽  
Aspect Mining ◽  
Crosscutting Concerns ◽  
Systematic Experiment ◽  
Statechart Diagram ◽  
Object Oriented Systems ◽  
Behavior Models

Aspect mining is a reverse engineering process that aims at finding crosscutting concerns in existing systems. This paper describes an aspect mining approach making use of the results of reverse engineering, statechart diagram, to aid in the understanding of an object-oriented software system’s behaviors. An aspect based on the recovered statechart diagram is defined as a set of states and an event. These states will transit to the same state after they send the event. Finally, systematic experiment is conducted in the paper in order to verify the correctness and validity of this approach.

A reverse engineering process for design level document production from ADA code

1991 ◽  
Vol 15 (10) ◽  
pp. 531-542
Author(s):  
G Canfora ◽  
A Cimitile ◽  
U De Carlini
Keyword(s):  
Reverse Engineering ◽  
Engineering Process

scholarly journals Reverse engineering process of cryostat components of Wendelstein 7-X

2009 ◽  
Vol 84 (7-11) ◽  
pp. 1558-1561 ◽  
Author(s):  
Tamás Rajna ◽  
Friedemann Herold ◽  
Christophe Baylard
Keyword(s):  
Reverse Engineering ◽  
Engineering Process

Customized Software Tools Integrated in Reverse Engineering Process of Rectangular Parts with Holes

2013 ◽  
Vol 371 ◽  
pp. 473-477 ◽  
Author(s):  
Gheorghe Oancea ◽  
Alexandru Manolescu ◽  
Iulian Bădan ◽  
Roxana Pescaru
Keyword(s):  
Reverse Engineering ◽  
Software Tools ◽  
Geometrical Parameters ◽  
Rotational Axis ◽  
Engineering Process ◽  
Internal Surfaces ◽  
Solid Models ◽  
Rotational Part ◽  
Design And Manufacture ◽  
Cloud Of Points

This paper presents how in the Reverse Engineering process can be integrated specific software tools, developed by the authors, which allow for digitized rectangular parts with internal surfaces of revolution, to obtain solid models and CNC program. The first tool named Rotational Axis Primitives and Recognition has implemented a set of algorithms and it is used for recognizing, from a cloud of points associated with a rotational part, the axis and geometrical parameters. The second tool named Hole_Application is created for forward engineering and it can be used to design and manufacture the industrial products with rectangular shape using intelligent technological objects for holes.

Reverse Engineering Process for the Generation of UML Diagrams in Web Services Composition

2015 ◽  
pp. 177-187
Author(s):  
Isaac Machorro-Cano ◽  
Yaralitset López-Ramírez ◽  
Mónica Guadalupe Segura-Ozuna ◽  
Giner Alor-Hernández ◽  
Lisbeth Rodríguez-Mazahua
Keyword(s):  
Web Services ◽  
Reverse Engineering ◽  
Web Services Composition ◽  
Engineering Process ◽  
Services Composition ◽  
Uml Diagrams

COMPREHENSIVE PROPERTY DETERMINATION FOR FIBER-REINFORCED POLYMER COMPOSITES IN EXTRUSION DEPOSITION ADDITIVE MANUFACTURING—BAYESIAN VS DETERMINISTIC This work introduces both deterministic and Bayesian methodologies to simultaneously determine the elastic constants of the constituent polymer and the fiber orientation state in a short fiber-reinforced polymer (SFRP) composite based on a small number of experimental measurements of the composite properties. The ability of the Bayesian approach to calibrate uncertainties makes it a promising tool for enabling a probabilistic framework for composites manufacturing digital twins. The two methods that enable the reverse engineering of the orientation of the fibers and the in-situ polymer properties are compared. For the extrusion deposition additive manufacturing (EDAM) process and other SFRP composites processes (e.g. injection molding), extensive characterization efforts are currently required to develop composites manufacturing digital twins. To circumvent the extensive characterization required, Digimat© provides a suite of tools to reverse engineer material properties of SFRPs. However, Digimat© lacks a methodology to inversely determine the fiber orientation state and the constituent polymer properties simultaneously. To that end, this work presents both a deterministic and hierarchical Bayesian approaches to determine the polymer properties and the fiber orientation state simultaneously. The results indicate that both approaches provide a reliable framework for the reverse engineering process. The deterministic approach provides a more rapid, point estimate methodology, whereas the Bayesian approach provides a more comprehensive methodology that includes uncertainties in the reverse engineering process. This work introduces both deterministic and Bayesian methodologies to simultaneously determine the elastic constants of the constituent polymer and the fiber orientation state in a short fiber-reinforced polymer (SFRP) composite based on a small number of experimental measurements of the composite properties. The ability of the Bayesian approach to calibrate uncertainties makes it a promising tool for enabling a probabilistic framework for composites manufacturing digital twins. The two methods that enable the reverse engineering of the orientation of the fibers and the in-situ polymer properties are compared. For the extrusion deposition additive manufacturing (EDAM) process and other SFRP composites processes (e.g. injection molding), extensive characterization efforts are currently required to develop composites manufacturing digital twins. To circumvent the extensive characterization required, Digimat© provides a suite of tools to reverse engineer material properties of SFRPs. However, Digimat© lacks a methodology to inversely determine the fiber orientation state and the constituent polymer properties simultaneously. To that end, this work presents both a deterministic and hierarchical Bayesian approaches to determine the polymer properties and the fiber orientation state simultaneously. The results indicate that both approaches provide a reliable framework for the reverse engineering process. The deterministic approach provides a more rapid, point estimate methodology, whereas the Bayesian approach provides a more comprehensive methodology that includes uncertainties in the reverse engineering process.

2021 ◽  
Author(s):  
AKSHAY J. THOMAS, ◽  
EDUARDO BAROCIO ◽  
ILIAS BILIONIS ◽  
R. BYRON PIPES
Keyword(s):  
Reverse Engineering ◽  
Bayesian Approach ◽  
Fiber Orientation ◽  
Engineering Process ◽  
Composites Manufacturing ◽  
Reinforced Polymer ◽  
Digital Twins ◽  
Polymer Properties ◽  
Orientation State ◽  
The Bayesian Approach

This work introduces both deterministic and Bayesian methodologies to simultaneously determine the elastic constants of the constituent polymer and the fiber orientation state in a short fiber-reinforced polymer (SFRP) composite based on a small number of experimental measurements of the composite properties. The ability of the Bayesian approach to calibrate uncertainties makes it a promising tool for enabling a probabilistic framework for composites manufacturing digital twins. The two methods that enable the reverse engineering of the orientation of the fibers and the in-situ polymer properties are compared. For the extrusion deposition additive manufacturing (EDAM) process and other SFRP composites processes (e.g. injection molding), extensive characterization efforts are currently required to develop composites manufacturing digital twins. To circumvent the extensive characterization required, Digimat© provides a suite of tools to reverse engineer material properties of SFRPs. However, Digimat© lacks a methodology to inversely determine the fiber orientation state and the constituent polymer properties simultaneously. To that end, this work presents both a deterministic and hierarchical Bayesian approaches to determine the polymer properties and the fiber orientation state simultaneously. The results indicate that both approaches provide a reliable framework for the reverse engineering process. The deterministic approach provides a more rapid, point estimate methodology, whereas the Bayesian approach provides a more comprehensive methodology that includes uncertainties in the reverse engineering process.

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