Case-Based Retrieval Approach of Supporting Process Planning in Layer-Based Additive Manufacturing

2007 ◽  
Author(s):  
Sungshik Yim ◽  
David Rosen
Keyword(s):  
Additive Manufacturing ◽  
Process Planning ◽  
Description Logic ◽  
Retrieval Method ◽  
Storage And Retrieval ◽  
Process Plans ◽  
Requirements Process ◽  
Design And Manufacturing ◽  
Design Requirements ◽  
Case Based

The process planning task for a given design problem in additive manufacturing can be greatly enhanced by referencing previously developed process plans. In this research, a case-based retrieval method, called the DFM (Design For Manufacturing) framework, that retrieves previously formulated process plans is proposed to support process planning. To support the DFM Framework, we have developed an information model (ontology) of manufacturing process knowledge in the domain of additive manufacturing processes, including design requirements, process plans, and rules that map requirements to plans. Description Logic (DL) is identified as an appropriate mathematical formalism to encode the ontology and realize the computational mapping between the design and manufacturing domains. Storage and retrieval algorithms are presented that, first, structure the repository of previous DFM problems and, second, enable DFM problems to be retrieved.

A Framework for Self-Realizing Process Models for Additive Manufacturing

2011 ◽  
Author(s):  
Sungshik Yim ◽  
David W. Rosen
Keyword(s):  
Neural Network ◽  
Additive Manufacturing ◽  
Process Planning ◽  
Process Model ◽  
Selective Laser Sintering ◽  
Process Models ◽  
Clustering Methods ◽  
In Series ◽  
Design Requirements ◽  
Planning Problems

This research discusses a framework for automating process model realization for additive manufacturing. The models map relationships from design requirements to process variables and can be utilized for future process planning. A repository is employed to collect data and contains previous process plans and corresponding design requirements. The framework organizes data through a statistical clustering method and builds regression models using a multi-layer neural network. Hierarchical and k-means clustering methods are employed in series to manage the data. A two layer neural network and augmented training algorithm are employed to build process models. The framework has been tested with Stereolithography and Selective Laser Sintering process planning problems to demonstrate its usefulness.

Knowledge Management With an Intelligent Tool for Additive Manufacturing

2015 ◽  
Author(s):  
Douglas Eddy ◽  
Sundar Krishnamurty ◽  
Ian Grosse ◽  
Maxwell Perham ◽  
Jack Wileden ◽  
...  
Keyword(s):  
Additive Manufacturing ◽  
Process Planning ◽  
Description Logic ◽  
Product Information ◽  
Salient Feature ◽  
Spur Gear ◽  
Structural Framework ◽  
Traditional Manufacturing ◽  
Ontological Framework ◽  
Optimal Set

Manufacturers face the challenge of deciding when additive manufacturing technology offers a suitable process to produce a given product. Information needed about process capabilities is constantly evolving and usually not organized well enough to support such decisions. This work introduces an ontological framework which identifies and semantically models the most applicable concepts of additive manufacturing relevant to process planning applications. Another salient feature includes the fit of this structural framework with both the new ASTM standard for additive manufacturing vocabulary and existing taxonomies for traditional manufacturing processes. Finally, within this framework we implemented description logic rules to identify the optimal set of processes for a product, the rationale for selecting this set of processes, and a logical link between a product’s features and its process plan. The reliability of the knowledge representation and its process planning capabilities are each tested and demonstrated by a case study example of the selection of the best processes to produce a steel spur gear.

Tolerance Analysis for Validating Manufacturing Process Plans

2014 ◽  
Author(s):  
Wentao Fu ◽  
Saigopal Nelaturi ◽  
Arvind Rangarajan ◽  
Tolga Kurtoglu
Keyword(s):  
Process Planning ◽  
Manufacturing Process ◽  
Degrees Of Freedom ◽  
Tolerance Analysis ◽  
Manufacturing Tolerance ◽  
Process Plans ◽  
Novel Approach ◽  
Manufacturing Process Planning ◽  
Design And Manufacturing ◽  
Engineering Constraints

In manufacturing process planning, it is critical to ensure that the part generated from a process plan complies with tolerances specified by designers to meet engineering constraints. Manufacturing errors are stochastic in nature and are introduced at almost every stage of executing a plan, for example due to inaccuracy of tooling, misalignment of location, distortion of clamping etc. Furthermore, these errors accumulate or ‘stack-up’ as the manufacturing process progresses to inevitably produce a part that varies from the designed model. The resultant variation should be within prescribed design tolerances. In this work, we present a novel approach for validating process plans using 3D tolerance stack-up analysis by representing variations of nominal features in terms of extents of their degrees of freedom within design and manufacturing tolerance zones. We will show how the manufacturing error stack-up can be effectively represented by composition and intersection of these transformations. We demonstrate several examples with different tolerance specifications to show the applicability of our approach for process planning.

Research on Automobile Panel Case Retrieval Methodology

2009 ◽  
Vol 16-19 ◽  
pp. 1318-1323
Author(s):  
Xian Liang Zong ◽  
Ping Wang ◽  
Hui Zheng
Keyword(s):  
Process Planning ◽  
Case Based Reasoning ◽  
Retrieval Method ◽  
Stamping Process ◽  
Automobile Panel ◽  
Automotive Panel ◽  
Stamping Process Planning ◽  
Reasoning Technique ◽  
Case Based

CBR (Case-based reasoning) technique is increasingly applied in the process planning and dies intelligent design for stamping parts. In these applications, stamping parts information acts as the problem domain of cases model, while stamping process and die information as the answer domain. The similarity computation and retrieval of stamping parts are essential to the case-based design of stamping process planning and dies. In this paper, that issue is studied targeting automotive panel as the research object, and a retrieval method for similar panel parts based on the automobile panel coding is proposed. The coding structure is designed considering the automobile panel's features, especially the geometry shape features and their relationship. And the corresponding similarity calculation method is put forward. Finally, a case study is used to reveal the effectiveness of this methodology.

Harnessing Process Variables in Additive Manufacturing for Design Using Manufacturing Elements

2020 ◽  
Vol 142 (7) ◽  
Author(s):  
Yi Xiong ◽  
Yunlong Tang ◽  
Sang-In Park ◽  
David W. Rosen
Keyword(s):  
Additive Manufacturing ◽  
Process Planning ◽  
Multiple Scales ◽  
Lattice Structure ◽  
Structure Property ◽  
Process Variables ◽  
Planning Strategy ◽  
Decision Tools ◽  
Process Plans ◽  
Planning Methods

Abstract Process plans in additive manufacturing (AM) have a profound impact on the performance of fabricated parts such as geometric accuracy and mechanical properties. Due to its layer-based, additive nature, AM processes can be controlled at multiple scales starting from the scan vector/pixel scale. However, most process planning methods in AM configure process settings at the part scale. This leaves large unexplored regions in the design space that may include optimal designs. To address these untapped potentials, we present a process planning strategy based on the concept of manufacturing elements (MELs) to harness process variables at low scales for design. First, we decompose a part design into multiple MELs that contain geometric and manufacturing information. Two-scale process–structure–property (PSP) relationships are then constructed for MELs and their assembly. Decision tools, including the compromise decision support problem, are employed to navigate two-scale PSP relationships for supporting designers in design exploration on process variables and optimization of process plans. The proposed strategy is illustrated with a process planning example for a lattice structure, which has multiple design goals and is to be fabricated using material extrusion.

PROCASE: A Prototype of Intelligent Case-Based Process Planning System With Simulation Environment

1993 ◽  
Author(s):  
Hao Yang ◽  
Wen F. Lu
Keyword(s):  
Process Planning ◽  
Planning System ◽  
Simulation Environment ◽  
Rule Based ◽  
Process Plans ◽  
Integrated Methodology ◽  
Process Planning System ◽  
Machining Operations ◽  
User Friendly ◽  
Case Based

Abstract An intelligent case-based process planning system with interactive graphic simulation environment, PROCASE, is developed to demonstrate an integrated methodology of case-based process planning system. In PROCASE, both the mechanical part features and the machining operations are represented with a frame based scheme. PROCASE contains a retriever, a modifier, a simulator and a repairer. It distinguishes itself from traditional rule-based process planning systems by representing the process planning knowledge through previous process planning cases instead of production rules. It therefore can overcome some problems in the traditional rule-based expert systems. PROCASE currently resides in IRIS Indigo workstation. With a user friendly graphic environment, the generated process plans can be demonstrated vividly. This simulation environment not only serves as a good assistance in debugging, but also helps the user to be convinced of the outcomes of the reasoning of PROCASE.

scholarly journals Additive Manufacturing for Effective Smart Structures: The Idea of 6D Printing

2021 ◽  
Vol 5 (5) ◽  
pp. 119
Author(s):  
Stelios K. Georgantzinos ◽  
Georgios I. Giannopoulos ◽  
Panteleimon A. Bakalis
Keyword(s):  
Additive Manufacturing ◽  
Degrees Of Freedom ◽  
Smart Structures ◽  
Interaction Mechanism ◽  
Modeling And Simulations ◽  
Environmental Stimulus ◽  
Material Component ◽  
Design And Manufacturing ◽  
First Time ◽  
Printing Techniques

This paper aims to establish six-dimensional (6D) printing as a new branch of additive manufacturing investigating its benefits, advantages as well as possible limitations concerning the design and manufacturing of effective smart structures. The concept of 6D printing, to the authors’ best knowledge, is introduced for the first time. The new method combines the four-dimensional (4D) and five-dimensional (5D) printing techniques. This means that the printing process is going to use five degrees of freedom for creating the final object while the final produced material component will be a smart/intelligent one (i.e., will be capable of changing its shape or properties due to its interaction with an environmental stimulus). A 6D printed structure can be stronger and more effective than a corresponding 4D printed structure, can be manufactured using less material, can perform movements by being exposed to an external stimulus through an interaction mechanism, and it may learn how to reconfigure itself suitably, based on predictions via mathematical modeling and simulations.

Automated Reuse of Solutions in Manufacturing Process Planning Through a Case-Based Approach

1996 ◽  
Author(s):  
M. Marefat ◽  
J. Britanik
Keyword(s):  
Process Planning ◽  
Manufacturing Process ◽  
Object Oriented ◽  
Process Plan ◽  
Primary Mechanism ◽  
Prismatic Parts ◽  
Manufacturing Process Planning ◽  
Computer Aided ◽  
Effective Use ◽  
Case Based

Abstract This research focuses on the development of an object-oriented case-based process planner which combines the advantages of the variant and generative approaches to process planning. The case-based process planner operates on general 3D prismatic parts, represented by a collection of features (eg: slots, pockets, holes, etc.). Each feature subplan is developed by the case-based planner. Then the feature subplans are combined into the global process plan for the part via a hierarchical plan merging mechanism. Abstracted feature subplans correspond to cases, which are used in subsequent planning operations to solve new problems. The abstracting and storing of feature subplans as cases is the primary mechanism by which the planner learns from its previous experiences to become more effective and efficient. The computer-aided process planner is designed to be extensible and flexible through the effective use of object-oriented principles.

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