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.

ASUPPA: A Framework for Interactive and Iterative Synthesis and Improvement of Process Plans

2000 ◽  
Author(s):  
Xiaomin Li ◽  
Subbarao Kambhampati ◽  
Jami Shah
Keyword(s):  
Process Planning ◽  
Search Space ◽  
Organizational Resistance ◽  
Context Sensitive ◽  
Process Plans ◽  
Search Mechanism ◽  
Planning Framework ◽  
Planning Methods ◽  
Complete Automation ◽  
Iterative Synthesis

Abstract The limited success and acceptance of automated process planning methods in the industry can be traced to the fact that most existing approaches aim at complete automation. We believe that the quest for complete automation is flawed, both because in practice optimality metrics for process plans are context-sensitive, and because there is significant organizational resistance to approaches that completely eliminate humans from the process planning framework. In this paper, we present an interactive and iterative planning framework, called ASUPPA, which focuses instead on providing intelligent assistance to a human process planner. After generating a “good” default process plan, ASUPPA engages in a “present – elicit criticism – revise” loop with an expert process planner. To operate successfully, ASUPPA needs access to the full search space of process plans, and have the ability to incrementally modify plans in response to expert criticism. The former is provided by basing ASUPPA on ASU Features Testbed, a comprehensive and systematic framework for recognizing and reasoning with features in machinable parts. To support the latter, the system is equipped with an iterative and interactive search mechanism. We will discuss the operational details of the resultant system, called ASUPPA.

Automated process planning: reasoning from first principles based on geometric relation constraints

1993 ◽  
Vol 7 (3) ◽  
pp. 159-179 ◽  
Author(s):  
Cornelius Nevrinceanu ◽  
Vassilios Morellas ◽  
Max Donath
Keyword(s):  
Process Planning ◽  
First Principles ◽  
Constraint Propagation ◽  
Planning Strategy ◽  
Part Geometry ◽  
Geometric Tolerances ◽  
Process Plans ◽  
Automated Process Planning ◽  
Geometric Relation ◽  
Automated Process

While previous work in automated process planning established plan ordering on an empirical basis alone, we derive our process plans based on the Holding-Under-Uncertainty Principle. We will introduce the principle, and we will describe the operational requirements needed to make this principle implementable in practice. The principle takes into account the form and geometric tolerances needed to locate features in deriving plan steps. Rather than just focusing on technological features, our planning strategy is controlled by the geometric relationships among features. By implementing a constraint propagation paradigm, we ensure that the tolerances accumulated in generating the part geometry remain within the tolerances specified by the design.

scholarly journals Multi-criteria planning model of engines parts additive manufacturing

2018 ◽  
Vol 224 ◽  
pp. 01119 ◽  
Author(s):  
Victoria Kokareva ◽  
Anton Agapovichev ◽  
Anton Sotov ◽  
Vitaliy Smelov ◽  
Vadim Sufiiarov
Keyword(s):  
Decision Making ◽  
Additive Manufacturing ◽  
Literature Review ◽  
Process Planning ◽  
Planning Process ◽  
State Of The Art ◽  
The State ◽  
Planning Model ◽  
Additive Process ◽  
Planning Methods

This paper reviews the state-of-the-art of an additive process planning methods amd models. Paper deals with the literature review of the planning process of additive manufacturing. The study also demonstrate multi-criteria planning model of engines parts additive manufacturing using multi-attributes decision-making problems approach.

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.

Agent-Based NC Process Planning for Complete Machining on Turning Centers

2000 ◽  
Author(s):  
Alfred Storr ◽  
Rui Li ◽  
Hansjoerg Stroehle
Keyword(s):  
Process Planning ◽  
Production Efficiency ◽  
Agent Based ◽  
Agent Theory ◽  
Process Plans ◽  
New Strategy ◽  
Planning Methods ◽  
Planning Task ◽  
Central Algorithm ◽  
Complex Planning

Abstract The application of turning centers for complete machining greatly increases production efficiency by means of introducing new machining possibilities. At the same time, it makes the generation of NC process plans more complicated and as a result the current process planning methods often fail in dealing with the new requirements. Based on agent theory this paper presents a new strategy for distributing a complex planning task to different relatively small planning units, so-called agents, which are defined considering both machine and workpiece structure. Instead of a central algorithm the agent based planning method generates NC process plans through some cooperative activities between different agents. The activity model and the cooperation rule are also discussed in detail.

scholarly journals A Feedrate Planning Method for the NURBS Curve in CNC Machining Based on the Critical Constraint Curve

2021 ◽  
Vol 11 (11) ◽  
pp. 4959
Author(s):  
Peng Guo ◽  
Yijie Wu ◽  
Guang Yang ◽  
Zhebin Shen ◽  
Haorong Zhang ◽  
...  
Keyword(s):  
Planning Method ◽  
Cnc Machining ◽  
Arc Length ◽  
Kinematic Constraint ◽  
Nurbs Curve ◽  
Planning Strategy ◽  
Feedrate Planning ◽  
Curvature Constraint ◽  
Planning Methods ◽  
The Relationship

The curvature of the NURBS curve varies along its trajectory, therefore, the commonly used feedrate-planning method, which based on the acceleration/deceleration (Acc/Dec) model, is difficult to be directly applied in CNC machining of a NURBS curve. To address this problem, a feedrate-planning method based on the critical constraint curve of the feedrate (CCC) is proposed. Firstly, the problems of existing feedrate-planning methods and their causes are analyzed. Secondly, by considering both the curvature constraint and the kinematic constraint during the Acc/Dec process, the concept of CCC which represents the relationship between the critical feedrate-constraint value and the arc length is proposed. Then the CCC of a NURBS curve is constructed, and it has a concise expression conforming to the Acc/Dec model. Finally, a feedrate-planning method of a NURBS curve based on CCC and the Acc/Dec model is established. In the simulation, a comparison between the proposed method and the conventional feedrate-planning method is performed, and the results show that, the proposed method can reduce the Acc/Dec time by over 40%, while little computational burden being added. The machining experimental results validate the real-time performance and stability of the proposed method, and also the machining quality is verified. The proposed method offers an effective feedrate-planning strategy for a NURBS curve in CNC machining.

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