Imperial College London
Portrait Picture

Dr Ajit Panesar

Faculty of Engineering, Department of Aeronautics

Senior Lecturer
 
 
 
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Contact

 

a.panesar Website

 
 
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Location

 

216City and Guilds BuildingSouth Kensington Campus

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Summary

 

Publications

Citation

BibTex format

@article{Araújo:2020:10.1080/00207543.2019.1686187,
author = {Araújo, LJP and Panesar, A and Özcan, E and Atkin, J and Baumers, M and Ashcroft, I},
doi = {10.1080/00207543.2019.1686187},
journal = {International Journal of Production Research},
pages = {6917--6933},
title = {An experimental analysis of deepest bottom-left-fill packing methods for additive manufacturing},
url = {http://dx.doi.org/10.1080/00207543.2019.1686187},
volume = {58},
year = {2020}
}
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RIS format (EndNote, RefMan)

TY  - JOUR
AB  - The adoption of Additive Manufacturing (AM) technology requires the efficient utilisation of the avail- able build volumes to minimise production times and costs. Three-dimensional algorithms, particularly the Deepest Bottom-Left-Fill (DBLF) heuristic, have been extensively used to tackle the problem of packing arbitrary 3D geometries within the AM sector. A particularly common method applied to more realistic packing problems is the combination of DBLF and metaheuristics such as Genetic Algorithms (GAs). Through a series of experiments, this paper experimentally investigates the practical aspects, and comparative performance of different DBLF based methods including a brute force algorithm and GA combined with DBLF for AM build volume packing. The insights into the relationship between algorithm efficiency (in terms of volume utilisation), simulation runtime, and practical requirements, in particular geometry rotation constraints are investigated. In addition to providing an increased comprehension of the practical aspects of applying DBLF algorithms in the AM context, this study confirms the limita- tions of traditional DBLF and the requirements for more flexible and intelligent placement strategies while experimentally demonstrating that higher degrees of freedom for part rotation contribute to small improvements in volume density. The resulting additional computational effort discourages this strategy, however.
AU  - Araújo,LJP
AU  - Panesar,A
AU  - Özcan,E
AU  - Atkin,J
AU  - Baumers,M
AU  - Ashcroft,I
DO  - 10.1080/00207543.2019.1686187
EP  - 6933
PY  - 2020///
SN  - 0020-7543
SP  - 6917
TI  - An experimental analysis of deepest bottom-left-fill packing methods for additive manufacturing
T2  - International Journal of Production Research
UR  - http://dx.doi.org/10.1080/00207543.2019.1686187
VL  - 58
ER  -
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