Large assembly management is a burgeoning problem which is encountered in all the automotive industries. As the vehicle assemblies of projects moves towards the fruition stage its size becomes more than 50GB. It thus becomes very monolithic to manage, making easy tasks such as making minor changes in the assembly or performing analysis extremely difficult to perform, moreover the huge assembly size alone is not the only problem but even the presence of several other components in the assembly tend to hinder any task that is to be performed.

1. International Journal of Applied Engineering Research
ISSN 0973-4562 Volume 9, Number 21 (2014) pp. 9905-9910
© Research India Publications
http://www.ripublication.com
Paper Code: 26947-IJAER
Research in Large Assembly Management Methods
Mr. Akshay Shukla
Student, Symbiosis Institute of Technology, Pune.
(M) +91-9767621469 shukla.akshay.1993@gmail.com
Mr. Raj Singh
Student, Symbiosis Institute of Technology, Pune.
(M) +91-8888751695 singh.raj400607@gmail.com
Mr. Yash Parikh
Assistant Professor, Symbiosis Institute of Technology, Pune.
(M) +91-9561518898 yash.parikh@sitpune.edu.in
Abstract
Large assembly management is a burgeoning problem which is encountered in
all the automotive industries. As the vehicle assemblies of projects moves
towards the fruition stage its size becomes more than 50GB. It thus becomes
very monolithic to manage, making easy tasks such as making minor changes
in the assembly or performing analysis extremely difficult to perform,
moreover the huge assembly size alone is not the only problem but even the
presence of several other components in the assembly tend to hinder any task
that is to be performed.
First method to manage the size of large assemblies in CATIA is by using
Load as CATIA Graphical Representation (CGR) which is an option available
in TeamCenter Integration CATIA developed by EB solutions. CGR is a light
weight format which reduces the size of large assemblies, hence shows
significant improvement in any operations performed in CATIA and also
greatly reduces the loading time.
Second method to stall these issues from surfacing is by implementing
spatial query in the company’s standard operation procedure. Spatial query is a
tool which is available in the Digital Mock-up Navigator workbench of
CATIA which allows the user to make a selection (a choice of a part or a
product in the assembly), around the vicinity of which components are
selected and activated as per the user specified constraints of accuracy and
clearance.
A caveat of spatial query tool is that for “CATIA V5R21” the tool shows
some unexpected results when working with smaller assemblies. Both of the

2. 9906 Mr. Akshay Shukla et al
above mentioned tools can be simultaneously used hence influencing and
improving the performance of the software itself. Holistically these tools are
very effective and can be instrumental in managing large assembly datum for
the companies.
Keywords: Large Assembly Management, CATIA, Spatial Query, CGR,
Digital Mock-up.
Introduction
A typical vehicle assembly project size becomes more than 50GB towards fruition
stage, thus it becomes very monolithic to manage. Easy tasks such as making minor
changes, or performing analysis in the assembly becomes extremely difficult because
of the huge assembly size. Even the presence of several other components in the
assembly hinders tasks that needs to be performed on it.
Current Scenario
Currently all Original Equipment Manufacturers (OEMs) face the critical challenge of
managing large assemblies because of the constant ever changing complexities in
designs. Hence making the need to keep large assembly management techniques and
technologies abreast with large assemblies exigent.
As mentioned earlier a typical automobile assembly consumes roughly 50GB disk
space. While loading, it consumes drastically on the RAM of the workstation, thereby
increasing the loading time of the assembly. It may take several hours to load such
assemblies from FSC (File management system Server Cache) into FCC (File
management system Client Cache). Because of such massive size of data handling,
popular CAD softwares which industries possess such as CATIA, UG NX, Pro-E etc.,
tend to lag in their performance, deteriorating them to making even simple tasks
extremely difficult to perform. This mainly occurs because the workstation’s memory
is not able to cope up with the size of the large assemblies. In terms of FPS (Frames
per Second), its performance may drop down to 1 or 2 FPS or even worse.
Research Overview and Tool Working
Spatial query does not require any modeling history to calculate and perform the
query hence light weight formats can also be used with spatial query such as: CGR.
Spatial Query
The proximity query calculation is not based on the representation visualized in the
session. Rather, it is based on a cubic representation of each part, the size of the cubes
of which is designated by the accuracy parameter. Because of the way in which the
detection algorithm is designed, the real distance between two parts in the visual
representation could be greater than the clearance parameter you specify, yet the two

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parts could be sufficiently close as to be considered neighbours.
An increase of the
clearance value can be due to:
The cubic representation of the parts:
Maximum increase=2*accuracy* √3
The positioning error:
Maximum increase=0.5*accuracy* √3
The clearance value transformed into cubes:
Maximum increase= accuracy* √3
The sum of above three deltas gives:
Maximum increase= 3.5*accuracy* √3.
In the example below, the proximity query was made using an accuracy
parameter=30mm and a clearance parameter=0 mm, yet two parts separated by a
distance of ~46 mm were considered to be touching, therefore neighbours.[1]
Fig 1. Proximity Query Overview.

4. 9908 Mr. Akshay Shukla et al
Load as CGR
CGR (CATIA Graphical Representation) is a light weight format similar to: IGES
(Initial Graphics Exchange Specification),.JT (Jupiter tessellation) etc., CGR retains
only the graphical model of a component as a dummy and erases the modeling history
of the part. Moreover the CGR graphically represents the parts using cubical
tessellation, reducing the size of the CGR significantly.[2].
Results & Discussions
Load as CGR
Load testing for comparison between regular loading and CGR loading for a vehicle
layout.
Table 2. Load Testing.
Loading Method Total Time Taken Total Size (in GB)
Load as CGR (first run) 26 minutes 2.29
Load as CGR (consecutive run) 19 minutes -
Regular (first run) 1 hour 32 minutes 8.64
Regular (consecutive run) 1 hour 2 minutes -
Table 2. CGR Contribution
Loading Method No. of CGR files Total no. of files
Load as CGR (first run) 1642 2514
Load as CGR (consecutive run) - -
Regular (first run) - 2514
Regular (consecutive run) - -
It can be observed (see Table 1 and Table 2) how the size of the assembly has
been reduced by a factor of 3.8 and the total loading from the beginning of the loading
to graphical activation has been reduced by a factor of 3.53 for the first run and by a
factor of 3.3 for the consecutive loading. It can also be observed (see Table 2) that the
contribution of the CGR in the assembly is a key factor in reducing the assembly size
as in the current case the number of CGR is about 65.31% of the complete assembly.
Spatial Query
Spatial query, query time benchmarking between activated and not activated
assemblies.

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Table 3. Loaded as CGR for spatial query benchmarking
Selection for query Without Activation
(in sec.)
With Activation
(in sec.)
Cable Routing Interfaces 120 60
Thermal Clearance 60 50
Systemwise Interfaces and Nearby Parts 120 120
Articulation Envelop Clearance 60 70
(See Table 3.) It can be observed that the spatial query does not have a very
significant time difference when the assembly is activated and when it is not
activated. Hence the need to activate the terminal node is superseded.
Future Scope
Spatial Query allows the user to activate only a selected component to work on, also it
reduces the memory usage because only the selection is represented. This tool is
helpful for analysis purpose; like: in a complete automobile assembly it is very
important to know the clashes and clearances of various components from each other.
For Example:
1) If the selection is the fuel line, then it is very important to know the clearance of
any heating element or any rotating component from it in the assembly for which
spatial query can be performed with the required constrains of clearance and any
part or assembly which gets activated after the run of the query is needed to be
reconditioned in order to avoid any hazardous conditions at the later stages of
product development. Hence saving both time and money for the development of
the product.
2) Spatial Query allows the users to clash check with other user’s components.
3) For contextual designing, designers require reference surfaces, for which they
need to publish other designer’s part’s surface. In order to identify concerning
parts in the vicinity, spatial query can be instrumental.
The load as CGR feature can be effectively used to manage large assemblies for
OEMs. As mentioned above, it can reduce the loading time which in turn helps in the
faster operation of CATIA.
The advantages stated above explicitly indicate that the implementation of both
spatial query and load as CGR in the company’s standard operation procedure as a
large assembly management technique can noticeably ameliorate the performance and
lissomness of large assemblies in CATIA allowing the user to be able to tinker with
more ease while adhering to the specifications provided. CGR would also reduce the
cost per workstation that company has to invest as high RAM for each workstation
will not be required.

6. 9910 Mr. Akshay Shukla et al
Conclusion
Despite the minor shortcomings of the spatial query tool with smaller assemblies,
holistically both these tools have proved to be very useful in managing large
assemblies by allowing the users to be able to load only required components as CGR,
from large assemblies saving time, memory etc.
Acknowledgements
The authors would like to present their sincere gratitude towards the faculty of
Mechanical Engineering at Symbiosis Institute of Technology, Pune. Also, this work
was supported in part by Mr. Lakshmi Narasimhan, Sr. Manager, PLM, Mahindra
Research Valley, Chennai, Tamil Nadu, India.
References
[1] CATIA V5R21-Hand Book, Spatial Query, Edition: 2011.
[2] Teamcenter CATIA Integration 8.3.2.3-Hand Book, Edition: 2011.