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The
collaborative engineering framework also yields an important
by-product: a vast amount of data and information captured in
digital form during development of several generations of
products. Special data mining tools can be used to process the
accumulated data and produce new knowledge. All such information
and knowledge can be made accessible over the network, and used in
developing future generations of products. Knowledge Management
(KM) is in fact, rapidly becoming an important part of Product
Lifecycle Management.
The focus of PLM on engineering data and knowledge, contrasts with
enterprise resource planning, supply chain management and customer
relationship management, which largely handle business process
data. There is however, an increasing overlap between the systems
and the distinctions are gradually blurring. In future, it is
likely that the systems will have seamless connections and data
exchanges with each other, and will provide access to any relevant
data through a standard (but customisable) user interface.
Research Initiatives at IIT Bombay
Our R&D focus is on developing a systematic approach and software
tools for collaborative engineering of cast components used in
automobile, aerospace, farming, mining, machine tools, electrical,
consumer, and other products. Over the last one decade, several
elements of a framework code–named WebICE (Web-based Intelligent
Collaborative Engineering) have been developed and used for
solving industrial problems. The framework allows product, tooling
and manufacturing engineers to design, analyse, and improve a
casting for lower cost and higher quality assurance using software
tools and Internet. The backbone of the system is an XML-based casting data mark-up
language (CDML), which captures over 2000 different items of
information about a casting project. The items range from part
geometric parameters to material properties, tooling element
designs, process plans, and costing details. Other files
containing 2D images, 3D models, library options, and
knowledge-bits (if-then rules) related to the casting can be
linked to different nodes of the CDML tree. The data is stored in
a web server, and team members can access and view it using a
standard browser. The large size of solid models prevents their
real-time exchange over standard network connections. To overcome
this problem, a special program has been developed to compress,
upload, download, decompress, and display the solid models. Several programs have been developed to assist the product,
tooling, and foundry engineers in their respective tasks, as well
as evaluate the product and process. These include: casting alloy
selection, process selection, process planning, methoding (feeding
and gating design), casting defect prediction,
product-process-producer compatibility analysis, shape complexity
estimation, tooling process selection, cost estimation, feature
recognition and DFX checks. Simpler programs are implemented in
PHP/Java and executed at the server itself, whereas
computation-intensive programs are implemented in C++ and run at
client computers, followed by exchange of results over the
network. The system has been used to troubleshoot and optimise many
castings ranging in weight from a few kilograms (e.g. compressor
casing and medical equipment housing in aluminium alloys) to
several tons (e.g. hydraulic pumps and press tool parts in ferrous
metals). Such projects are carried out by active involvement of
product, tooling, and manufacturing engineers, and coupled with
continuing education programs to impart the necessary theoretical
background. Our research focuses strongly on different methodologies and
software tools for collaborative engineering, including
intelligent CAX, DFX, PLM and KM; these have a direct and
immediate impact on the competitiveness of manufacturing firms.
Today, many research laboratories in leading universities, and
several journals and conferences are dedicated to various aspects
of collaborative engineering.
Conclusion
Currently the Indian manufacturing industry is in the global
limelight. Just as Japan in 1980s focussed on quality, and China
in 1990s established its price competitiveness, India can stake a
claim to response competitiveness. This is possible by applying
information technology–in which we have already gained world-class
experience and reputation–for product lifecycle management and
collaborative engineering. Because our industry mainly comprises
small and medium size firms, the solutions must be inexpensive and
genuinely easy-to-use. This is a challenge that can be addressed
only by collaborative R&D between engineering institutes, the IT
sector and the manufacturing industry.
Contact: bravi@me.iitb.ac.in
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Editorial