I would like to continue on this blog based on my previous ones.
Data mining is applied in many areas such as
business, tele-communication, medicine etc. But, there has not been similar
interest and activity in the manufacturing domain. Some of the reasons are –
Majority of researchers in the manufacturing domain
are no familial with the data mining tools.
Majority of data mining researchers are not familiar
with the complex manufacturing domain.
The few researchers who are skilled in bothe the
areas are not able to access the manufacturing enterprise data.
It is difficult to evaluate the effectiveness and benefits
when the data mining tools are implemented in the manufacturing domain.
Only a few years ago the researchers have started to
explore the potential of data mining tools in the manufacturing domain. This
has shown a tremendous growth in the manufacturing domain which uses data
mining tools. The manufacturing researchers are not familiar with the data mining
tools and which domain is manufacturing is suitable for data mining
implementation.
We know that manufacturing systems and processes are
very complex, it involves various stages of operation and many variables
related to the operation at each stage. Some if the many problems faced by
engineers are controlling variables to make the quality consistent, production
time shorter and lower cost. These problems include, process defects, failure
with unknown cause, product variability etc. System and process engineers try
to understand the relationship between parameters and variables of the system
using mathematical models. Data mining enables computers to quickly and
exhaustively find those relationships which are useful for manufacturing
systems and processes. The strategies for implementation of data mining in
manufacturing are different from the non – manufacturing business. Data mining
implementation calls for people with good mathematical and computer skills.
Visualization have made the data mining accessible to large number of audience.
Some of the data mining applications are -
1.
Manufacturing system modeling
2.
Manufacturing process control
3.
Quality control
4.
Monitoring and diagnosis
5.
Safety evaluation
6.
Process planning /and scheduling
7.
Optimization of manufacturing yield
8.
Assembly selection; and
9.
Learning robotics
10.
Material requirement planning
11.
Preventive machine maintenance, etc
As discussed before the
collecting, cleaning of datasets are time consuming. One of the most important
step is to define the data model.
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