Instruct: Identify the main and secondary category of Arxiv papers based on the titles and abstracts
Query: Artificial Intelligent Diagnosis and Monitoring in Manufacturing   The manufacturing sector is heavily influenced by artificial
intelligence-based technologies with the extraordinary increases in
computational power and data volumes. It has been reported that 35% of US
manufacturers are currently collecting data from sensors for manufacturing
processes enhancement. Nevertheless, many are still struggling to achieve the
'Industry 4.0', which aims to achieve nearly 50% reduction in maintenance cost
and total machine downtime by proper health management. For increasing
productivity and reducing operating costs, a central challenge lies in the
detection of faults or wearing parts in machining operations. Here we propose a
data-driven, end-to-end framework for monitoring of manufacturing systems. This
framework, derived from deep learning techniques, evaluates fused sensory
measurements to detect and even predict faults and wearing conditions. This
work exploits the predictive power of deep learning to extract hidden
degradation features from noisy data. We demonstrate the proposed framework on
several representative experimental manufacturing datasets drawn from a wide
variety of applications, ranging from mechanical to electrical systems. Results
reveal that the framework performs well in all benchmark applications examined
and can be applied in diverse contexts, indicating its potential for use as a
critical corner stone in smart manufacturing.

14
The categories of this paper are: math-ph
5
The categories of this paper are: gr-qc
36
The categories of this paper are: cmp-lg
33
The categories of this paper are: plasm-ph
28
The categories of this paper are: alg-geom
15
The categories of this paper are: nucl-ex
32
The categories of this paper are: atom-ph
34
The categories of this paper are: chem-ph
18
The categories of this paper are: econ
24
The categories of this paper are: dg-ga
2
The categories of this paper are: math
7
The categories of this paper are: hep-th
20
The categories of this paper are: acc-phys
37
The categories of this paper are: supr-con
25
The categories of this paper are: patt-sol
31
The categories of this paper are: ao-sci