Abstract Currently, we live in a world where all fields are developing very rapidly. In particular, the field of water management is day by day, and supply system being intelligent automated. Nevertheless, mechanical means human labor used to monitor level many facilities our region. This situation causes problems automatic system. this article, will consider process automating measurement cont...

Abstract Terahertz tomographic imaging as well machine learning tasks represent two emerging fields in the area of nondestructive testing. Detecting outliers measurements that are caused by defects is main challenge inline process monitoring. An efficient control enables to intervene directly during manufacturing and, consequently, reduce product discard. We focus on plastics and ceramics, for ...

Changes in the physicochemical conditions of process unit, even under control, may lead to what are generically referred to as faults. The cognition of causes is very important, because the system can be diagnosed and fault tolerated. In this article, we discuss and propose an artificial neural network that can detect the incipient and gradual faults either individually or mutually. The mai...

Nowadays, bulk of the designers prefer to outsource some parts of their design and fabrication process to the third-part companies due to the reliability problems, manufacturing cost and time-to-market limitations. In this situation, there are a lot of opportunities for malicious alterations by the off-shore companies. In this paper, we proposed a new placement algorithm that hinders the hardwa...