The System Assessment
Oil & Gas
Technology is available which enables a compressed air flow meter to measure not only the magnitude of the flow, but also the direction. Why is this important? In this article we will describe two case studies where bi-directional compressed air flow measurement plays a key role to come to the right conclusions. In the first case study, we will describe an electronics manufacturing plant, which has a large interconnected ring network with two air compressor rooms located in different buildings. The two air compressor rooms are about five hundred feet apart. In the second case study, the effect of compressed air flow measurement upstream of a local receiver tank is described.
Compressed air optimization measures adopted by PTMSB have reduced the consumption of compressed air by 31 percent resulting in savings of about 3,761,000 kWh per year in energy consumption. The monetary savings are MYR 1,090,627 per year ($255,000 USD). The CO2 reduction is estimated at 2,735 ton per year.
Compressed air is a critical utility widely used throughout the food industry. Being aware of the composition of compressed air used in your plant is key to avoiding product contamination. Your task is to assess the activities and operations that can harm a product, the extent to which a product can be harmed, and how likely it is that product harm will occur. Assessing product contamination is a multi-step process in which you must identify the important risks, prioritize them for management, and take reasonable steps to remove or reduce the chance of harm to the product, and, in particular, serious harm to the consumer.
The objective of this project is to help the building automation industry develop novel products that more cost-effectively identify faults (unwanted conditions) and inefficiencies in the operation of the compressed air plants of industrial facilities. More cost-effective fault detection and diagnostics (FDD) products can come to the building automation marketplace only after that industry makes very significant advances in the state-of-the-art of its FDD software tools from what it currently offers. Those advances require making common practice of rules-based artificial intelligence (AI) methods that the building automation industry has shown little to no familiarity with in its technology so far. This project will utilize, under controlled conditions, the compressed air plant of the NIST campus as a facility for test and development of an embedded rules-based FDD tool based upon NIST expertise.