Avionics System Performance Management

1998 ◽  
Author(s):  
Bhavesh Damania ◽  
Steve Vestal ◽  
Devesh Bhatt ◽  
Rashmi Bhatt
Keyword(s):  
Performance Management ◽  
System Performance

Chiller system performance management with market basket analysis

Facilities ◽  
2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Wai Tung Ho ◽  
Fu Wing Yu
Keyword(s):  
Performance Management ◽  
System Performance ◽  
Coefficient Of Performance ◽  
Prediction Errors ◽  
Frequency Method ◽  
Content Type ◽  
Operating Variables ◽  
Electricity Use ◽  
System Components ◽  
Operating Constraints

Purpose This study aims to apply association rule mining (ARM) to uncover specific associations between operating components of a chiller system and improve its coefficient of performance (COP), hence reducing the electricity use of buildings with central air conditioning. Design/methodology/approach First, 13 operating variables were identified, comprising measures of temperatures and flow rates of system components and their switching statuses. The variables were grouped into four bins before carrying out ARM. Strong rules were produced to associate the variables and switching statuses with different COP classes. Findings The strong rules explain existing constraints on practising chiller sequencing and prioritise variables for optimisation. Based on strong rules for the highest COP class, the optimal operating strategy involves rescheduling chillers and their associated components in pairs during a high load operation. Resetting the chilled water supply temperature is the next best strategy, followed by resetting the condenser water entering temperature, subject to operating constraints. Research limitations/implications This study considers the even frequency method with four bins only. Replication work can be done with other discretisation methods and different numbers of classes to compare potential differences in the bin ranges of the optimised variables. Practical implications The strong rules identified by ARM highlight associations between variables and high or low COPs. This supports the selection of critical variables and the operating status of system components to maximise the COP. Tailor-made optimisation strategies and the associated electricity savings can be further evaluated. Originality/value Previous studies applied ARM for chiller fault detection but without considering system performance under the interaction of different components. The novelty of this study is its demonstration of ARM’s intelligence at discovering associations in past operating data. This enables the identification of tailor-made energy management opportunities, which are essential for all engineering systems. ARM is free from the prediction errors of typical regression and black-box models.

System Performance Management on Designing a Manufacturing System

2000 ◽  
Vol 2000.3 (0) ◽  
pp. 557-558
Author(s):  
Michinaga MANO ◽  
Shinya NONAKA ◽  
Yoshiro FUKUDA ◽  
Fumio KOJIMA ◽  
Keiji MITUYUKI
Keyword(s):  
Performance Management ◽  
System Performance ◽  
Manufacturing System

Advancing Urban Multimodal Transportation System Performance Management

2017 ◽  
Vol 2646 (1) ◽  
pp. 17-27 ◽  
Author(s):  
Stephanie Dock ◽  
Ryan Westrom ◽  
Kevin Lee ◽  
Burak Cesme
Keyword(s):  
Performance Management ◽  
Performance Measures ◽  
System Performance ◽  
Urban Areas ◽  
Transportation System ◽  
Visualization Tool ◽  
Department Of Transportation ◽  
Policy Makers ◽  
Multimodal Transportation ◽  
The Public

As in many cities, congestion in Washington, D.C., is one of the top concerns of residents, businesses, travelers, and policy makers. Monitoring and communicating system performance from a mobility perspective is challenging, particularly when dealing with the multimodal nature of travel in urban areas. The District Department of Transportation has identified a set of performance measures for multimodal mobility—including congestion—that are based on available data and is making these metrics available to the public and to policy makers through an innovative visualization tool. The study’s approach, measures, and visualization component provide a model for other jurisdictions to consider adopting when seeking to better understand and convey the challenges, opportunities, and interdependencies of multimodal travel.

Sign in / Sign up

Export Citation Format

Share Document