AN�ANALYTICAL�METHOD�TO�ASSESSMENT�FACILITY�MANAGEMENT�SERVICES�IN�CASE�STUDY

2012 ◽  
Author(s):  
Silvia Vilcekova
Keyword(s):  
Analytical Method ◽  
Facility Management ◽  
Management Services

scholarly journals Architecture For Automation System Metrics Collection, Visualization and Data Engineering – HAMK Sheet Metal Center Building Automation Case Study

2019 ◽  
Vol 9 (1) ◽  
pp. 561-570
Author(s):  
Khoa Dang ◽  
Igor Trotskii
Keyword(s):  
System Integration ◽  
Data Analytics ◽  
Building Energy ◽  
Facility Management ◽  
Automation System ◽  
Building Energy Efficiency ◽  
Building Automation ◽  
Automation Systems ◽  
Integration Data

AbstractEver growing building energy consumption requires advanced automation and monitoring solutions in order to improve building energy efficiency. Furthermore, aggregation of building automation data, similarly to industrial scenarios allows for condition monitoring and fault diagnostics of the Heating, Ventilations and Air Conditioning (HVAC) system. For existing buildings, the commissioned SCADA solutions provide historical trends, alarms management and setpoint curve adjustments, which are essential features for facility management personnel. The development in Internet of Things (IoT) and Industry 4.0, as well as software microservices enables higher system integration, data analytics and rich visualization to be integrated into the existing infrastructure. This paper presents the implementation of a technology stack, which can be used as a framework for improving existing and new building automation systems by increasing interconnection and integrating data analytics solutions. The implementation solution is realized and evaluated for a nearly zero energy building, as a case study.

Value of Bootstrapping Staged Deployment of Infrastructure: Case Study in Space Infrastructure Deployment

2017 ◽  
Author(s):  
Koki Ho ◽  
Hao Chen ◽  
Harrison Kim
Keyword(s):  
Analytical Model ◽  
Analytical Method ◽  
Space Exploration ◽  
Optimal Number ◽  
Single Stage ◽  
Operational Planning ◽  
Uncertain Environment ◽  
Infrastructure System ◽  
Space Infrastructure

This paper analyzes the value of staged deployment for complex infrastructure system and propose a concept of bootstrapping staged deployment. Staged deployment has been well known for its advantage of providing flexibility in an uncertain environment. In contrast, this paper demonstrates that the proposed bootstrapping staged deployment can even add values in a deterministic environment. The key idea of bootstrapping staged deployment is to have the previously deployed stages support the subsequent deployment. We develop an analytical model to demonstrate the effects of bootstrapping staged deployment with a case study in space exploration. Our analysis results show that with a well-coordinated deployment plan, staged deployment can overperform single-stage deployment even in a deterministic environment, and that there is an optimal number of stages in terms of lifecycle cost under certain conditions. Our method can find the analytical expression for the optimal number of stages and its deployment strategies. The general findings from the proposed concept and analytical method can advance our knowledge about systems staged deployment, and make operational planning of resource generation infrastructure more efficient.

scholarly journals Case Study: Database Management for Solid Waste Management Services

2017 ◽  
Vol 6 (3) ◽  
pp. 133-137 ◽  
Author(s):  
Tuangthong Patcharaprutipakorn ◽  
◽  
Direk Thongaraim ◽  
Nujcha Thatreenaranon
Keyword(s):  
Waste Management ◽  
Solid Waste ◽  
Database Management ◽  
Solid Waste Management ◽  
Study Database ◽  
Management Services

Artificial intelligence exploitation in facility management using deep learning

2020 ◽  
Vol 20 (4) ◽  
pp. 609-624
Author(s):  
Mohamed Marzouk ◽  
Mohamed Zaher
Keyword(s):  
Artificial Intelligence ◽  
Deep Learning ◽  
Life Cycle Cost ◽  
Facility Management ◽  
Support Vector ◽  
Maintenance Costs ◽  
Content Type ◽  
Protection Systems ◽  
Future Work

Purpose This paper aims to apply a methodology that is capable to classify and localize mechanical, electrical and plumbing (MEP) elements to assist facility managers. Furthermore, it assists in decreasing the technical complexity and sophistication of different systems to the facility management (FM) team. Design/methodology/approach This research exploits artificial intelligence (AI) in FM operations through proposing a new system that uses a deep learning pre-trained model for transfer learning. The model can identify new MEP elements through image classification with a deep convolutional neural network using a support vector machine (SVM) technique under supervised learning. Also, an expert system is developed and integrated with an Android application to the proposed system to identify the required maintenance for the identified elements. FM team can reach the identified assets with bluetooth tracker devices to perform the required maintenance. Findings The proposed system aids facility managers in their tasks and decreases the maintenance costs of facilities by maintaining, upgrading, operating assets cost-effectively using the proposed system. Research limitations/implications The paper considers three fire protection systems for proactive maintenance, where other structural or architectural systems can also significantly affect the level of service and cost expensive repairs and maintenance. Also, the proposed system relies on different platforms that required to be consolidated for facility technicians and managers end-users. Therefore, the authors will consider these limitations and expand the study as a case study in future work. Originality/value This paper assists in a proactive manner to decrease the lack of knowledge of the required maintenance to MEP elements that leads to a lower life cycle cost. These MEP elements have a big share in the operation and maintenance costs of building facilities.

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