Efficient Facility Management Research Articles

Electrical consumption forecasting in sports venues: A proposed approach based on neural networks and ARIMAX Models

Building energy demand accounts for an important part of global energy consumption and emissions. Load forecasting is a crucial functionality for building management systems (BMSs) in order to optimize the energy supply and use with the goal of achieving economic and environmental benefits. Furthermore, if the building is a sports/event venue (one of the most energy-intensive facility type), load forecasting acquires an even greater importance.This paper presents a new forecasting hybrid technique that combines an ensemble of Artificial Neural Networks (ANNs) with an AutoRegressive Integrated Moving Average with eXternal inputs (ARIMAX) model. The proposed methodology is designed for the 24-hour-ahead electrical consumption forecasting of sports venues. These types of buildings are generally characterized by large fluctuations in their load caused by the hosted events, and therefore they are challenging for forecasting tools. The ANNs ensemble is composed of the average output of several multi-layer perceptrons, while the ARIMAX is used to correct the prediction provided by the ANNs working on the ensemble residual. The proposed approach can be easily implemented within a BMS that can be crucial for an efficient facility management. The hybrid methodology has been tested and validated on the load data of a real football arena. The proposed methodology achieves a MAPE of 9.03 % on an open dataset, and 9.38% on a closed dataset, outperforming standard machine learning techniques, hybridization techniques involving time-series and machine learning methods, as well as a state of the art event venue load forecasting technique. Furthermore, a feature importance study reveals that all the selected inputs are crucial in achieving the result. Finally, the inclusion of results related to an open dataset encourages further studies and comparisons.

EXPLORING SCIENTIFIC DOMAIN OF OCCUPANCY ANALYSIS, POE, AND DT IN AECO INDUSTRY: A SCIENTOMETRIC APPROACH

Building occupancy patterns strongly influence organizational effectiveness during the operation and maintenance (O&M) phase. Actual occupancy is highly variable over time and differs from the static occupancy levels considered during design phases. Consequently, poor levels of space management, use, and cleanness are detected during the O&M phase, affecting user well-being and satisfaction. Occupancy monitoring and analysis are needed to achieve effective and efficient facility management (FM) and user well-being. The article explores the scientific domains of occupancy detection and analysis, and related main approaches, i.e., post-occupancy evaluations (POEs) and digital twins (DTs) in the architecture, engineering, construction and operation (AECO) industry. A scientometric approach through science mapping and data visualization is applied to analyze 386 bibliographic records from Scopus database. The temporal trend analysis and conceptual structure of the scientific domain are investigated, drawing a picture of the body of knowledge. The performed analysis uncovered the temporal distribution of the publications and the relationships among the topics. DT is a recent topic in the early stages of investigation, while POEs are mature approaches related to sustainability, energy efficiency, productivity, building performance optimization, and user satisfaction. Occupancy detection and analysis are related to FM but less investigated topics in recent years. The research aims to uncover possible research gaps and open challenges in the field for further research aiming to support the optimization of occupancy and space management in the O&M phase, increasing workplace adaptability to changing conditions and needs and user satisfaction and well-being over time.

Understanding Season Ticket Holder Attendance Decisions

Predicting attendance at events is important for efficient facility management and marketing to maximize crowds. Most work to date is conducted at the aggregate level; however, the large crowd size being predicted often means important individual decisions are masked. In many markets, increased nonattendance by season ticket holders (STHs) is being reported, which is troubling given they have prepaid and are expected to be highly loyal. To understand who attends, rather than just how many, the authors analyze the “no-show” behavior of over 5,900 individual STH of one professional team over a season. Results show that in addition to game viewing and quality conditions, age, tenure, expenditure, and prior game attendance are predictors of individual attendance decisions, with differences in how individuals are influenced by winning and uncertainty of outcome. The paper expands understanding of drivers of STH attendance decisions and provides guidance toward managerial strategies for STH management.

Achieving Smarter Buildings and More Efficient Facilities Management

As buildings become more complex, smarter, interconnected, and self-reporting, can technologies be used to the advantage of the end-user and society? This study looks to determine if implementing big data can improve sustainability and increase efficiency in facilities management. Big data, the internet of things (IoT), their application in the construction industry, connection to sustainability, and impact on facilities management are researched. The research employs a mixed-methods approach with critical literature review, primary qualitative research by interviews, and quantitative data research by questionnaire with assessment through mind mapping and SPSS statistical analysis. Key findings identify an industry concept of big data, the IoT, BIM as a primary data contributor on AEC projects, with technology being most assistive to inception and design phases and improving decision making. Implications for industry arise from unrelated usage and misunderstanding of terminology. The study identifies space for further research into the topic.

Educational and digital tools as factors of service quality increase in Thailand 4.0 era (the case of Suvarnabhumi Airport, Bangkok)

Currently, Thailand implemented the project Thailand 4.0 essentially highlighted on better performance on human resource as well as an information technology management. However, service quality is the key to create the business differentiation as well as to elevate a superior level of market competitiveness. The aviation industry is one of the most intense competitive industry, therefore, passengers’ satisfaction on airport service quality and its’ efficient facility management is the most important factor that can create business differentiation and influenced a sustainable industry accordingly. This paper seeks to investigate the (1) factors that affect service quality and (2) passengers’ satisfaction of Suvarnabhumi airport in Thailand 4.0 era. Where the concept of Importance-Performance Analysis (IPA) has been implemented in this research, the results show that passenger’s expectation on service quality was higher than the services that passengers received in many areas. However, from 150 questionnaires that have been released, the research results indicated that most of the respondents placed the highest satisfaction on the quality of internet and wireless connectivity service as the top priority at Suvarnabhumi Airport, whereas the lowest satisfaction is placed on the service quality of an immigration process where the effectiveness of human resources management is the key element affecting the service quality. Moreover, there is a recommendation on the self-check-in-counter and the processing of this service that needs to be modernized and promote passengers to use this technology widely. Hence, to enhance the airport service quality toward Thailand 4.0, the technology should be taken into account at every level to increase passengers’ satisfaction throughout the passenger’s arrival, departure and transit process accordingly.

Geographical information systems and monitoring of climatic conditions in cities

Modern geographic information systems are able to visualize almost any information in their maps. Important is the data that the GIS should visualize. This data consists of information from the cadaster, passports or city plan. This paper discusses the possibilities of visualizing climate data based on a sensory network. The results can be used in the planning and development of the city. Internet of Things is a modern part of the Smart City concept that forms the basis of the modern city. The world’s most modern cities are equipped with hundreds or thousands of sensors. The data can be used for planning and development of the city. The result is more efficient facility management of the city, administration and operation, strategy and planning. In conjunction with building information management, more precisely city information management, significant savings can be achieved. Climatic conditions measure various institutes outside the influence of the city. For efficient use of data, the possibility to operate these sensors operatively and deploy them according to their own requirements and needs, the city should have its own sensor network for measuring climatic conditions.

Modelling queues at ferry stations: principles and application

It is well known that the flow of passengers at ferry stations is characterised by random variations following ferry schedules. Recognising the need to manage congestion, an approach based on queuing models is proposed. The motivation for this type of modelling comes from the short-term, where the knowledge of bottlenecks is essential for efficient facility management. An empirical case study is presented to explore the effectiveness of the queuing model and reveal waiting times, service times, queuing duration and service levels. The methodological framework proposed in this paper sheds new light on service points and is therefore a good starting point for improving processes at peak times. In addition, the queuing model can be used to simulate more complex scenarios in the future.

Energy efficiency practices in facilities management in Johannesburg

Purpose The purpose of this study is to examine at energy efficiency practices within the facilities management sector and barriers to adopting energy efficient strategies, it further explored the factors that promote the employment of energy efficient practices. Design/methodology/approach The data were gathered by means of an electronic survey, administered to facilities managers in Johannesburg. Findings Energy efficient lighting is the most used energy efficiency practice. It further uncovered that occupant engagement and education is considered least, amongst current energy efficiency practices. This study revealed that the biggest barrier to the implementation of energy efficient facilities management practices was the cost implications of adopting FM strategies and rated the lowest were policies and regulations of energy efficiency standards. Cost reduction was the highest rated factor that promotes energy efficiency practices. Practical implications Occupants should be educated on energy efficiency through a change of their behaviours and also exposed to the benefits of using energy conservation measures. Management buy-in should be the goal of the facilities manager for the success of energy efficient practices. Originality/value This study is an encompassing study on energy efficiency where many aspects of energy efficiency and factors that promote energy efficiency were explored.

Augmented reality system for facility management using image-based indoor localization

Abstract Image-based localization has provided opportunities for efficient facility management. Combined with augmented reality (AR), automated localization can offer visually assistive information in facility management. However, implementing an AR-based facility management system with image-based localization is difficult. Device-intensive methods or markers were prerequisites for facility information display. Localization accuracy and information readability and accessibility were some of the issues to be resolved for a successful representation of facility information. This paper presents an AR system for facility management using an image-based indoor localization method that estimates the user's indoor position and orientation by comparing the user's perspective to building information modeling (BIM) based on a deep learning computation. A graphics processing unit (GPU)-enabled server is used for the deep learning computation, and the resultant information is wirelessly transferred to the mobile AR device through transmission control protocol/Internet protocol (TCP/IP). Thereafter, spatial mapping visually fits the object of interest (e.g. pipes) onto the AR image using three-dimensional (3D) sensing capability of AR device. Experts evaluated that the proposed system has potential for improved facility management and identified future research direction, such as integrated information presentation and effective reflection of rehabilitation efforts on the drawings.

Facility management of smart buildings

The current development of smart buildings is conditioned by the development of smart technologies, bringing many new phenomena into the construction industry that change ownership, user and management environments. The optimized and truly functional smart building already includes engineering and non-technical aspects, which must, however, be respected during all life cycles. This requires the emergence of completely new expertise or the extension of the existing expertise, including facility management. Smart buildings enable cost savings and facilitated operation to facility management. Moreover, smart buildings also contain significant multidisciplinarity, especially in pertaining technical areas. This requires the facility manager to monitor individual disciplines and ensure their interoperability and optimal functioning to meet the needs of building users. This contribution is based on practical experiences and focuses on the analysis of the new demands that smart buildings require in management issues, the evaluation of synergies between smart buildings and efficient facility management for maximizing the use of the building and its sustainability. It also quantifies the benefits of facility management for the operation of smart buildings and their utility value, depending on the degree of integration of services.

Optimal FM Strategy for Commercial Office Buildings Using Fuzzy Synthetic Evaluation

AbstractFor owners of aged buildings, considerable attention needs to be devoted to efficient facility management (FM) to extend building life and achieve life-cycle cost savings. The fundamental s...

Evaluation of Handover Requirements of Construction Information for Efficient Facility Management

Evaluation of Handover Requirements of Construction Information for Efficient Facility Management

A user-centric space heating energy management framework for multi-family residential facilities based on occupant pattern prediction modeling

Space heating is the highest energy consumer in the operation of residential facilities in cold regions. Energy saving measures for efficient space heating operation are thus of paramount importance in efforts to reduce energy consumption in buildings. For effective functioning of space heating systems, efficient facility management coupled with relevant occupant behaviour information is necessary. However, current practice in space heating control is event-driven rather than user-centric, and in most cases relevant occupant information is not incorporated into space heating energy management strategies. This causes system inefficiency during the occupancy phase. For multi-family residential facilities, integrating occupant information within space heating energy management strategies poses several challenges; unlike with commercial facilities, in multi-family facilities occupant behavior does not follow any fixed activity-schedule pattern. In this study, a framework is developed for extracting relevant information about the uncertainties pertaining to occupant patterns (i.e., demand load) in multi-family residential facilities by identifying the factors affecting space heating energy consumption. This is achieved using sensor-based data monitoring during the occupancy phase. Based on the analysis of the monitoring data, a structure is defined for developing an occupant pattern prediction model that can be integrated with energy management strategies to reduce energy usage in multi-family residential facilities. To demonstrate the developed framework, a multi-family residential building in Fort McMurray, Canada, is chosen as a case study. This paper shows that integrating the developed occupant pattern prediction model within space heating energy management strategies can assist facility managers to achieve space heating energy savings in multi-family residential facilities.

BIMデータ化された設計図書を用いた施設管理の効率化

This study aims at considering efficient facilities management using existing design documents converted to building information models. Numerous buildings were constructed during Japan's period of high economic growth and the conservation of those buildings is now a social issue. The deficiency of not only a periodic inspection but also the management of the construction information causes those circumstances. Because the use of the design documents is important for the maintenance of existing buildings, the use of building information models made from these documents is examined in this study. In these buildings, apart from the design documents, from routine work of facilities management, repair records printed in paper are generated in large quantities and accumulate every year, but are left uncared for. These data has a utility value for improving future facilities management. In the maintenance of facilities, whenever malfunctions and troubles happen, treatments are ex post facto conducted. It is useful for constructing an effective maintenance cycle to predict these troubles beforehand. To achieve the above-mentioned goal, by linking repair records to building information models, the system for predicting the renewal date of the components of building, which used the spatial or network relationship among the components of building information models, was constructed. Tsukuba University's repair records for buildings were collected for the analyses. After the items and each entry content were confirmed, the information written in the repair records was input into a spreadsheet. About inputted data, simple totaling was carried out based on reported consultations and the building name in order to gain an understanding of the characteristics of the collected documents. Based on the result of the totaling, consultation contents and buildings for the analyses were determined. Next, attempts were made to calculate the time between problems of the building components via multiple regression analyses. A Door and an air conditioner and lamp bulb, fluorescent lamp were treated as a case study. The time between problems of the target class was selected as an objective variable. These values were acquired by confirming the dates written in the entry columns for a building or a room. Explanatory variables were acquired from BIM data along with other materials. Whenever possible, original paper documents will be used to create the BIM data used in our method. Three methods of data acquisition from building information models were conducted in this study. The first method used the attribute information of the object, which was determined when it was located. The second method used the attribute information of the object, which was determined when some objects including it were located. The third method used the inclusion relations between a room and other classes. The forced entry method was adopted for the analyses. Because the calculations were conducted in phases, we classified the cases based on the kind of objective variables or sample group or whether room-based explanatory variables were added. As for two cases (door, lamp bulb and fluorescent lamp) which used a room-based objective variable and data group B, the adjusted R-squared value got higher by adding the explanatory variables acquired from BIM data. However, because the R-squared value itself is low in these cases, improving the regression model is necessary in order to use it for the prediction. About the explanatory variables acquired from BIM data, the floor at which the door is located (Door) and the number of lighting fixtures (Lamp bulb, Fluorescent lamp) were statistically significant in data group B. And from the interview to engineers, the utility value for considering the extension of the time between troubles was pointed out in these variables.

생애주기 정보공유를 위한 자산관리 업무기능 분석

과거 1960~70년대에 급격한 경제발전으로 인하여 국내에는 수많은 건물이 건설되었으며, 특히 2000년 이후에는 대형화, 첨단화된 수많은 건물들이 건설이 되고 있다. 이러한 건물의 전 생애주기 비용 (Life Cycle Cost) 중, 운영 및 유지관리 단계 비용은 전체의 약 85%를 차지 (Teicholz 2004)하고 있어 건축물에 대한 효율적인 자산관리가 강조된다. 하지만 운영 및 유지관리 단계에서 필요한 정보들은 초기 기획 단계부터 설계, 시공 단계를 넘어오면서 각각의 정보들의 호환이 부족하다. 단계를 거듭할수록 정보에 대한 가치는 증가하지만 정보의 상호 호환의 부족으로 인하여 비효율적인 부분이 발생하고 있다 (Foster 2011). 본 연구에서는 먼저 발주자 관점에서 자산관리의 주요 업무기능을 3개의 대분류와 19개의 중분류로 도출하였다. 다음으로는 도출한 항목들을 바탕으로 자산관리 업무량의 비중, 자산관리 업무별 소요 데이터의 비중, 그리고 생애주기 단계별로 발생하는 데이터의 비중에 대한 평가방법론을 제안함으로써, 효율적인 운영 및 유지관리를 위한 방안을 제안하였다. 마지막으로, 제안된 방법론은 공공 및 민간 기업의 사례를 바탕으로 적용성을 검토하였다. In the 1960s and 1970s when Korea experienced rapid economic growth, a considerable number of buildings were constructed in the country. And since 2000, a large number of sizable and complex buildings have been being built. Specifically, as the operation and maintenance cost alone accounts for 85% of the life cycle cost of a building, efficient Facility Management (FM) is required. However, data needed in the operation and maintenance phase are not sufficiently exchangeable with data created in other phases like the planning, design and construction phases. The upper phase has higher value of data but data exchange rate is low, resulting in inefficiency. To this end, this research derived major business functions for facility management: three categories and 19 detailed functions in classification from owner's perspective. Based on the derived items, this research proposes a methodology to evaluate the 'FM Workload', 'Facility Management (FM) Data', and 'FM Data Created in Engineering and Construction Phases' thereby analyzing plans for efficient operation and maintenance. The applicability of proposed methodology was tested by examining real-world cases of public and private companies.

스포츠센터 운동기구 예약 시스템의 설계 및 구현

ABSTRACT Many people feel uncomfortable when fitness center is crowded with people in all at the same time. So we propose exercise machines reservation system for resolving the problem that people feel uncomfortable in fitness center. In this paper, we design and implement the exercise machines reservation system that allows for users to reserve fitness equipments by using a NFC-based smart band. A user can reserve exercise machine using some reservation device. he or she will receive notifications through the smart band about when and which machine she or he will have to use. The user can do exercise with a recommended program, and can use any equipments conveniently even in a peak time because no one is waiting. Also, a manager can save cost through the efficient facility management and provide customized member management. Additionally, manager don’t need to purchase other exercise machines or computers. 키워드 : 헬스케어, 예약 시스템, 웨어러블 디바이스, NFC Key word : Healthcare, Reservation System, Wearable Device, NFC

Development of Data-Flow Control Algorithm of Wireless Network for Sewage Disposal Facility

Recently, water sewage disposal facilities are able to manage real-time data collection and record management through compact broadband modem LAN switching technology. Therefore, it needs more stable and efficient facility management. So, we required practical use of environmental facilities convergence based on broadband integrated modem. In this paper, we proposed short distance wireless communication network of compact broadband modem for sewage disposal facilities. And it received data inside of water treatment facility using the two communication methods (IEEE802.11x and IEEE802.15.4x). Then, our proposed an data-flow control algorithm of wireless network technology will prioritize processing data when emergency happen through collecting data, analysis data and processing. Lastly, we proved usefulness by experiment and simulation analysis.

Inspection Method for Near-ground Corrosion in Steel Poles for More Efficient Facility Management

Inspection Method for Near-ground Corrosion in Steel Poles for More Efficient Facility Management

FM and milk production: herd ventilation systems in hot climates

Purpose – The following editorial aims to highlight the potential impact that efficient facilities management with regards to agricultural ventilation systems could have in hot climates. Design/methodology/approach – Through a review of the literature surrounding different ventilation systems and their benefits and disadvantages on milk production, evidence to support the aims was compiled. Through looking at the direct effects on milk yield and how these values vary across the globe a scope of the potential effect of better facilities management was created. Findings – This paper found that although more expensive to install and power mechanical ventilation provided many benefits to animal welfare and productivity. However, in contrast developing countries were relying upon more traditional methods such as natural ventilation, which have limitations in tropical climates. By using India as a case study the potential benefits of improving productivity on the emissions of green house gases was illustrated. Research limitations/implications – The findings in this editorial are limited by the quality and amount of literature currently published regarding ventilation methods in many developing nations such as India. Practical implications – Practically it is a complex process to quantify the processes involved in milk production. Therefore, the data referenced in this editorial is subject to vary across the globe with contrasting farming techniques and livestock breeds. Originality/value – This paper brings an original view on how better management of ventilation systems; most noticeably within developing nations with hot climates could potential produce large benefits. Through increased productivity within the world's largest milk producers the green house gas emissions from agriculture can be reduced.

Life cycle cost analysis on educational facilities in Japan

The life cycle cost (LCC) is considerably important in facility management. However, there are some problems related to the assessment of LCC. This research aims to establish an efficient facility management system for educational institutions. First, the analysis of the actual LCC of university facilities clarifies the difference between the theoretical LCC and the actual LCC. Second, from the standpoint of both engineering and management, this research examines the factors which cause the difference. The comparison between budget and closing accounts shows the actual adjusting function in facility management. In particular, the timing and cost of repairing and renovation is subject to the facility management policy. Finally, this paper shows the recommendation for the realistic estimation method of LCC based on different facility management policies and examples of LCC planning based on two types of facility management policies. This paper discusses how to plan and manage the LCC.