The integration of facility management and mobile cloud computing is an innovative and vital undertaking to improve facility maintenance and management. Even though recent studies have proposed various methods of implementing mobile cloud computing, there remains an issue of simplifying data structures and maximising productivity. This paper presents a solution to mobilise corrective maintenance processes. Based on a comprehensive literature review on productivity, lean maintenance, and mobile computing technology, a mobile cloud computing application is proposed to improve information quality and availability. This study proposes a mobile cloud computing system for facilities management staff performing building operations and maintenance using QR code and cloud computing technologies. The mobile cloud computing system was used in a field experiment at the Singapore Institute of Technology to verify the proposed solution and demonstrate its effectiveness in corrective maintenance practice. The results obtained from the experiment demonstrated the effectiveness of the solution in reducing waiting, motion, and over-processing waste, leading to improvement in facility management productivity. The advantage of the proposed solution lies in its ability to transform facility management work processes by maximising usefulness delivered from invested resources, i.e., enhance value delivery.
Cite as: “Kng JHJ and Fadeyi MO (2021). Mobile cloud computing application solution for waste reduction in the facility management process. Built Environment Applied Research Sharing #08. ISSUU Digital Publishing.”
This technical note provides guidance on how python can be used to automate the process of verifying building information modelling (BIM) files. The research conducted and reported in this paper is a follow up to the Chua and Fadeyi (2021) study in which dynamo was used to perform automatic verification of BIM files. The guiding questions for this present study were: (i) Would the excel outputs from dynamo and python be the same? (ii) Can the use of python provide better customisation of the verification process and the derived building information than dynamo? Excel outputs from python and dynamo were found to be the same or similar when compared. For verification functions where the outputs are similar, python provided concise information needed better than the dynamo because of the better customisation benefits python provides. Python also provided better customisation of the process of doing the automatic verification. The automation verification benefits provided by python, like in dynamo, can significantly optimise the process and productivity of validating building information modelling (BIM) files.
Keywords: Building information modelling, Digital facility management, Productivity, Python, Computational thinking
Cite as: “Low TW, Fadeyi MO, and Low MYH (2021). Guidance for performing automatic verification of building information modelling (BIM) files using Python. Built Environment Applied Research Sharing #07 (Technical Note). ISSUU Digital Publishing.”
This study provides a potential solution that may improve productivity in the current facility management industry. An accurate and updated building asset information plays a crucial role in ensuring facilities management’s effectiveness and efficiency. Maintenance and operation require accurate building asset information to improve the maintenance process. An automated solution has earlier been developed to extract data from the equipment asset list in PDF files to the AIR template in excel. However, to ensure that the extracted information from the equipment asset list is accurate and updated, the AIR template must be verified against the onsite images. The current practice in the industry involves manual entry of information from images as well as the manual verification process. This practice requires more staff and time needed to consolidate the image information. With the increasing number of image information to consolidate, the rate of error also increases. An automated solution is developed and tested to extract data from images and to verify the AIR template for PDF files in this study. The solution aims to reduce staff and time needed to complete the task without compromising the accuracy. The developed solution’s test results show that it can reduce the time taken significantly and improve accuracy during data collection and verification. The survey done after the test provides insights and possible improvement for the developed solution.
Keywords: Asset Information Requirements (AIR), Digital Facility Management, Productivity, Python, Automated Image Retrieval
Cite as: “Kwok NQ, Fadeyi MO, and Low MYH (2021). Automated retrieval of photo data for asset information requirements (AIR) input using Python. Built Environment Applied Research Sharing #06. ISSUU Digital Publishing.”
Facility managers or facility management firms usually painstakingly and manually import building critical assets information from assets information requirements (AIR) to a building 3D model. Unfortunately, such practice requires a lot of resources, manpower, time, energy, material, etc., to deliver the required usefulness – Quantity of quality that serves the function needed without compromising safety. Thus, value delivery is compromised for all stakeholders involved. There are many times that there are many errors in the imported critical assets information, further compromising value delivery for all stakeholders involved. This project aims to identify the root cause of the deficiency in value delivery and use digital solutions to optimise the process of value delivery. Specifically, the project aims to develop an automated solution that can reduce the time and potentially manpower and energy required to import a building critical assets information from an automated AIR generator, previously developed by the authors, to a building 3D model with no error. The proposed automated solution was developed using Python Scripting in Dynamo for Revit and experimentally tested for the required efficiency and effectiveness. The developed automated solution provided a 99% time reduction over the manual method currently adopted in the digital facility management industry with zero error in the importation of the critical assets information. The findings also show no limitation to the number of building critical assets and their information that one person can do. The resources saved due to the developed automated can be deployed to other projects to deliver more value instead of focusing on one project for several months or more. The developed automated solution can aid the achievement of high value-oriented productivity in the facility management industry.
Keywords: Asset Information Requirements (AIR), Digital Facility Management, Productivity, Dynamo, Building Information Modelling
The productivity of facility managers in delivering healthy and energy efficient buildings can be determined by the information available for managing the building. Incomplete, inaccurate, and irrelevant information can compromise productivity. In a digitalized architecture, engineering, and construction (AEC) industry, facility managers are required to use building information modelling (BIM) models for their facility management operations. It is not uncommon for facility managers to submit incomplete, inaccurate, and irrelevant as-built BIM models to facility managers, leading to low productivity due to non-usage or usage of the BIM model with errors. Unfortunately, many facility managers do not have automated solutions for identifying and rectifying BIM errors. This study aims to provide automated programming solutions that could help facility managers identify and rectify errors in BIM models with the complexity level of a high rise building and transform the BIM model to a facility management ready model. The investigation on the validation of the developed automated programming solution with built environment professionals suggests that the solutions can considerably reduce the time taken and accuracy for correcting the BIM model and make it facility management ready. The participants’ feedback also suggests that the developed solution is satisfying to use, user friendly, and could improve the work process. Lessons and ideas of the developed automated programming solution reported in this paper can help develop solutions that will aid the adoption of BIM models for facility management operations.
Keywords: Facility management, Building information modelling, Computational BIM, Productivity, Dynamo
Sheltered walkways are common urban features in Singapore as pedestrians utilise them as pathways to public transportation locations in Singapore. In a tropical environment like Singapore, with high solar intensity and frequent and heavy rains, the walkways provide essential benefits in reducing users’ thermal discomfort and wetness. Of particular concern in the design of sheltered walkways in Singapore is the need for protection from wind-driven rain. This part of the pedestrian’s comfort is often neglected. Sheltered walkways are built with vertical, and 30° angled rainfall in mind. The considerations of the influence of wind are often neglected in the design of sheltered walkways, which results in a larger area of walkways receiving a high amount of rain penetration. To better evaluate the design of sheltered walkways, it is crucial to understand the pedestrian’s perspective and the correlation between wind and rain, and its effects on sheltered walkway design. Findings from the use of 3-Dimensional Computational Fluid Dynamics (CFD) simulations of wind flow and wind-driven rain for sheltered walkway designs are presented in this study. Additionally, a proposed microcontroller prototype, Arduino UNO, is built to validate the feasibility of the design solution. This study demonstrates the importance of considering wind-driven rain during the sheltered walkway design process.
Keywords: Shelter walkways, Wind-driven rain, Land Transport Authority, Computation fluid dynamics, Prototype design, Walk2Ride
Cite as: “Guam YN and Fadeyi MO (2020). Optimisation of sheltered walkways performance to mitigate wind-driven rain in Singapore. Built Environment Applied Research Sharing #03, ISSUU Digital Publishing Platform.”
The maintenance and operations of building to ensure suitable building performance require consolidation of complete and accurate building asset information. The consolidation of building asset information is done in the asset information requirement (AIR) template. The AIR template is designed according to the building owner’s requirements. The risk of consolidating inaccurate asset information into an AIR template increases with an increasing number of building asset information to be consolidated. The current practice in the industry involves manual on and forth coping of critical asset information from PDF file and pasting on excel template cell by cell. This practice causes more time to be spent on consolidation. To reduce the time taken, companies usually deploy more several staff to do consolidation tasks. The risk of errors occurring in the current manual consolidation practice is high due to inherent human error. An automated solution was developed and tested to examine how it could aid accurate consolidation of building asset information into an AIR template within a short period and with potential for lesser manpower. The developed solution reduces the time taken to consolidate asset information into an AIR template by 99% with zero error. The developed solution also reduces the need for experienced staff to do the consolidation. The findings suggest the number of staff required, even with a large building with many critical assets can be reduced significantly. The solution developed and reported in this paper is essential to the effort needed to improve productivity in the facility management industry.
Keywords: Facility management, Asset information, Asset Information Requirements (AIR), Digital Facility Management, Productivity
Cite as: “Ng HM and Fadeyi MO (2020). Development of a solution to optimise the process for consolidating asset information into asset information requirements (AIR) template. Built Environment Applied Research Sharing #02, ISSUU Digital Publishing Platform.”
Building Information Modelling (BIM) is a process that allows multiple project stakeholders to collaborate from the planning and design stage to the construction of the building within a 3D model. In turn, the information can then be extended to be used for facility operations and management. However, the effective operational benefits inherent in BIM models are not usually realised at the facility management (FM) stage. There are two main circumstances to consider; inaccurate as-built BIM models received from the contractors and the lack of BIM skills by facility owners and managers to check BIM models received for accuracies, completeness, and any other problems. Additionally, they are also unsure about how to transform the 3D as-built BIM models to 6D BIM FM models, which will be more suitable for operational use. Thus, the BIM models are usually left untouched, unused, and neglected throughout the building’s operations stages. This, in turn, wastes the efforts placed into the creation of as-built BIM models in the first place. There is a need to provide a solution to these problems to improve productivity in the FM sector. A solution that could potentially help address the concerns was developed. The potential benefits inherent in the developed solution was tested. There was a noticeable reduction in the time taken in identifying errors and inaccuracy in as-built models, and transforming as-built 3D models to 6D FM models. This study is important because it provides the knowledge needed to streamline and improve productivity in the facility management sector.
Keywords: Facility management, Building Information modelling, Computational BIM, Productivity
Cite as: “Chua C and Fadeyi MO (2020). The use of dynamo to automate the process needed to prepare building information modelling (BIM) models for facility management and operations. Built Environment Applied Research Sharing #01, ISSUU Digital Publishing Platform.”