Decision making of maritime development scenario on the impact of naval base for supporting navy ships operations

The Indonesian Navy is the spearhead in maintaining maritime security in Indonesian waters. In carrying out its main tasks, the Indonesian Navy has components of an Integrated Fleet Weapon System in which there are elements of Ships and Naval Bases. To ensure the effectiveness of carrying out operations by ship elements, ship operations are supported by the Naval Base as the organizer of the support function. Naval Base's carrying capacity consists of 5 (five) support functions, including: (1) support for anchoring facilities; (2) support for supply facilities; (3) support for maintenance and repair facilities; (4) support facility maintenance personnel; and (5) support for base development facilities. Naval Base does not yet have its dock to support anchoring facilities for ship operations. In addition to cooperation in the use of the Naval Base anchorage facility, there is also cooperation in port security, both in terms of land and port water aspects. As the number of ship visits at Naval Base Harbor increases, the dock utility increases. The increase in dock utility resulted in a decrease in port services which also resulted in a decrease in the Naval Base Carrying Capacity. To improve port services, Pelindo III implements the port development program contained in the Naval Base Port Master Plan in Permen KP number 792 of 2017. In this study, an analysis of the impact of the Naval Base Port development policy on the carrying capacity of the Naval Base was carried out. The data analysis uses System Dynamics modeling with a simulation period of 30 years in 3 development scenarios, namely short-term scenarios, medium-term scenarios, and long-term scenarios. From the simulation results, it is found that the construction of the Naval Base port affects the Naval Base Carrying Capacity with an average increase of 1.8% in each policy scenario. The increase in Naval Base Carrying Capacity has an effect on increasing Ship Operations by an average of 1.8% and also increasing the Security of Naval Base Harbor by an average of 0.14%. The results of the analysis of this study can be used as consideration for policymaking by the Navy.

Examining the Role of NGOs in Community Water and Sanitation Improvement

This chapter examined the role of NGOs in water and sanitation improvement and the effects on the residence of Tunayilli in the Sagnarigu District. The design was descriptive. Questionnaires and interview guides were administered to household heads and key informants. Findings revealed that the water and sanitation condition in Tunayilli is generally poor. NGOs play diverse roles including the provision of water and sanitation facilities, community mobilization, and facility maintenance to ensure their sustained usability. However, inadequate funding, weak community mobilization, poor maintenance culture, and low education are challenges to water and sanitation improvement programmes of NGOs in the community. Measures to mitigate these includes increased central government funding, public education, community involvement, enforcement of sanitation by-laws, and regular maintenance of water and sanitation systems in the community. Stakeholders should intensify and sustain their educational campaigns. Meanwhile, by-laws on water and sanitation should be enforced and offenders prosecuted.

A Review of Embedding Artificial Intelligence in Internet of Things and Building Information Modelling for Healthcare Facility Maintenance Management

Latest innovations in Internet of Things (IoT) technologies as well as the new paradigms in Artificial Intelligence systems are opening up opportunities to create smart computing infrastructures for the Healthcare Facility Management. However, the current scenario of hospital buildings maintenance management is strongly characterized by slow, redundant, and not integrated processes, which lead to loss of money, resources, and time. On the other hand, lack of data and information in as-built digital models considerably limits the potential of Building Information Modelling in Facility Maintenance Management. Consequently, optimization of data collection process and management is required. In this light, this paper presents a review of embedding AI (Artificial Intelligence) in BIM-IoT integration for the process of healthcare Facility Maintenance Management (FMM) in order to conquer the current challenges. The first challenge in front of integrating IoT– BIM, is the lack of information; the second challenge is BIM’s sematic information that has not been able to display indoor conditions’ elements which should be reconsidered; and the third challenge is the data size which is stored in systems as well as the eligibility of individuals to apply the related data. Additionally, some emerging trends in IoT are reviewed such as the combination of Machine Learning and Artificial Intelligence in order to exploit their advantages and complement their limitations, which enable new promising IoT applications.

Offering a preventive solution to defects in commercial building facility system using BIM

Purpose Commercial building facility systems are costly, and due to the complexity of operation and maintenance (O&M), some failures can cause irreversible expensive damage. Currently, few capabilities of building information modeling (BIM) have been used in the facility maintenance operation. The purpose of this paper is to use a tool for making it easier to predict preventable defects in commercial building facility systems by examining a complete BIM. Design/methodology/approach To this end, a list of frequent defects in the facility system was achieved by a review of commercial building literature. Then, by examining a complete BIM model, the available methods and tools for O&M facilities during the operation period are identified and analyzed. Findings The results of the paper show that the solution presented based on total productive maintenance (TPM) subsets can effectively prevent facility system defects during the operation and maintenance period. An expert team assesses the validation of results. Originality/value The findings can help facility managers to adopt measures using TPM methods to prevent defects through an integrated BIM platform. The examination is based on case studies, surveys, expert experience and a thorough literature review.

Development of Simulation for Predicting Maintenance Costs for Educational Facilities

In Korea, educational facilities are managed after issues are detected. Furthermore, due to imprecisely estimated maintenance costs, there are problems in managing educational facilities such as excessive budgets, etc. it is impossible to accurately estimate costs for various cases such as repairs and damages. Thus, the overall maintenance costs were analyzed based on probability of cases that may occur. This study proposes a system that predicts maintenance subjects and maintenance costs using probability values and that predicts the total maintenance cost through simulations. This study used simulations to accurately predict maintenance costs in various unexpected situations. The study was carried out by classifying into three categories according to each feature. The features were described according to the type of each item and simulation of the categorized items were produced separately to calculate the expected price. In the case of ‘annual fixed expenses’, the total of the maintenance cost tended to increase with a secondary curve where the slope gradually grows with time. In the case of ‘irregular expenses due to repairs/changes caused by minor failures’, maintenance cost had a certain cycle according to a failure rate according to the life of each item and an inflation rate of 1.9% was applied to show a tendency for occurrence to grow. In the case of ‘Replacement/repair costs according to the scheduled period for the entire educational facility’, the simulation results showed that each item had a constant cycle depending on the replacement period and that facility maintenance costs did occur. This study presumed data for simulations, but did not verify it. By supplementing such limitations, it will be possible to produce a reliable simulation model. The expected effect of reducing budget waste by predicting the exact cost of educational facilities through simulation.

Mobile Crowdsourcing-based Data Collection for User-centered Facility Maintenance Management

Data collection enabled by existing FMM systems lacks 1) the top-down information solicitation on facility conditions, such as crowdsourcing task division, and 2) geo-referenced occupant feedback. Mobile crowdsourcing has great potential to improve current FMM practice, especially in terms of timely data collection. In this context, this paper explores the feasibility of mobile crowdsourcing for FMM data collection and highlights the associated opportunities and challenges. A survey is carried out on a university campus in order to gain an understanding of the human, data, system, geospatial, and automation characteristics of mobile crowdsourcing for FMM data collection on post-secondary campuses. The survey results are analyzed to reveal the challenges and recommendations for mobile crowdsourcing for user-centered FMM. A conceptual framework is proposed to apply mobile crowdsourcing for FMM. This research contributes to the body of knowledge by synthesizing the challenges, opportunities, and a framework of mobile crowdsourcing-based data collection for FMM.