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This research proposes the study of the pathology in floor finishes, focussing on proactive maintenance strategies to promote the durability of these elements. A model to assess the floorings' performance levels was designed to support decision-making regarding maintenance activities to be carried out, in order to prevent the defects and extend the floors' service life.

The model to measure the floorings' level of performance was developed based on the literature and applied in fieldwork, focussed on visual inspections of floor finishes. Photographs were taken and standardized inspection forms were used to collect the data about the defects in the floors.

This study provides a simple classification model to assess floorings' performance levels, capable to define priorities and help decision-makers in adopting maintenance activities. The model was validated through a case study, which showed that occasionally the choice of the floor finishes is incorrectly made only based on aesthetic criteria and not taking into account the main criteria, i.e. the use of space.

This work contributes to a development of methodologies to assess floorings' performance levels, to study the behavior of different floor finishes, to propose maintenance strategies to improve their performance in service and adopt better solutions in the buildings' design phase.

This paper aims to design a vulnerability assessment model considering the multidimensional and systematic approach to disaster risk and vulnerability. This model serves to both risk mitigation and disaster preparedness phases of humanitarian logistics.

A survey of 27,218 households in Pueblo Rico and Dosquebradas was conducted to obtain information about disaster risk for landslides, floods and collapses. We adopted a cross entropy-based approach for the measure of disaster vulnerability (Kullback–Leibler divergence), and a maximum-entropy estimation for the reconstruction of risk a priori categorization (logistic regression). The capabilities approach of Sen supported theoretically our multidimensional assessment of disaster vulnerability.

Disaster vulnerability is shaped by economic, such as physical attributes of households, and health indicators, which are in specific morbidity indicators that seem to affect vulnerability outputs. Vulnerability is heterogeneous between communities/districts according to formal comparisons of Kullback–Leibler divergence. Nor social dimension, neither chronic illness indicators seem to shape vulnerability, at least for Pueblo Rico and Dosquebradas.

The results need a qualitative or case study validation at the community/district level.

We discuss how risk mitigation policies and disaster preparedness strategies can be driven by empirical results. For example, the type of stock to preposition can vary according to the disaster or the kind of alternative policies that can be formulated on the basis of the strong relationship between morbidity and disaster risk.

Entropy-based metrics are not widely used in humanitarian logistics literature, as well as empirical data-driven techniques.

The purpose of this paper is to propose a maintenance programme for flat roofs in existing buildings, based on the inspection of 26 buildings in-service conditions, located in the Lisbon region, in Portugal. A proactive maintenance of flat roofs in existing buildings allows reducing their pathology, thus improving their performance and service life.

The maintenance plan was established based on the degradation state of the maintenance source elements (MSEs) analysed, the aggressiveness of the surrounding environment and the age of the roofs and maintenance actions carried out during the roofing systems’ life cycle.

The maintenance plan proposed in this study includes the prioritization of the interventions, the definition of the required maintenance operations and the definition of the frequency of the intervention, considering the service lives of the MSEs.

The study addresses only roofs located in the Lisbon area. Even though a relatively large sample of 26 roofs was used, the findings and conclusions can clearly be extrapolated for a much wider scope.

The maintenance plan proposed in this study considers a planning of proactive maintenance operations to continuously and effectively monitor all the relevant MSE.

This plan allows minimizing the incidence and spread of defects, thus enabling the optimization of resources, reducing the costs of the entire maintenance system and improving the quality of the built environment.

Regular inspection and maintenance is recommended to preserve and sustain built cultural heritage. Systematising inspection processes and knowledge on defects, and providing pictorial guides for evaluating defects is an approach that may facilitate their condition survey. Generating pictorial guides for preliminary visual inspection of Modern Heritage buildings with rendered-painted facade concerning two defects (i.e. crack and efflorescence) is aimed in this study. These guides are thought as aids in determining the defect levels and deciding the necessity of advanced examination and/or maintenance. Analysing briefly the evolution of crack over time in the inspected buildings under environmental conditions of Istanbul (Turkey) is also aimed.

Preliminary guide generation was based mainly on literature survey on defects, and visual data collection from eight Modern Movement examples in Istanbul. The guides were then refined through systematic visual inspection of three buildings among them. Evolution of crack over time was analysed through a second inspection performed after 2.5 years.

Visual inspections showed that crack is the commonest defect occurring mostly on projecting structural members, while efflorescence is less in number. Comparison of cracks' visuals taken in the first and second inspections showed that deterioration process is slow.

Modern heritage buildings usually have some characteristic features, which may sometimes lead to accumulation of defects at certain locations or may lead to formation of certain defects. Generating visual guides as a start for an initiative for a comprehensive defects catalogue particular for Modern Movement buildings in line with associated cultural heritage standards may contribute to their preservation by easing the condition surveys.

Supplier selection is a complex and strategic activity needed in every organization, involving many stakeholders and different attributes as price, delivery performance, and product quality. Globalization, in the last decades, increased the competitiveness between vendors, enhancing the use of decision models to support the best choice based on optimizations and bidding variations due to specific needs. This chapter presents three models of multi-dimensional auctions to improve an international humanitarian NGO process procurement efficiency by reducing procurement costs and the decision-making process time. These models have the advantage to be easily implementable in typically complex environments where there is a large number of categories, suppliers, and other features.

The first proposed model uses combinatorial auctions and is suited for procurement, where suppliers can benefit from cost complementarity. The second one uses volume discount auctions and is suited for volumetric purchases, where discounts for large quantities are common. The third one is a multi-attribute model, which computes the best possible solution considering several criteria and can be used in case of complex purchases that involve various categories and trade-offs and are subject to spot prices.

Several design considerations for this type of auctions are reviewed, as well as the mathematical formulation to determine the best alternative (i.e., winner) that can be solved using simple tools like Microsoft Excel. The models are optimized by a mixed-integer programming, and the multi-attribute one is developed using multi-criteria decision analysis (MCDA). All three models developed in this research showed superior results compared to the baseline, being between 9% and 20% more efficient than a regular supplier selection (singly choosing the lowest price) and improving the bidding compliance.

This study, a practice forum article, aims to presents the lessons learned and the development of a discrete event simulation model to support the funerary system management of São Paulo City, Brazil, during the COVID-19 pandemic.

A discrete event simulation model was developed by the authors as soon as the pandemic affected the city of São Paulo, Brazil. Based on the model, several scenarios with varying minimum, median and peak demands (i.e. the number of deaths) were tested and evaluated. The lessons learned from the scenario analysis and implementation of the decision-making of the city government of São Paulo are discussed in this article.

The lessons learned about the coordination, inventory management and other operational characteristics in funerary logistics during the pandemic are shared with a model, which quantifies the demand for vehicles, coffins, graves and teams in the cemeteries in different simulated scenarios.

The São Paulo State Civil Defense used this information during the pandemic to prepare the funerary system of the municipality.

The study presents methods to mitigate the sanitary, environmental and psychosocial problems related to the funerary system.

Studies on funerary systems are scarce. This study presents the results that supported the dimensioning of the funerary system during the pandemic and operational lessons about the logistics to support decision-making in future events.

This paper aims to present the internalization process by which Venezuelan migrants and refugees are resettled. Using system dynamics, the authors model a Brazilian humanitarian operation (“Acolhida” – Welcome), simulate the internalization process, propose policies and provide lessons learned for future migratory operations.

Using system dynamics simulation, the authors use Acolhida Operation’s historical data to recreate the reception and resettlement process of Venezuelan migrants and refugees. The authors identify the main bottlenecks in the system and propose policies to respond to scenarios according to the number of internalization vacancies, that is, available places in Brazil where migrants and refugees can be resettled. Finally, based on interviews with former decision-makers, the model represents a first attempt to convert the pressure of public opinion on authorities into temporary shelters as a way of reducing the number of unassisted people.

The results confirm that internalization vacancies are the main constraint when resettling Venezuelan migrants and refugees. Had the internalization program been promoted since the operation’s beginning, there would have been fewer unassisted people in Roraima and fewer shelters. The pressure-converting mechanism presented in this study, although incipient, constitutes a first attempt to support decision-makers in determining when to build temporary shelters.

This study can be useful to public authorities and humanitarian organizations when developing policies to enhance resettlement in migratory crises. In Acolhida’s case, the internalization program should continue to be the operation’s priority and can be enhanced by investing more resources to create internalization vacancies while maintaining logistical capacities.

The authors suggest policies to improve the Acolhida internalization program: give more people the choice to relocate in other cities, increase turnover in shelters and provide a more efficient and effective response to Venezuelan migration in Roraima.

Although a number of studies have applied system dynamics to humanitarian operations, few models have focused on migratory emergencies, such as those occurring in northern Brazil. The model is applied to the largest humanitarian operation carried out in the Brazilian territory and provides decision-makers with valuable insights and alternatives for better implementation in the future. Furthermore, this study narrows the gap between the social sciences and modeling and simulation techniques by proposing ways of predicting migratory implications in the construction of shelters and resettlement policies.

The purpose of this paper is to present a methodology in order to improve inspections' diagnosis during façades' service life through in‐service criteria. On‐site performance assessment and deciding on the maintenance of renders can only be improved if quantitative parameters are pre‐established at the design stage and monitored under service conditions.

The methodology is based on a set of in‐service parameters inferred from visual observation and measurements and their methods of assessment (based on visual inspections, auxiliary techniques, in‐situ and laboratorial testing). These have been arrived at by inspecting the façade rendering on 44 buildings (cement‐based renders), of different ages and types of degradation.

This paper focuses on 23 proposed mechanical and physical‐chemical parameters that can complement the ones already established by standards or technical data, obtained in lab conditions, using standard specimens or small models. They are assessed by techniques that have been applied to renders or other façade elements such as concrete or timber structures. The reliability of this in‐service performance assessment is discussed together with its potential as an aid to deciding on predictive maintenance action after an inspection's diagnosis.

The originality of this approach stems from the fact that in‐service parameters derived from both laboratory and in‐situ measurements can improve understanding of the behaviour of façade rendering, which is an important step in planning and monitoring maintenance. Two aspects are emphasised: the behaviour of materials/systems is assessed in real conditions, and the subjectivity of in‐service diagnosis is reduced when more than one performance parameter is assessed.

The aim of this research study is to develop a risk-based framework that can quantify maintainability to forecast future maintainability of a building at early stages as a decision tool to minimize increase of maintenance cost.

A survey-based approach was used to explore the risk factors in the domain of maintainability risks under tropical environmental conditions. The research derived ten risk factors based on 58 identified causes related to maintainability issues as common to high-rise buildings in tropical conditions. Impact of these risk factors was evaluated using an indicator referred to as the “maintenance score (MS)” which was derived from the “whole-life maintenance cost” involved in maintaining the expected “performance” level of the building. Further, an ensemble neural network (ENN) model was developed to model the MS for evaluating maintainability risks in high-rise buildings.

Results showed that predictions from the model were highly compatible and in the same order when compared with calculations based on actual past data. It further showed that, maintainability of buildings could be improved if the building was designed, constructed and managed properly by controlling their maintainability risks.

The ENN model was used to analyze maintainability of a high-rise building. Thus, it provides a useful tool for designers, clients, facilities managers/maintenance managers and users to analyze maintainability risks of buildings at early stages.

Maintenance is a compulsory cost in any asset's operation and requires sufficient budget to be supported. However, insufficient maintenance allocation would lead to maintenance prioritization being practiced as a solution to relief the maintenance demands. The purpose of this paper is to review and discuss the related literature on the factors considered and methods practiced in maintenance prioritization, especially in asset managements.

A thorough literature search related to factors and methods used in maintenance prioritization was conducted through several journal databases. The keywords maintenance priority, maintenance prioritization, priority management and maintenance planning were used. Publications related to maintenance priority from the period of 1990 to 2016 were reviewed and filtered out. Literature focusing on methods and factors related to maintenance prioritization were analyzed and discussed.

This study presented the trend and publications related to maintenance priority throughout 1990 to 2016. Publications related with methods and factors were analyzed. The most used priority-setting methods include analytical hierarchy process; priority criterion; priority matrix; and failure mode and effect analysis. Factors for maintenance priority were categorized into four categories which are technical, financial, social and political category. A discussion on the strategic direction of maintenance prioritization was conducted to highlight future research and possible improvements.

The paper contains a state of the art on publications and discussion related to the factors, methods and suggestions on the strategic aspect of maintenance prioritization. It offers insights and information on the current body of knowledge to academics, researchers, maintenance managers, practitioners and stakeholders concerned with asset management.