Isabel L. Nunes

Fuzzy approach for reducing subjectivity in estimating occupational accident severity

Quantifying or, more generally, estimating the severity of the possible consequences of occupational accidents is a decisive step in any occupational risk assessment process. Because of the lack of historic information (accident data collection and recording are incipient and insufficient, particularly in construction) and the lack of practical tools in the construction industry, the estimation/quantification of occupational accident severity is a notably arbitrary process rather than a systematic and rigorous assessment. This work proposes several severity functions (based on a safety risk assessment) to represent biomechanical knowledge with the aim of determining the severity level of occupational accidents in the construction industry and, consequently, improving occupational risk assessment quality. We follow a fuzzy approach because it makes it possible to capture and represent imprecise knowledge in a simple and understandable way for users and specialists.

Usability of Interfaces

Adequate usability is important because it is a characteristic of product quality that leads to improving product acceptability, increasing user satisfaction, improving product reliability and it is also financially beneficial to companies. Such benefit can be seen from two points of view, one related with workers’ productivity (less training time and faster task completion), and the other with product sells (products are easier to sell and market themselves, when users had positive experiences) (Nunes, 2006).

Qualitative Model for Risk Assessment in Construction Industry: A Fuzzy Logic Approach

Risk Assessment for Health and Safety (RAH&S) of workers is a complex task that entails the consideration of many parameters which are, more often than not, difficult to quantify. RAH&S in the construction industry is rampant with inadequate data and/or imprecise and incomplete information, particularly in the design stage, for which traditional quantitative approaches do not give adequate answers. In this work we outline the basic aspects for a Qualitative Risk Assessment Model (QRAM) based on elicited data and using a fuzzy logic approach.

A Fuzzy Multicriteria Methodology to Manage Priorities and Resource Assignment in Critical Situations

Humanitarian Assistance and Disaster Relief operations require strong Crises Management capabilities and this call for robust decision-making support tools. This chapter addresses the main requirements to comply by such systems considering both the desired level of interaction maturity among organizations and the characteristics of an emergency management system. It further presents the SINGRAR (Integrated System for Priority Management and Resource Assignment) which is an emergency management model developed for implementing fuzzy distributed emergency management expert systems that (a) provide a common platform for the compilation of the incident status, (b) include decision support system features that provide support for managing priorities of alternative courses of action based on the current operational context, (c) support the command and control process, (d) act as an expert system advising lines of actions, and (e) federate different databases which are used in conjunction with the knowledge base. The chapters includes a case study where is illustrated the application of the model in a complex inter-agency emergency management scenario.

Integration of human factors principles in LARG organizations – a conceptual model

Nowadays many companies are undergoing organizational transformations in order to meet the changing market demands. Thus, in order to become more competitive, supply chains (SC) are adopting new management paradigms to improve SC performance: lean, agile, resilient and green (LARG paradigms). The implementation of new production paradigms demands particular care with the issues related with Human Factors to avoid health and safety problems to workers and losses to companies. Thus, the successful introduction of these new production paradigms depends among others on a Human Factors oriented approach. This work presents a conceptual framework that allows integrating ergonomic and safety design principles during the different implementation phases of lean, agile, resilient and green practices.

Empirical Studies in User Experience of an Emergency Management System

A system designed following usability principles, and considering users preferences and expectations ensures a high quality of user experience, which is particularly important when the system is used to support complex tasks. That is the case of emergency response operations’ coordination and execution. This work, conducted using an action research methodology, addresses challenges faced by the THEMIS project team during the conceptualization, design and implementation of an emergency management intelligent system, aiming to support disaster response operations and to improve the planning and execution efforts in disaster and crisis’ scenarios.

Applications of Fuzzy Logic in Risk Assessment - The RA_X Case

Risk management for work accidents and occupational diseases is of utmost importance considering the high toll paid each year in human life, human suffering and the social and economical costs resulting from work accidents and work-related disorders. According to European Agency for Safety and Health at Work every year 5,720 people die in the European Union (EU) as a consequence of work-related accidents (EASHW, 2010). The same Agency points that the International Labour Organisation estimates that an additional 159,500 workers die every year from occupational diseases in the EU. Taking both figures into consideration, it is estimated that every three-and-a-half minutes somebody in the EU dies from work-related causes. EUROSTAT performed the Labour Force Survey 2007 regarding the situation on accidents at work and work-related health problems for the 27 EU Member States (EU-27). The main findings were (Eurostat, 2009):

Knowledge Management in the Development of an Intelligent System to Support Emergency Response

Intelligent systems use applied artificial intelligence techniques with the aim of reaching, in a specific domain, a level of analysis and performance comparable to human experts. Intelligent systems are able to engage in complex inference processes, necessary for evaluating alternative options, presenting high quality conclusions and advice, and to offer explanations about the rationale that led to such conclusions. Knowledge Management is a key process associated to the development of intelligent systems, since it elicits, codifies, validates and relates the knowledge elements that are stored in the system’s Knowledge Base. The paper focus on the issues involved in the design of the THEMIS intelligent system’s Knowledge Base, and of the cooperative and participatory processes applied for knowledge elicitation, referring the usage of ontologies and UML use-cases. THEMIS project purpose is to develop an intelligent system to support complex and stressful Emergency Management activities. The outcome of the described Knowledge Management process can be determinant to quality of the user experience when exploiting the system, since most of the pragmatic and hedonic qualities of the interactions of an intelligent system are closely related with the characteristics of the underlying knowledge base and inferencing process.

Augmented Reality in Support of Disaster Response

Disaster Management is a complex process, usually dealing with a large amount of uncertain, incomplete and vague information, which normally requires the coordination and collaboration among a variety of actors. THEMIS (disTributed Holistic Emergency Management Intelligent System) is designed as an intelligent system aimed at supporting real time disaster management activities of decision-makers in command posts, and responders in the field. It gathers information from multiple sources (e.g., users, sensors, crowdsourcing), and provides situational awareness based on a georeferenced common picture which is shared among system users This paper presents the preliminary work developed in the context of the THEMIS project addressing the use of Augmented Reality by first responders in a context of disasters relief operations.

A fuzzy expert system model to deal with supply chain disturbances

A fuzzy expert system methodology is proposed, based on the combination of bow-tie diagrams and fuzzy set theory. It was designed to support the management of supply-chain (SC) disturbances. Such disturbances are understood as risks to the SC. This methodology includes a phased process starting with the analysis of potential disturbances using cause-and-effect diagrams, followed by a bow-tie analysis relating disturbances, causes, barriers and consequences, used to derive fuzzy rules applied in the SC risk assessment, and ending with advice on mitigating measures to control the consequences of disturbances. The evaluation of the methodology based on scenarios offered promising results about its capabilities.