Seleção de tecnologia para minimização de emissões de compostos orgânicos voláteis durante as operações de carregamento de navios: utilização de uma ferramenta de tomada de decisão

Como em qualquer outra organização, as empresas de engenharia química vêm cada vez mais utilizando ferramentas de Tomadas de Decisão para escolhas de soluções técnicas para projetos, operações, desenvolvimento, dentre tantas. A tomada de decisão é o processo de responder a um problema, utilizando um conjunto de técnicas qualitativas e quantitativas para selecionar a solução ou ação, dentre várias alternativas que seja mais adequada para a resolução daquele problema. Dentre estas ferramentas, as mais utilizadas são a MAUT, do inglês Multiattribute Utility Theory (Teoria de Utilidade Multiatributos) e a AHP, do inglês Analytic Hierarchy Process (Processo de Análise Hierárquica).Neste trabalho, estes dois métodos são aplicados num mesmo problema de engenharia química: a seleção de um sistema para tratamento de compostos orgânicos voláteis durante o carregamento de navios que transportam petróleo e derivados. Para isto é realizada, em primeiro lugar, a descrição detalhada de cada método, a conceituação de composto orgânico volátil, a legislação pertinente e a descrição de cada alternativa como solução para controle deste tipo de emissão. Os resultados apontados pelos métodos MAUT e AHP são então comparados a fim de verificar se ambos conduzem a mesma solução. Pretende-se também observar o grau de influencia das diferentes áreas de atuação de uma organização na escolha final da tomada de decisão e verificar as percepções dos profissionais sobre cada método aplicado. Percebeu-se, entretanto, que as metodologias não conduziram, neste trabalho, a soluções idênticas, devido à influência das características de cada método, e que profissionais de uma mesma área de atuação tendem a tomarem o mesmo tipo de decisão

Deconstruction plan assessment using multi-criteria decision-making methods

The purpose of this paper is to present two multi-criteria decision-making models, including an Analytic Hierarchy Process (AHP) model and an Analytic Network Process (ANP) model for the assessment of deconstruction plans and to make a comparison between the two models with an experimental case study. Deconstruction planning is under pressure to reduce operation costs, adverse environmental impacts and duration, in the meanwhile to improve productivity and safety in accordance with structure characteristics, site conditions and past experiences. To achieve these targets in deconstruction projects, there is an impending need to develop a formal procedure for contractors to select a most appropriate deconstruction plan. Because numbers of factors influence the selection of deconstruction techniques, engineers definitely need effective tools to conduct the selection process. In this regard, multi-criteria decision-making methods such as AHP have been adopted to effectively support deconstruction technique selection in previous researches. in which it has been proved that AHP method can help decision-makers to make informed decisions on deconstruction technique selection based on a sound technical framework. In this paper, the authors present the application and comparison of two decision-making models including the AHP model and the ANP model for deconstruction plan assessment. The paper concludes that both AHP and ANP are viable and capable tools for deconstruction plan assessment under the same set of evaluation criteria. However, although the ANP can measure relationship among selection criteria and their sub-criteria, which is normally ignored in the AHP, the authors also indicate that whether the ANP model can provide a more accurate result should be examined in further research.

The analytic hierarchy process to support decision-making processes in infrastructure projects with social impact

There is an increasing awareness among all kinds of organisations (in business,government and civil society) about the benefits of jointly working with stakeholders to satisfy both their goals and the social demands placed upon them. This is particularly the case within corporate social responsibility (CSR) frameworks. In this regard, multi-criteria tools for decision-making like the analytic hierarchy process (AHP) described in the paper can be useful for the building relationships with stakeholders. Since these tools can reveal decision-maker’s preferences, the integration of opinions from various stakeholders in the decision-making process may result in better and more innovative solutions with significant shared value. This paper is based on ongoing research to assess the feasibility of an AHP-based model to support CSR decisions in large infrastructure projects carried out by Red Electrica de España, the sole transmission agent and operator of the Spanishelectricity system.

An application of the analytic hierarchy process and fuzzy logic inference in a decision support system for forage selection

Forage selection plays a prominent role in the process of returning cultivated lands back into grasslands. The conventional method of selecting forage species can only provide attempts for problem-solving without considering the relationships among the decision factors globally. Therefore, this study is dedicated to developing a decision support system to help farmers correctly select suitable forage species for the target sites. After collecting data through a field study, we developed this decision support system. It consists of three steps: (1) the analytic hierarchy process (AHP), (2) weights determination, and (3) decision making. In the first step, six factors influencing forage growth were selected by reviewing the related references and by interviewing experts. Then a fuzzy matrix was devised to determine the weight of each factor in the second step. Finally, a gradual alternative decision support system was created to help farmers choose suitable forage species for their lands in the third step. The results showed that the AHP and fuzzy logic are useful for forage selection decision making, and the proposed system can provide accurate results in a certain area (Gansu Province) of China.

Interactive management control via analytic hierarchy process (AHP). An empirical study in a public university hospital

Management control in public university hospitals is a challenging task because of continuous changes due to external pressures (e.g. economic pressures, stakeholder focuses and scientific progress) and internal complexities (top management turnover, shared leadership, technological evolution, and researcher oriented mission). Interactive budgeting contributed to improving vertical and horizontal communication between hospital and stakeholders and between different organizational levels. This paper describes an application of Analytic Hierarchy Process (AHP) to enhance interactive budgeting in one of the biggest public university hospital in Italy. AHP improved budget allocation facilitating elicitation and formalization of units' needs. Furthermore, AHP facilitated vertical communication among manager and stakeholders, as it allowed multilevel hierarchical representation of hospital needs, and horizontal communication among staff of the same hospital, as it allowed units' need prioritization and standardization, with a scientific multi-criteria approach, without using complex mathematics. Finally, AHP allowed traceability of a complex decision making processes (as budget allocation), this aspect being of paramount importance in public sectors, where managers are called to respond to many different stakeholders about their choices.

Analytic hierarchy process helps evaluate projects in Indian oil pipeline industry

Conventionally, oil pipeline projects are evaluated thoroughly by the owner before investment decision is made using market, technical and financial analysis sequentially. The market analysis determines pipelines throughput and supply and demand points. Subsequent, technical analysis identifies technological options and economic and financial analysis then derives the least cost option among all technically feasible options. The subsequent impact assessment tries to justify the selected option by addressing environmental and social issues. The impact assessment often suggests alternative sites, technologies, and/or implementation methodology, necessitating revision of technical and financial analysis. This study addresses these issues via an integrated project evaluation and selection model. The model uses analytic hierarchy process, a multiple-attribute decision-making technique. The effectiveness of the model has been demonstrated through a case application on cross-country petroleum pipeline project in India.

Benchmarking project management practices of Caribbean organizations using analytic hierarchy process

Effective management of projects is becoming increasingly important for any type of organization to remain competitive in today’s dynamic business environment due to pressure of globalization. The use of benchmarking is widening as a technique for supporting project management. Benchmarking can be described as the search for the best practices, leading to the superior performance of an organization. However, effectiveness of benchmarking depends on the use of tools for collecting and analyzing information and deriving subsequent improvement projects. This study demonstrates how analytic hierarchy process (AHP), a multiple attribute decision-making technique, can be used for benchmarking project management practices. The entire methodology has been applied to benchmark project management practice of Caribbean public sector organizations with organizations in the Indian petroleum sector, organizations in the infrastructure sector of Thailand and the UK. This study demonstrates the effectiveness of a proposed benchmarking model using AHP, determines problems and issues of Caribbean project management in the public sector and suggests improvement measures for effective project management.

Project risk management:a combined analytic hierarchy process and decision tree approach

Time, cost and quality achievements on large-scale construction projects are uncertain because of technological constraints, involvement of many stakeholders, long durations, large capital requirements and improper scope definitions. Projects that are exposed to such an uncertain environment can effectively be managed with the application of risk management throughout the project life cycle. Risk is by nature subjective. However, managing risk subjectively poses the danger of non-achievement of project goals. Moreover, risk analysis of the overall project also poses the danger of developing inappropriate responses. This article demonstrates a quantitative approach to construction risk management through an analytic hierarchy process (AHP) and decision tree analysis. The entire project is classified to form a few work packages. With the involvement of project stakeholders, risky work packages are identified. As all the risk factors are identified, their effects are quantified by determining probability (using AHP) and severity (guess estimate). Various alternative responses are generated, listing the cost implications of mitigating the quantified risks. The expected monetary values are derived for each alternative in a decision tree framework and subsequent probability analysis helps to make the right decision in managing risks. In this article, the entire methodology is explained by using a case application of a cross-country petroleum pipeline project in India. The case study demonstrates the project management effectiveness of using AHP and DTA.

Selection of power market structure using the analytic hierarchy process

Selection of a power market structure from the available alternatives is an important activity within an overall power sector reform programme. The evaluation criteria for selection are both subjective as well as objective in nature and the selection of alternatives is characterised by their conflicting nature. This study demonstrates a methodology for power market structure selection using the analytic hierarchy process (AHP), a multiple attribute decision-making technique, to model the selection methodology with the active participation of relevant stakeholders in a workshop environment. The methodology is applied to a hypothetical case of a State Electricity Board reform in India.

Application of analytic hierarchy process for measuring and comparing the global performance of intensive care units

Purpose: To develop a model for the global performance measurement of intensive care units (ICUs) and to apply that model to compare the services for quality improvement. Materials and Methods: Analytic hierarchy process, a multiple-attribute decision-making technique, is used in this study to evolve such a model. The steps consisted of identifying the critical success factors for the best performance of an ICU, identifying subfactors that influence the critical factors, comparing them pairwise, deriving their relative importance and ratings, and calculating the cumulative performance according to the attributes of a given ICU. Every step in the model was derived by group discussions, brainstorming, and consensus among intensivists. Results: The model was applied to 3 ICUs, 1 each in Barbados, Trinidad, and India in tertiary care teaching hospitals of similar setting. The cumulative performance rating of the Barbados ICU was 1.17 when compared with that of Trinidad and Indian ICU, which were 0.82 and 0.75, respectively, showing that the Trinidad and Indian ICUs performed 70% and 64% with respect to Barbados ICU. The model also enabled identifying specific areas where the ICUs did not perform well, which helped to improvise those areas. Conclusions: Analytic hierarchy process is a very useful model to measure the global performance of an ICU. © 2005 Elsevier Inc. All rights reserved.

Combining analytic hierarchy process and goal programming for logistics distribution network design

Logistics distribution network design is one of the major decision problems arising in contemporary supply chain management. The decision involves many quantitative and qualitative factors that may be conflicting in nature. This paper applies an integrated multiple criteria decision making approach to design an optimal distribution network. In the approach, the analytic hierarchy process (AHP) is used first to determine the relative importance weightings or priorities of alternative warehouses with respect to both deliverer oriented and customer oriented criteria. Then, the goal programming (GP) model incorporating the constraints of system, resource, and AHP priority is formulated to select the best set of warehouses without exceeding the limited available resources. In this paper, two commercial packages are used: Expert Choice for determining the AHP priorities of the warehouses, and LINDO for solving the GP model. © 2007 IEEE.

Green supply chain performance measurement using the analytic hierarchy process:a comparative analysis of manufacturing organisations

The main purpose of this research is to develop and deploy an analytical framework for measuring the environmental performance of manufacturing supply chains. This work's theoretical bases combine and reconcile three major areas: supply chain management, environmental management and performance measurement. Researchers have suggested many empirical criteria for green supply chain (GSC) performance measurement and proposed both qualitative and quantitative frameworks. However, these are mainly operational in nature and specific to the focal company. This research develops an innovative GSC performance measurement framework by integrating supply chain processes (supplier relationship management, internal supply chain management and customer relationship management) with organisational decision levels (both strategic and operational). Environmental planning, environmental auditing, management commitment, environmental performance, economic performance and operational performance are the key level constructs. The proposed framework is then applied to three selected manufacturing organisations in the UK. Their GSC performance is measured and benchmarked by using the analytic hierarchy process (AHP), a multiple-attribute decision-making technique. The AHP-based framework offers an effective way to measure and benchmark organisations’ GSC performance. This study has both theoretical and practical implications. Theoretically it contributes holistic constructs for designing a GSC and managing it for sustainability; and practically it helps industry practitioners to measure and improve the environmental performance of their supply chain. © 2013 Copyright Taylor and Francis Group, LLC. CORRIGENDUM DOI 10.1080/09537287.2012.751186 In the article ‘Green supply chain performance measurement using the analytic hierarchy process: a comparative analysis of manufacturing organisations’ by Prasanta Kumar Dey and Walid Cheffi, Production Planning & Control, 10.1080/09537287.2012.666859, a third author is added which was not included in the paper as it originally appeared. The third author is Breno Nunes.

Analytic hierarchy process analyses risk of operating cross-country petroleum pipelines in India

The existing method of pipeline health monitoring, which requires an entire pipeline to be inspected periodically, is both time-wasting and expensive. A risk-based model that reduces the amount of time spent on inspection has been presented. This model not only reduces the cost of maintaining petroleum pipelines, but also suggests an efficient design and operation philosophy, construction methodology, and logical insurance plans. The risk-based model uses the analytic hierarchy process (AHP), a multiple-attribute decision-making technique, to identify the factors that influence failure on specific segments and to analyze their effects by determining probability of risk factors. The severity of failure is determined through consequence analysis. From this, the effect of a failure caused by each risk factor can be established in terms of cost, and the cumulative effect of failure is determined through probability analysis. The technique does not totally eliminate subjectivity, but it is an improvement over the existing inspection method.

Applying the Analytic Hierarchy Process in healthcare research: A systematic literature review and evaluation of reporting

Background: The Analytic Hierarchy Process (AHP), developed by Saaty in the late 1970s, is one of the methods for multi-criteria decision making. The AHP disaggregates a complex decision problem into different hierarchical levels. The weight for each criterion and alternative are judged in pairwise comparisons and priorities are calculated by the Eigenvector method. The slowly increasing application of the AHP was the motivation for this study to explore the current state of its methodology in the healthcare context. Methods: A systematic literature review was conducted by searching the Pubmed and Web of Science databases for articles with the following keywords in their titles or abstracts: "Analytic Hierarchy Process," "Analytical Hierarchy Process," "multi-criteria decision analysis," "multiple criteria decision," "stated preference," and "pairwise comparison." In addition, we developed reporting criteria to indicate whether the authors reported important aspects and evaluated the resulting studies' reporting. Results: The systematic review resulted in 121 articles. The number of studies applying AHP has increased since 2005. Most studies were from Asia (almost 30 %), followed by the US (25.6 %). On average, the studies used 19.64 criteria throughout their hierarchical levels. Furthermore, we restricted a detailed analysis to those articles published within the last 5 years (n = 69). The mean of participants in these studies were 109, whereas we identified major differences in how the surveys were conducted. The evaluation of reporting showed that the mean of reported elements was about 6.75 out of 10. Thus, 12 out of 69 studies reported less than half of the criteria. Conclusion: The AHP has been applied inconsistently in healthcare research. A minority of studies described all the relevant aspects. Thus, the statements in this review may be biased, as they are restricted to the information available in the papers. Hence, further research is required to discover who should be interviewed and how, how inconsistent answers should be dealt with, and how the outcome and stability of the results should be presented. In addition, we need new insights to determine which target group can best handle the challenges of the AHP. © 2015 Schmidt et al.