Decision support system for inspection and maintenance:a case of oil pipelines

The existing method of pipeline health monitoring, which requires an entire pipeline to be inspected periodically, is unproductive. A risk-based decision support system (DSS) that reduces the amount of time spent on inspection has been presented. The risk-based DSS uses the analytic hierarchy process (AHP), a multiple attribute decision-making technique, to identify the factors that influence failure on specific segments and analyzes their effects by determining probability of occurrence of these 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 model optimizes the cost of pipeline operations by reducing subjectivity in selecting a specific inspection method, identifying and prioritizing the right pipeline segment for inspection and maintenance, deriving budget allocation, providing guidance to deploy the right mix labor for inspection and maintenance, planning emergency preparation, and deriving logical insurance plan. The proposed methodology also helps derive inspection and maintenance policy for the entire pipeline system, suggest design, operational philosophy, and construction methodology for new pipelines.

Integrated project evaluation and selection using multiple-attribute decision-making technique

The evaluation and selection of industrial projects before investment decision is customarily done using marketing, technical and financial information. Subsequently, environmental impact assessment and social impact assessment are carried out mainly to satisfy the statutory agencies. Because of stricter environment regulations in developed and developing countries, quite often impact assessment suggests alternate sites, technologies, designs, and implementation methods as mitigating measures. This causes considerable delay to complete project feasibility analysis and selection as complete analysis requires to be taken up again and again till the statutory regulatory authority approves the project. Moreover, project analysis through above process often results sub-optimal project as financial analysis may eliminate better options, as more environment friendly alternative will always be cost intensive. In this circumstance, this study proposes a decision support system, which analyses projects with respect to market, technicalities, and social and environmental impact in an integrated framework using analytic hierarchy process, a multiple-attribute decision-making technique. This not only reduces duration of project evaluation and selection, but also helps select optimal project for the organization for sustainable development. The entire methodology has been applied to a cross-country oil pipeline project in India and its effectiveness has been demonstrated. © 2005 Elsevier B.V. All rights reserved.

Performance measurement of intensive care services in hospitals:The case of Barbados

The Intensive Care Unit (ICU) being one of those vital areas of a hospital providing clinical care, the quality of service rendered must be monitored and measured quantitatively. It is, therefore, essential to know the performance of an ICU, in order to identify any deficits and enable the service providers to improve the quality of service. Although there have been many attempts to do this with the help of illness severity scoring systems, the relative lack of success using these methods has led to the search for a form of measurement, which would encompass all the different aspects of an ICU in a holistic manner. The Analytic Hierarchy Process (AHP), a multiple-attribute, decision-making technique is utilised in this study to evolve a system to measure the performance of ICU services reliably. This tool has been applied to a surgical ICU in Barbados; we recommend AHP as a valuable tool to quantify the performance of an ICU. Copyright © 2004 Inderscience Enterprises Ltd.

Decision support system for project selection

The evaluation and selection of industrial projects before investment decision is customarily done using marketing, technical, and financial information. Subsequently, environmental impact assessment and social impact assessment are carried out mainly to satisfy the statutory agencies. Because of stricter environment regulations in developed and developing countries, quite often impact assessment suggests alternate sites, technologies, designs, and implementation methods as mitigating measures. This causes considerable delay to complete project feasibility analysis and selection as complete analysis requires to be taken up again and again until the statutory regulatory authority approves the project. Moreover, project analysis through the above process often results in suboptimal projects as financial analysis may eliminate better options as more environment friendly alternative will always be cost intensive. In this circumstance, this study proposes a decision support system which analyses projects with respect to market, technicalities, and social and environmental impact in an integrated framework using analytic hierarchy process, a multiple attribute decision-making technique. This not only reduces duration of project evaluation and selection, but also helps select an optimal project for the organization for sustainable development. The entire methodology has been applied to a cross-country oil pipeline project in India and its effectiveness has been demonstrated. © 2008, IGI Global.

A risk-based model for inspection and maintenance of cross-country petroleum pipeline

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 efficient design and operation philosophy, construction methodology and logical insurance plans. The risk-based model uses Analytic Hierarchy Process (AHP), a multiple attribute decision-making technique, to identify the factors that influence failure on specific segments and analyzes 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.

Decision support system for risk management:a case study

This study demonstrates a quantitative approach to construction risk management through analytic hierarchy process and decision tree analysis. All the risk factors are identified, their effects are quantified by determining probability and severity, and various alternative responses are generated with cost implication for mitigating the quantified risks. The expected monetary values are then derived for each alternative in a decision tree framework and subsequent probability analysis aids the decision process in managing risks. The entire methodology is explained through a case application of a cross-country petroleum pipeline project in India and its effectiveness in project management is demonstrated.

Construction risk management:a quantitative approach

Conventional project management techniques are not always sufficient for ensuring time, cost and quality achievement of large-scale construction projects due to complexity in planning and implementation processes. The main reasons for project non-achievement are changes in scope and design, changes in Government policies and regulations, unforeseen inflation) under-estimation and improper estimation. Projects that are exposed to such an uncertain environment can be effectively managed with the application of risk numagement throughout project life cycle. However, the effectiveness of risk management depends on the technique in which the effects of risk factors are analysed and! or quantified. This study proposes Analytic Hierarchy Process (AHP), a multiple attribute decision-making technique as a tool for risk analysis because it can handle subjective as well as objective factors in decision model that are conflicting in nature. This provides a decision support system (DSS) to project managenumt for making the right decision at the right time for ensuring project success in line with organisation policy, project objectives and competitive business environment. The whole methodology is explained through a case study of a cross-country petroleum pipeline project in India and its effectiveness in project1nana.gement is demonstrated.

Risk based decision support system for effective implementation of projects

Conventional project management techniques are not always sufficient to ensure time, cost and quality achievement of large-scale construction projects due to complexity in planning, design and implementation processes. The main reasons for project non-achievement are changes in scope and design, changes in government policies and regulations, unforeseen inflation, underestimation and improper estimation. Projects that are exposed to such an uncertain environment can be effectively managed with the application of risk management throughout the project's life cycle. However, the effectiveness of risk management depends on the technique through which the effects of risk factors are analysed/quantified. This study proposes the Analytic Hierarchy Process (AHP), a multiple attribute decision making technique, as a tool for risk analysis because it can handle subjective as well as objective factors in a decision model that are conflicting in nature. This provides a decision support system (DSS) to project management for making the right decision at the right time for ensuring project success in line with organisation policy, project objectives and a competitive business environment. The whole methodology is explained through a case application of a cross-country petroleum pipeline project in India and its effectiveness in project management is demonstrated.

Multiple attribute decision making approach to petroleum pipeline route selection

Petroleum pipelines are the nervous system of the oil industry, as this transports crude oil from sources to refineries and petroleum products from refineries to demand points. Therefore, the efficient operation of these pipelines determines the effectiveness of the entire business. Pipeline route selection plays a major role when designing an effective pipeline system, as the health of the pipeline depends on its terrain. The present practice of route selection for petroleum pipelines is governed by factors such as the shortest distance, constructability, minimal effects on the environment, and approachability. Although this reduces capital expenditure, it often proves to be uneconomical when life cycle costing is considered. This study presents a route selection model with the application of an Analytic Hierarchy Process (AHP), a multiple attribute decision making technique. AHP considers all the above factors along with the operability and maintainability factors interactively. This system has been demonstrated here through a case study of pipeline route selection, from an Indian perspective. A cost-benefit comparison of the shortest route (conventionally selected) and optimal route establishes the effectiveness of the model.

Optimization of facility location-allocation problem in customer-driven supply chain

This paper develops and applies an integrated multiple criteria decision making approach to optimize the facility location-allocation problem in the contemporary customer-driven supply chain. Unlike the traditional optimization techniques, the proposed approach, combining the analytic hierarchy process (AHP) and the goal programming (GP) model, considers both quantitative and qualitative factors, and also aims at maximizing the benefits of deliverer and customers. In the integrated approach, the AHP is used first to determine the relative importance weightings or priorities of alternative locations with respect to both deliverer oriented and customer oriented criteria. Then, the GP model, incorporating the constraints of system, resource, and AHP priority is formulated to select the best locations for setting up the warehouses without exceeding the limited available resources. In this paper, a real case study is used to demonstrate how the integrated approach can be applied to deal with the facility location-allocation problem, and it is proved that the integrated approach outperforms the traditional costbased approach.

An integrated multiple criteria decision making approach for resource allocation in higher education

Resource allocation is one of the major decision problems arising in higher education. Resources must be allocated optimally in such a way that the performance of universities can be improved. This paper applies an integrated multiple criteria decision making approach to the resource allocation problem. In the approach, the Analytic Hierarchy Process (AHP) is first used to determine the priority or relative importance of proposed projects with respect to the goals of the universities. Then, the Goal Programming (GP) model incorporating the constraints of AHP priority, system, and resource is formulated for selecting the best set of projects without exceeding the limited available resources. The projects include 'hardware' (tangible university's infrastructures), and 'software' (intangible effects that can be beneficial to the university, its members, and its students). In this paper, two commercial packages are used: Expert Choice for determining the AHP priority ranking of the projects, and LINDO for solving the GP model. Copyright © 2007 Inderscience Enterprises Ltd.

Strategic logistics outsourcing:an integrated QFD and fuzzy AHP approach

This paper develops an integratedapproach, combining quality function deployment (QFD), fuzzy set theory, and analytic hierarchy process (AHP) approach, to evaluate and select the optimal third-party logistics service providers (3PLs). In the approach, multiple evaluating criteria are derived from the requirements of company stakeholders using a series of house of quality (HOQ). The importance of evaluating criteria is prioritized with respect to the degree of achieving the stakeholder requirements using fuzzyAHP. Based on the ranked criteria, alternative 3PLs are evaluated and compared with each other using fuzzyAHP again to make an optimal selection. The effectiveness of proposed approach is demonstrated by applying it to a Hong Kong based enterprise that supplies hard disk components. The proposed integratedapproach outperforms the existing approaches because the outsourcing strategy and 3PLs selection are derived from the corporate/business strategy.

Whole life performance bid evaluation in the Korean public sector

Korea has increasingly adopted design-build for public construction projects in the last few years. There is a much greater awareness of the need to change a system based on ‘Value for Money’ which is high on the government's agenda. A whole life performance bid evaluation model is proposed to aid decision makers in the selection of a design-builder. This is based on the integration of a framework using an analytic hierarchy process as the bid awarding system is being changed from one based on lowest price, to one based on best value over the life-cycle. Key criteria like whole life cost, service life planning and design quality are important through the key stages of evaluation process. The model uses a systematic and holistic approach which enables a public sector to make better decisions in design-builder selection, which will deliver whole life benefits, based on long term cost-effectiveness and whole life.

Decision support system for spare parts warehousing

Spare parts warehousing decision-making plays an important role in today's manufacturing industry as it derives an optimum inventory policy for the organizations. Previous research on spare parts warehousing decision-making did not deal with the problem holistically considering all the subjective and objective criteria of operational and strategic needs of the manufacturing companies in the process industry. This study reviews current relevant literature and develops a conceptual framework (an integrated group decision support system) for selecting the most effective warehousing option for the process industry using the analytic hierarchy process (AHP). The framework has been applied to a multinational cement manufacturing company in the UK. Three site visits, eight formal interviews, and several discussions have been undertaken with personnel of the organization, many of which have more than 20 years of experience, in order to apply the proposed decision support system (DSS). Subsequently, the DSS has been validated through a questionnaire survey in order to establish its usefulness, effectiveness for warehousing decision-making, and the possibility of adoption. The proposed DSS is an integrated framework for selecting the best warehousing option for business excellence in any manufacturing organization.

Project risk management using multiple criteria decision-making technique and decision tree analysis:a case study of Indian oil refinery

This study proposes an integrated analytical framework for effective management of project risks using combined multiple criteria decision-making technique and decision tree analysis. First, a conceptual risk management model was developed through thorough literature review. The model was then applied through action research on a petroleum oil refinery construction project in the Central part of India in order to demonstrate its effectiveness. Oil refinery construction projects are risky because of technical complexity, resource unavailability, involvement of many stakeholders and strict environmental requirements. Although project risk management has been researched extensively, practical and easily adoptable framework is missing. In the proposed framework, risks are identified using cause and effect diagram, analysed using the analytic hierarchy process and responses are developed using the risk map. Additionally, decision tree analysis allows modelling various options for risk response development and optimises selection of risk mitigating strategy. The proposed risk management framework could be easily adopted and applied in any project and integrated with other project management knowledge areas.