BOCR framework for decision analysis

This paper considers establishing a framework for modellig decision analysis problems where the analyst must cope with uncertainty, multiple objectives, multiple attributes and multiple actors. These probems rise when considering large scale and complex decision problems encountered in real world applications in domains such as risk assessment and managment, infrastrucutres planning, complex process monitoring, supply chain planning, etc. To tackle this modelling chalenges, we propose to use BOCR (benefit, opportunity, cost, and risk) paradigm to identify attributes that must characterize an alternative with regard to a given objective. Then Bayesian network and/or AHP (analytic hierrarchy process) analysis can be used to assess the values of these later attributes. Finally an aggregation method based on satisficing game is developed that permit to evaluate each alternative by two measures: selectability degree constructed using “positive” attributes (benefit and opportunity) and the rejectability degree built on “negative” attributes (cost and risk)

Hazard function deployment: a QFD-based tool for the assessment of working tasks–a practical study in the construction industry

Despite the efforts made, the number of accidents has not significantly decreased in the construction industry. The main reasons can be found in the peculiarities of working activities in this sector, where hazard analysis and safety management are more difficult than in other industries. To deal with these problems, a comprehensive approach for hazard analysis is needed, focusing on the activities in which a working task is articulated since they are characterized by different types of hazards and thus risk levels. The study proposes a methodology that integrates quality function deployment (QFD) and analytic network process methods to correlate working activities, hazardous events and possible consequences. This provides more effective decision-making, while reducing the ambiguity of the qualitative assessment criteria. The results achieved can augment knowledge on the usability of QFD in safety research, providing a basis for its application for further studies

Subcontractor Selection Review Industry XYZ With Analytic Network Process (ANP) Method

In the steel construction of the Kendari Newport Container Facilitiy and Utilities Project's which was undertaken by the XYZ Contractor, there was a problem. Until the contractor issued a warning letter against the selected subcontractor because of delays in work. This research aims to examine the stages of selection subcontractors whether there is an error in decision making that causes delays work by subcontractor that selected as a partners.Therefore, decision makers need right selection methods. Multi Criteria Decision Making (MCDM) method is an appropriate method for the selection of several criteria. One of them is the Analytic Network Process (ANP) -Risk Assessment method.Based on the analysis using the ANP method ,sub-criteria with the highest priority weight is the bid price with a weight of 17.13%, The final results of the overall analysis showed that subcontractor B get in first place with a score 2,97. In this research subcontractor B has the highest value, which means that the subcontractor is feasible and accordance with the assessment of XYZ Company to be a partner to doing the steel construction work in this case stud

Improved Decision Model for Evaluating Risks in Construction Projects

The paper develops an innovative risk evaluation methodology to address the challenges of multicriteria decision-making problem of project evaluation and selection. The methodology considers the fuzzy analytic network process (FANP) to incorporate the interdependencies of different risk factors, and failure mode and effect analysis (FMEA) to conduct the rating analysis of projects to develop the decision matrix. Finally, evaluation based on the distance from the average solution compares alternative projects and reports the optimal solution. The proposed approach allows project managers to engage in the evaluation process and to use fuzzy linguistic values in the assessment process. A case study from the construction sector is selected to verify the efficacy of the proposed approach over other popular approaches in the literature

A RISK-BASED VERIFICATION FRAMEWORK FOR OFFSHORE WIND FARM DEVELOPMENT: DESIGN, INSTALLATION, OPERATIONS AND MAINTENANCE OF OFFSHORE WIND TURBINES

This thesis encompasses a holistic review of the development trends in wind turbine technology (onshore and offshore) and the challenges perceived at the stages of design, construction and operations of modern-day wind energy technology (Friedrich and Lukas, 2017). The main focus of this study is to evaluate the risks associated with offshore wind farm development (OWFD). This is achieved by first estimating those perceived risks, understanding the relative importance of each individual risk, and carrying out an assessment using a specialist analytical tool known as AHiP-Evi. AHiP-Evi was developed through a combination of application of Analytic Hierarchy Process (AHP) and Evidential Reasoning (ER) techniques. The AHP was used to ascertain the weighting of the respective risk variables according to their relative importance, while the ER was used to evaluate the aggregated influence of the collective risk variables associated with the OWFD. Finally, a specific modelling tool known as BN-SAT (Bayesian Network Sensitivity Analysis Technique) was developed to evaluate the probabilities of occurrence of the variable nodes and their overall impacts on the decision node (OWFD). The BN-SAT is comprised of a combination of Bayesian networks (BNs) concepts and a sensitivity analysis (SA) approach. The AHiP-Evi model initially developed in this study is transformed into the BN structure in order to compute the conditional and unconditional prior probability for each starting node using the NETICA analytical software to determine the aggregated impact of the specific risk variables on the OWFD. The outcome from this modelling analysis is then compared to the initial assessment carried out by the application of the AHiP-Evi modelling tool in order to validate the robustness of both modelling tools. In the case study of this research, the percentage difference of the outcomes of the two models is insignificant, which demonstrates the fact that both systems are effective. The Fuzzy Analytic Hierarchy Process (FAHP) and Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) were integrated to develop a specific model for the selection of best-case risk management technique (RMT). Based on the decision makers’ (DMs) aggregated judgements, it was possible to compute the values and determine the best-case RMT dependent on the decision variables driving the decision - for example, costs and benefits, through the developed integrated model known as FAHP-FTOPSIS. The outcome of this selection model has been seen to be reasonably practical and a successful conclusion of the research contribution. Awareness of the aggregated impact of the risk variables is important in making the decision about appropriate investments in a strategic improvement of risk management and efficient resource allocations to the offshore wind industry

A decision support system for demolition safety risk assessment

Demolition can be defined as dismantling, razing, destroying or wrecking of any building or structure or any part thereof. Demolition work involves many of the hazards associated with construction. However, demolition also involves additional hazards due to unknown factors which makes demolition work particularly dangerous. In order to make the demolition project safer, everyone at a demolition site must be fully aware of the hazards they may encounter and the safety precautions that they must take to protect themselves and their employees. Safety risk assessment is a planning tool that can be used to improve safety performance at demolition site. In the absence of a special tool for demolition safety risk assessment, a prototype Decision Support System (DSS) based on failure mode and effect analysis that enables decision makers to systematically and semi-quantitatively identify, analyze and evaluate safety risks factors in demolition project has been developed. The prototype is named Hybrid Demolition Safety Risk Assessor (HDSRA). It has three modules; (i) safety risk identification, (ii) safety risk analysis and (iii) safety risk evaluation. Module one aids the decision makers to identify thirty-seven safety risks that is developed by reviewing safety literatures and forming consensus among Delphi panel of experts. In addition, the module introduces seven immediate causes that trigger occurrence of those thirty-seven safety risks. The second module comprised a hybrid decision making model based on Decision Making Trial and Evaluation Laboratory (DEMATEL) and Analytic Network Process (ANP) that relatively estimates likelihood of thirty-seven safety risks with respect to seven immediate causes. The third module evaluates and prioritizes the safety risks by using two ranking methods; Analytic Hierarchy Process (AHP) and VIseKriterijumska Optimizacija I Kompromisno Resenje (VIKOR). The HDSRA prototype is then developed by integrating module 1, 2 and 3 and evaluated by a group of demolition experts. HDSRA acts as information source that can be used by demolition contractors to identify safety risks in a systematic way. Therefore, possibility of raising error during risk identification process in the implementation of demolition work is reduced. Decision support system that is produced by the HDSRA prototype, proactively proposes action that should be taken by demolition safety experts to control risks at workplace. And finally, HDSRA can be also used as a training tool to raise safety awareness among demolition workers

Selection of maintenance, renewal and improvement projects in rail lines using the analytic network process

[EN] This paper addresses one of the most common problems that a railway infrastructure manager has to face: to prioritise a portfolio of maintenance, renewal and improvement (MR&I) projects in a railway network. This decision-making problem is complex due to the large number of MR&I projects in the portfolio and the different criteria to take into consideration, most of which are influenced and interrelated to each other. To address this problem, the use of the analytic network process (ANP) is proposed. The method is applied to a case study in which the Local Manager of the public company, who is responsible for the MR&I of Spanish Rail Lines, has to select the MR&I projects which have to be executed first. Based on the results, it becomes evident that, for this case study, the main factor of preference for a project is the location of application rather than the type of project. The main contributions of this work are: the deep analysis done to identify and weigh the decision criteria, how to assess the alternatives and provide a rigorous and systematic decision-making process, based on an exhaustive revision of the literature and expertiseThe translation of this paper was funded by the Universitat Politecnica de Valencia.Montesinos-Valera, J.; Aragonés-Beltrán, P.; Pastor-Ferrando, J. (2017). Selection of maintenance, renewal and improvement projects in rail lines using the analytic network process. Structure and Infrastructure Engineering. 13(11):1476-1496. https://doi.org/10.1080/15732479.2017.1294189S147614961311Abril, M., Barber, F., Ingolotti, L., Salido, M. A., Tormos, P., & Lova, A. (2008). An assessment of railway capacity. Transportation Research Part E: Logistics and Transportation Review, 44(5), 774-806. doi:10.1016/j.tre.2007.04.001Ahern, A., & Anandarajah, G. (2007). 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Offshoring Decision based on a framework for risk identification

[EN] Offshoring has been a growing practice in the last decade. This involves transferring or sharing management control of a business process (BP) to a supplier in a different country. Offshoring implicates information exchange, coordination and trust between the overseas supplier and the company that means to assume risk. In this paper categories and types of risk have been hierarchically classified using a new approach with the aim to propose a multilevel reference model for Supply Chain Risk evaluation. This classification has been used to analysis the offshoring decision taking into account not only operational and financial risks but other aspects as strategic, compliance, reputation and environmental. The proper risk identification can help to take the correct decision whether or not to bet on offshoring or maintain all the processes in the country of origin.Franconetti Rodríguez, P.; Ortiz Bas, Á. (2013). Offshoring Decision based on a framework for risk identification. IFIP Advances in Information and Communication Technology. 408:540-547. doi:10.1007/978-3-642-40543-3_57S540547408Aron, R., Singh, J.V.: Getting Offshoring Right. Harvard Bus. Rev. 83, 135–155 (2005)Contractor, F.J., Kumar, V., Sumit, V., Kundu, K., Pedersen, J.: Reconceptualizing the Firm in a World of Outsourcing and Offshoring: The Organizational and Geographical Relocation of High-Value Company Functions. J. Manage. Stud. 47, 1417–1433 (2010)Holweg, M., Reichhart, A., Hong, E.: On risk and cost in global sourcing, Int. J. Int. J. Prod. Econ. 131, 333–341 (2011)Kleindorfer, P.R., Saad, G.H.: Managing Disruption Risks in Supply Chains. Prod. Oper. Manag. 14, 53–68 (2005)Neiger, D., Rotaru, K., Churilov, L.: Supply chain risk identification with value-focused process engineering. J. Oper. Manag. 27, 154–168 (2009)Kumar, S., Kwong, A., Misra, C.: Risk mitigation in offshoring of business operations. J. Manufac. Tech. Manag. 20, 442–459 (2009)Bandaly, D., Satir, A., Kahyaoglu, Y., Shanker, L.: Supply chain risk management –I: Conceptualization, framework and planning process. Risk Management 14, 249–271 (2012)Klimov, R., Merkuryev, Y.: Simulation model for supply chain reliability evaluation. Balt. J. Sust. 14, 300–311 (2008)Chopra, S., Sodhi, M.S.: Managing Risk To Avoid Supply-Chain Breakdown. MIT Sloan management review 53 (2004)Blackhurst, J.V., Scheibe, K.P., Johnson, D.J.: Supplier risk assessment and monitoring for the automotive industry. Int. J. Phys. Distrib. 38, 143–165 (2008)Tang, O., Musa, S.N.: Identifying risk issues and research advancements in supply chain risk management, Int. J. Production Economics 133, 25–34 (2011)Christopher, M., Mena, C., Khan, O.: Approaches to managing global sourcing risk. Supply Chain Manag 16, 67–81 (2011)Olson, D.L., Wu, D.: Risk Management models for supply chain: a scenario analysis of outsourcing to China. Supply Chain Manag 16, 401–408 (2011)Supply Chain Council, Inc. SCOR: The Supply Chain Reference ISBN 0615202594Lambert, D.: Supply Chain Management: Processes, Partnerships, Performance, 3rd edn.Kern, D., Moser, R., Hartmann, E.: Supply risk management: model development and empirical analysis. Int. J. Phys. Distrib. 42, 60–82 (2008)Saaty, T.L.: The analytic hierarchy and analytic network measurement processes: Applications to decisions under Risk. Eur. J. Pure. Appl. Math., 122–196 (2008)Lockamy III, A., McCormack, K.: Analysing risks in supply networks to facilitate outsourcing decisions. Int. J. Prod. Res. 48(2), 593–611 (2010