an analytic hierarchy process based model for the selection of decision categories in maintenance systems

Abstract This paper presents a model, based on Analytic Hierarchy Process, to support a maintenance manager with a suitable tool for focusing on the most relevant choices which need to be prioritized. The paper provides an insight on how structural and infra-structural decision elements, traditionally conceived for assessing the manufacturing strategy of a company, could be adopted as criteria for configuring a maintenance system. A model based on Analytic Hierarchy Process has been developed and tested in two industrial case studies in order to demonstrate how it can guide a maintenance manager in keeping the strategic decisions coherently with the overall company's manufacturing strategy. Main beneficiaries are mainly maintenance managers who have to tackle relevant strategic decisions in managing their maintenance systems. Given the increasing role of maintenance within the operations strategy of a company, the heterogeneity of actors involved, with the relevant risk of assuming conflicting decisions, it is of utmost importance to lever on adequate and shared decision support systems rather than relying on a mere empirical knowledge. The model proposed in this paper, based on the Analytic Hierarchy Process, fills this gap since it provides a structured support in the decision making process by comparing and prioritising the relevant strategic decisions pertaining to the configuration of a maintenance system

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). Railway projects prioritisation for investment: Application of goal programming. Transport Policy, 14(1), 70-80. doi:10.1016/j.tranpol.2006.10.003Al-Harbi, K. M. A.-S. (2001). Application of the AHP in project management. International Journal of Project Management, 19(1), 19-27. doi:10.1016/s0263-7863(99)00038-1Aragonés-Beltrán, P., Chaparro-González, F., Pastor-Ferrando, J. P., & Rodríguez-Pozo, F. (2010). An ANP-based approach for the selection of photovoltaic solar power plant investment projects. Renewable and Sustainable Energy Reviews, 14(1), 249-264. doi:10.1016/j.rser.2009.07.012Aragonés-Beltrán, P., Chaparro-González, F., Pastor-Ferrando, J.-P., & Pla-Rubio, A. (2014). An AHP (Analytic Hierarchy Process)/ANP (Analytic Network Process)-based multi-criteria decision approach for the selection of solar-thermal power plant investment projects. Energy, 66, 222-238. doi:10.1016/j.energy.2013.12.016Arif, F., Bayraktar, M. E., & Chowdhury, A. G. (2016). Decision Support Framework for Infrastructure Maintenance Investment Decision Making. Journal of Management in Engineering, 32(1), 04015030. doi:10.1061/(asce)me.1943-5479.0000372Arunraj, N. S., & Maiti, J. (2010). Risk-based maintenance policy selection using AHP and goal programming. Safety Science, 48(2), 238-247. doi:10.1016/j.ssci.2009.09.005Asensio, J., & Matas, A. (2008). Commuters’ valuation of travel time variability. Transportation Research Part E: Logistics and Transportation Review, 44(6), 1074-1085. doi:10.1016/j.tre.2007.12.002Bana e Costa, C. A., & Oliveira, R. C. (2002). Assigning priorities for maintenance, repair and refurbishment in managing a municipal housing stock. European Journal of Operational Research, 138(2), 380-391. doi:10.1016/s0377-2217(01)00253-3Bana e Costa, C. A., & Vansnick, J.-C. (2008). A critical analysis of the eigenvalue method used to derive priorities in AHP. European Journal of Operational Research, 187(3), 1422-1428. doi:10.1016/j.ejor.2006.09.022Belton, V., & Stewart, T. J. (2002). Multiple Criteria Decision Analysis. doi:10.1007/978-1-4615-1495-4Bouch, C. J., Roberts, C., & Amoore, J. (2010). Development of a common set of European high-level track maintenance cost categories. Proceedings of the Institution of Mechanical Engineers, Part F: Journal of Rail and Rapid Transit, 224(4), 327-335. doi:10.1243/09544097jrrt316Bouyssou, D., Marchant, T., Pirlot, M., Perny, P., Tsoukiàs, A., & Vincke, P. (2000). Evaluation and Decision Models. International Series in Operations Research & Management Science. doi:10.1007/978-1-4615-1593-7Evaluation and Decision Models with Multiple Criteria. (2006). International Series in Operations Research & Management Science. doi:10.1007/0-387-31099-1Brans, J. P., Vincke, P., & Mareschal, B. (1986). How to select and how to rank projects: The Promethee method. European Journal of Operational Research, 24(2), 228-238. doi:10.1016/0377-2217(86)90044-5Cantarelli, C. C., van Wee, B., Molin, E. J. E., & Flyvbjerg, B. (2012). Different cost performance: different determinants? Transport Policy, 22, 88-95. doi:10.1016/j.tranpol.2012.04.002Cheng, C.-H. (1997). Evaluating naval tactical missile systems by fuzzy AHP based on the grade value of membership function. European Journal of Operational Research, 96(2), 343-350. doi:10.1016/s0377-2217(96)00026-4Cheng, E. W. L., & Li, H. (2005). Analytic Network Process Applied to Project Selection. Journal of Construction Engineering and Management, 131(4), 459-466. doi:10.1061/(asce)0733-9364(2005)131:4(459)Damart, S., & Roy, B. (2009). The uses of cost–benefit analysis in public transportation decision-making in France. Transport Policy, 16(4), 200-212. doi:10.1016/j.tranpol.2009.06.002Durango-Cohen, P. L., & Madanat, S. M. (2008). Optimization of inspection and maintenance decisions for infrastructure facilities under performance model uncertainty: A quasi-Bayes approach. Transportation Research Part A: Policy and Practice, 42(8), 1074-1085. doi:10.1016/j.tra.2008.03.004Durango-Cohen, P. L., & Sarutipand, P. (2009). Maintenance optimization for transportation systems with demand responsiveness. Transportation Research Part C: Emerging Technologies, 17(4), 337-348. doi:10.1016/j.trc.2009.01.001Dyer, J. S. (1990). Remarks on the Analytic Hierarchy Process. Management Science, 36(3), 249-258. doi:10.1287/mnsc.36.3.249Famurewa, S. M., Asplund, M., Rantatalo, M., Parida, A., & Kumar, U. (2014). Maintenance analysis for continuous improvement of railway infrastructure performance. Structure and Infrastructure Engineering, 11(7), 957-969. doi:10.1080/15732479.2014.921929Famurewa, S. M., Stenström, C., Asplund, M., Galar, D., & Kumar, U. (2014). Composite indicator for railway infrastructure management. Journal of Modern Transportation, 22(4), 214-224. doi:10.1007/s40534-014-0051-1Figueira, J., Greco, S., & Ehrogott, M. (2005). Multiple Criteria Decision Analysis: State of the Art Surveys. International Series in Operations Research & Management Science. doi:10.1007/b100605FitzRoy, F., & Smith, I. (1995). The demand for rail transport in European countries. Transport Policy, 2(3), 153-158. doi:10.1016/0967-070x(95)96745-7Furuya, A., & Madanat, S. (2013). Accounting for Network Effects in Railway Asset Management. Journal of Transportation Engineering, 139(1), 92-100. doi:10.1061/(asce)te.1943-5436.0000477Gao, L., Guo, R., & Zhang, Z. (2013). An augmented Lagrangian decomposition approach for infrastructure maintenance and rehabilitation decisions under budget uncertainty. Structure and Infrastructure Engineering, 9(5), 448-457. doi:10.1080/15732479.2011.557388Gerçek, H., Karpak, B., & Kılınçaslan, T. (2004). A multiple criteria approach for the evaluation of the rail transit networks in Istanbul. Transportation, 31(2), 203-228. doi:10.1023/b:port.0000016572.41816.d2Goverde, R. M. P. (2010). A delay propagation algorithm for large-scale railway traffic networks. Transportation Research Part C: Emerging Technologies, 18(3), 269-287. doi:10.1016/j.trc.2010.01.002Grimes, G. A., & Barkan, C. P. L. (2006). Cost-Effectiveness of Railway Infrastructure Renewal Maintenance. Journal of Transportation Engineering, 132(8), 601-608. doi:10.1061/(asce)0733-947x(2006)132:8(601)Harker, P. T., & Vargas, L. G. (1990). Reply to «Remarks on the Analytic Hierarchy Process» by J. S. Dyer. Management Science, 36(3), 269-273. doi:10.1287/mnsc.36.3.269Huisman, T., & Boucherie, R. J. (2001). Running times on railway sections with heterogeneous train traffic. Transportation Research Part B: Methodological, 35(3), 271-292. doi:10.1016/s0191-2615(99)00051-xHwang, C.-L., & Yoon, K. (1981). Multiple Attribute Decision Making. Lecture Notes in Economics and Mathematical Systems. doi:10.1007/978-3-642-48318-9Ieda, H., Kanayama, Y., Ota, M., Yamazaki, T., & Okamura, T. (2001). How can the quality of rail services in Tokyo be further improved? Transport Policy, 8(2), 97-106. doi:10.1016/s0967-070x(01)00002-6Ishizaka, A., & Labib, A. (2011). Review of the main developments in the analytic hierarchy process. Expert Systems with Applications. doi:10.1016/j.eswa.2011.04.143Ishizaka, A., & Nemery, P. (2013). Multi-Criteria Decision Analysis. doi:10.1002/9781118644898Ivanović, I., Grujičić, D., Macura, D., Jović, J., & Bojović, N. (2013). One approach for road transport project selection. Transport Policy, 25, 22-29. doi:10.1016/j.tranpol.2012.10.001Johansson, P., & Nilsson, J.-E. (2004). An economic analysis of track maintenance costs. Transport Policy, 11(3), 277-286. doi:10.1016/j.tranpol.2003.12.002Kabir, G., Sadiq, R., & Tesfamariam, S. (2013). A review of multi-criteria decision-making methods for infrastructure management. Structure and Infrastructure Engineering, 10(9), 1176-1210. doi:10.1080/15732479.2013.795978Karanik, M., Wanderer, L., Gomez-Ruiz, J. A., & Pelaez, J. I. (2016). Reconstruction methods for AHP pairwise matrices: How reliable are they? Applied Mathematics and Computation, 279, 103-124. doi:10.1016/j.amc.2016.01.008Karydas, D. M., & Gifun, J. F. (2006). A method for the efficient prioritization of infrastructure renewal projects. Reliability Engineering & System Safety, 91(1), 84-99. doi:10.1016/j.ress.2004.11.016Kułakowski, K. (2015). Notes on order preservation and consistency in AHP. European Journal of Operational Research, 245(1), 333-337. doi:10.1016/j.ejor.2015.03.010Kumar, G., & Maiti, J. (2012). Modeling risk based maintenance using fuzzy analytic network process. Expert Systems with Applications, 39(11), 9946-9954. doi:10.1016/j.eswa.2012.01.004Lee, A. H. I., Chen, H. H., & Kang, H.-Y. (2009). Operations management of new project development: innovation, efficient, effective aspects. Journal of the Operational Research Society, 60(6), 797-809. doi:10.1057/palgrave.jors.2602605LEE, A. H. I., KANG, H.-Y., & CHANG, C.-C. (2011). AN INTEGRATED INTERPRETIVE STRUCTURAL MODELING–FUZZY ANALYTIC NETWORK PROCESS–BENEFITS, OPPORTUNITIES, COSTS AND RISKS MODEL FOR SELECTING TECHNOLOGIES. International Journal of Information Technology & Decision Making, 10(05), 843-871. doi:10.1142/s0219622011004592Liang, C., & Li, Q. (2008). Enterprise information system project selection with regard to BOCR. International Journal of Project Management, 26(8), 810-820. doi:10.1016/j.ijproman.2007.11.001Macharis, C., & Bernardini, A. (2015). Reviewing the use of Multi-Criteria Decision Analysis for the evaluation of transport projects: Time for a multi-actor approach. Transport Policy, 37, 177-186. doi:10.1016/j.tranpol.2014.11.002Mardani, A., Jusoh, A., & Zavadskas, E. K. (2015). Fuzzy multiple criteria decision-making techniques and applications – Two decades review from 1994 to 2014. Expert Systems with Applications, 42(8), 4126-4148. doi:10.1016/j.eswa.2015.01.003Medury, A., & Madanat, S. (2013). Incorporating network considerations into pavement management systems: A case for approximate dynamic programming. Transportation Research Part C: Emerging Technologies, 33, 134-150. doi:10.1016/j.trc.2013.03.003Millet, I., & Saaty, T. L. (2000). On the relativity of relative measures – accommodating both rank preservation and rank reversals in the AHP. European Journal of Operational Research, 121(1), 205-212. doi:10.1016/s0377-2217(99)00040-5Nyström, B., & Söderholm, P. (2010). Selection of maintenance actions using the analytic hierarchy process (AHP): decision-making in railway infrastructure. Structure and Infrastructure Engineering, 6(4), 467-479. doi:10.1080/15732470801990209Olsson, N. O. E., Økland, A., & Halvorsen, S. B. (2012). Consequences of differences in cost-benefit methodology in railway infrastructure appraisal—A comparison between selected countries. Transport Policy, 22, 29-35. doi:10.1016/j.tranpol.2012.03.005Özgür, Ö. (2011). Performance analysis of rail transit investments in Turkey: İstanbul, Ankara, İzmir and Bursa. Transport Policy, 18(1), 147-155. doi:10.1016/j.tranpol.2010.07.004Özkır, V., & Demirel, T. (2012). A fuzzy assessment framework to select among transportation investment projects in Turkey. Expert Systems with Applications, 39(1), 74-80. doi:10.1016/j.eswa.2011.06.051Pardo-Bosch, F., & Aguado, A. (2014). Investment priorities for the management of hydraulic structures. Structure and Infrastructure Engineering, 11(10), 1338-1351. doi:10.1080/15732479.2014.964267Phillips, L. D., & Bana e Costa, C. A. (2007). Transparent prioritisation, budgeting and resource allocation with multi-criteria decision analysis and decision conferencing. Annals of Operations Research, 154(1), 51-68. doi:10.1007/s10479-007-0183-3Roy, B. (1991). The outranking approach and the foundations of electre methods. Theory and Decision, 31(1), 49-73. doi:10.1007/bf00134132Saaty, T. L. (1990). How to make a decision: The analytic hierarchy process. European Journal of Operational Research, 48(1), 9-26. doi:10.1016/0377-2217(90)90057-iSaaty, T. L. (2006). Rank from comparisons and from ratings in the analytic hierarchy/network processes. European Journal of Operational Research, 168(2), 557-570. doi:10.1016/j.ejor.2004.04.032Saaty, T. L. (2008). Relative measurement and its generalization in decision making why pairwise comparisons are central in mathematics for the measurement of intangible factors the analytic hierarchy/network process. Revista de la Real Academia de Ciencias Exactas, Fisicas y Naturales. Serie A. Matematicas, 102(2), 251-318. doi:10.1007/bf03191825SAATY, T. L., & SAGIR, M. (2009). EXTENDING THE MEASUREMENT OF TANGIBLES TO INTANGIBLES. International Journal of Information Technology & Decision Making, 08(01), 7-27. doi:10.1142/s0219622009003247Saaty, T. L., & Shih, H.-S. (2009). Structures in decision making: On the subjective geometry of hierarchies and networks. European Journal of Operational Research, 199(3), 867-872. doi:10.1016/j.ejor.2009.01.064Saaty, T. L., & Tran, L. T. (2007). On the invalidity of fuzzifying numerical judgments in the Analytic Hierarchy Process. Mathematical and Computer Modelling, 46(7-8), 962-975. doi:10.1016/j.mcm.2007.03.022Saaty, T. L., & Vargas, L. G. (1993). Experiments on rank preservation and reversal in relative measurement. Mathematical and Computer Modelling, 17(4-5), 13-18. doi:10.1016/0895-7177(93)90171-tSalem, O. M., Miller, R. A., Deshpande, A. S., & Arurkar, T. P. (2013). Multi-criteria decision-making system for selecting an effective plan for bridge rehabilitation. Structure and Infrastructure Engineering, 9(8), 806-816. doi:10.1080/15732479.2011.615843Seyedshohadaie, S. R., Damnjanovic, I., & Butenko, S. (2010). Risk-based maintenance and rehabilitation decisions for transportation infrastructure networks. Transportation Research Part A: Policy and Practice, 44(4), 236-248. doi:10.1016/j.tra.2010.01.005Shattuck, M., & Wagner, C. (2016). Peter Fishburn’s analysis of ambiguity. Theory and Decision, 81(2), 153-165. doi:10.1007/s11238-016-9534-3Sohn, K. (2008). A systematic decision criterion for the elimination of useless overpasses. Transportation Research Part A: Policy and Practice, 42(8), 1043-1055. doi:10.1016/j.tra.2008.03.003Thomas, L. J., Rhind, D. J. A., & Robinson, K. J. (2005). Rail passenger perceptions of risk and safety and priorities for improvement. Cognition, Technology & Work, 8(1), 67-75. doi:10.1007/s10111-005-0021-9Tsamboulas, D. A. (2007). A tool for prioritizing multinational transport infrastructure investments. Transport Policy, 14(1), 11-26. doi:10.1016/j.tranpol.2006.06.001Vaidya, O. S., & Kumar, S. (2006). Analytic hierarchy process: An overview of applications. European Journal of Operational Research, 169(1), 1-29. doi:10.1016/j.ejor.2004.04.028Wallenius, J., Dyer, J. S., Fishburn, P. C., Steuer, R. E., Zionts, S., & Deb, K. (2008). Multiple Criteria Decision Making, Multiattribute Utility Theory: Recent Accomplishments and What Lies Ahead. Management Science, 54(7), 1336-1349. doi:10.1287/mnsc.1070.083

Development of titanium dioxide nanoparticles/nanosolution for photocatalytic activity

Biological and chemical contaminants by man-made activities have been serious global issue. Exposure of these contaminants beyond the limits may result in serious environmental and health problem. Therefore, it is important to develop an effective solution that can be easily utilized by mankind. One of the effective ways to overcome this problem is by using titanium dioxide (TiO2). TiO2 is a well-known photocatalyst that widely used for environmental clean-up due to its ability to decompose organic pollutant and kill bacteria. Although it is proven TiO2 has an advantage to solve this concern, its usefulness unfortunately is limited only under UV light irradiation. Therefore, the aim of this work was to investigate the potential of TiO2 that can be activated under visible light by the incorporation of metal ions (Fe, Ag, Zr and Ag-Zr). In this study, sol-gel method was employed for the synthesis of metal ions incorporated TiO2. XRD analysis revealed that all samples content biphasic anatase-brookite TiO2 of size 3 nm to 5 nm. It was found that the incorporation of these metal ions did not change the morphology of TiO2 but the crystallinity and optical properties were affected. The crystallinity of anatase in the biphasic TiO2 was found to be decreased and favored brookite formation. PL analysis showed metal ions incorporation suppressed the recombination of electron-hole pairs while the band gap energy of TiO2 (3.2 eV) was decreased by the incorporation of Fe (2.46 eV) and Ag (2.86 eV). Among this incorporation, Ag-Zr incorporated TiO2 showed highest performance for methyl orange degradation (93%) under fluorescent xxv light irradiation for 10 h. This follows by Zr-TiO2 (82%), Fe-TiO2 (75%) and Ag�TiO2 (43%). Meanwhile, the highest antibacterial performance was exhibited by Ag�TiO2. TEM images showed that E.coli bacterium was killed within 12 h after treated with Ag-TiO2. The results obtained from the fieldwork study established that Ag-Zr incorporation have excellent performances for VOC removal and antibacterial test. The VOC content after treated with Ag-Zr-TiO2 fulfilled the Industry Code of Practice on Indoor Air Quality 2010 which is lower than 3 ppm. In addition, the percentage of microbes also found to be decrease around 45 % within 5 days of monitoring

Strategy Selection for Product Service Systems Using Case-based Reasoning

A product service system integrates products and services in order to lower environmental impact. It can achieve good eco-efficiency and has received increase in the last decade. This study focuses on strategy selection for product service system design. Case-based reasoning is utilized to provide suggestions for finding an appropriate strategy. To build a case database, successful PSS cases from the literature and websites were collected and formulated. Twelve indices under three categories were analyzed and selected to describe cases. A lot of successful PSS cases and their information were collected. Forty seven cases were used in this study because of the completeness of information. The analytic hierarchic process is used to find the relative weights of the factors that relate to the selection of customers. These weights are used in calculating the similarity in the case-based reasoning process. The successful strategy of the most similar case is extracted and recommended for PSS strategy determination. More than 90% of tested cases obtained an appropriate strategy from the most similar case. Finally, two new products are introduced to find the best strategy for product service system design and development using the proposed case-based reasoning system

Application of context knowledge in supporting conceptual design decision making

Conceptual design is the most important phase of the product life cycle as the decisions taken at conceptual design stage affect the downstream phases (manufacture, assembly, use, maintenance, and disposal) in terms of cost, quality and function performed by the product. This research takes a holistic view by incorporating the knowledge related to the whole context (from the viewpoint of product, user, product's life cycle and environment in which the product operates) of a design problem for the consideration of the designer to make an informed decision making at the conceptual design stage. The design context knowledge comprising knowledge from these different viewpoints is formalised and a new model and corresponding computational framework is proposed to support conceptual design decision making using this formalised context knowledge. Using a case study, this paper shows the proof of the concept by selecting one concept among different design alternatives using design context knowledge thereby proactively supporting conceptual design decision making for an informed and effective decision making

Multi crteria decision making and its applications : a literature review

This paper presents current techniques used in Multi Criteria Decision Making (MCDM) and their applications. Two basic approaches for MCDM, namely Artificial Intelligence MCDM (AIMCDM) and Classical MCDM (CMCDM) are discussed and investigated. Recent articles from international journals related to MCDM are collected and analyzed to find which approach is more common than the other in MCDM. Also, which area these techniques are applied to. Those articles are appearing in journals for the year 2008 only. This paper provides evidence that currently, both AIMCDM and CMCDM are equally common in MCDM

Multi-Criteria Analysis in Compound Decision Processes. The AHP and the Architectural Competition for the Chamber of Deputies in Rome (Italy)

In 1967, a national architectural competition was released for a preliminary project proposal, aimed at the realization of the new building for the Chamber of Deputies in Rome. The outcomes of that competition were unusual: eighteen projects were declared joint winners, and no winner was consequently selected. With reference to that event, this research aims to examine the usefulness of the evaluation tools that are currently employed and the positive effects that one of these techniques would have had, as support for the identification of the “winner” project, are highlighted. Therefore, an hypothetical examination/adjustment of the decision process of that competition through the Analytic Hierarchy Process (AHP) is developed, analyzing the outputs obtained by the implementations of this technique on the final decision. In addition to confirming the usefulness of the evaluation tools for compound and conflicting decision processes, the results of this experiment led to a further understanding of the socio-cultural dynamics related to the original outcomes of the competition analyzed. View Full-Tex

Current practice and challenges towards handling uncertainty for effective outcomes in maintenance

The combination of viable heuristic attributes with statistical measurements presents significant challenges in industrial maintenance for complex assets under through-life service contracts. Techniques to obtain and process heuristic attributes raise numerous uncertainties which often go undefined and unmitigated. A holistic view of these uncertainties may improve decision-making capabilities and reduce maintenance costs and turnaround time. It is therefore necessary to identify and rank factors that influence uncertainties originating from challenges in the above context. This, along with an identification of who contributes to such challenges and current practice to handle them, sets the focus for this study. The influence of 32 categorised factors on uncertainty is assessed through a questionnaire completed by nine experienced maintenance managers from a leading defence company. The pedigree approach is applied to score validity of respondents’ answers according to their experience and job role to normalise scores. Results are discussed in interviews with respondents along with current practice in and ways to improve uncertainty assessment. Scores are weighted through the Analytical Hierarchy Process (AHP) in order to identify the most influential factors on uncertainty in maintenance. The analysis revealed that these include: intellectual property rights (IPR), maintainer performance, quality of information, resistance to change, stakeholder communication and technology integration. These are verified with 40 practitioners from various industrial backgrounds. From the interviews, it is deemed that a holistic view of heuristic and statistical attributes ultimately allows for more accomplished decision-making but requires trade-offs between quality and cost over the asset’s life cycle

Public initiatives of settlement transformation. A theoretical-methodological approach to selecting tools of multi-criteria decision analysis

In Europe, the operating context in which initiatives of settlement transformation are currently initiated is characterized by a complex, elaborate combination of technical, regulatory and governance-related factors. A similar set of considerations makes it necessary to address the complex decision-making problems to be resolved through multidisciplinary, comparative approaches designed to rationalize the process and treat the elements to be considered in systematic fashion with respect to the range of alternatives available as solutions. Within a context defined in this manner, decision-making processes must often be used to obtain multidisciplinary and multidimensional analyses to support the choices made by the decision-makers. Such analyses are carried out using multi-criteria tools designed to arrive at syntheses of the numerous forms of input data needed to describe decision-making problems of similar complexity, so that one or more outcomes of the synthesis make possible informed, well thought-out, strategic decisions. The technical literature on the topic proposes numerous tools of multi-criteria analysis for application in different decision-making contexts. Still, no specific contributions have been drawn up to date on the approach to take in selecting the tool best suited to providing adequate responses to the queries of evaluation that arise most frequently in the various fields of application, and especially in the settlement sector. The objective of this paper is to propose, by formulating a taxonomy of the endogenous and exogenous variables of tools of multi-criteria analysis, a methodology capable of selecting the tool best suited to the queries of evaluation which arise regarding the chief categories of decision-making problems, and particularly in the settlement sector