Search Results (10)

Considering the complexity of laser cutting technology, and difficulties and limitations when applying traditional multi-criteria decision-making (MCDM) methods, this study proposes a fuzzy MCDM methodology for the analysis of the fibre laser cutting process, assessment of alternative cutting conditions and selection of favourable cutting conditions. The experiment in fibre laser cutting of mild steel was based on a Box–Behnken design by considering three input parameters (focus position, cutting speed and oxygen pressure) and four relevant criteria for the assessment of cutting conditions (kerf width on a straight and curved cut, surface roughness and surface productivity). The proposed fuzzy MCDM methodology makes use of expert knowledge and experimental data for criteria evaluation and decision matrix development, respectively, while three fuzzy MCDM methods (fuzzy TOPSIS, fuzzy WASPAS and fuzzy ARAS) were used to determine the complete ranking of alternatives. Kendall’s tau-b and Spearman’s rho correlation tests were applied to compare the obtained ranking lists, while the stability of the ranking was assessed with the application of the Monte Carlo simulation. Finally, to approximate the fuzzy decision-making rule, a second-order model was developed to reveal the significance of process parameters and identify favourable laser cutting conditions. Full article

The capacity of transport infrastructure is one of the very important tasks in transport engineering, which depends mostly on the geometric characteristics of road and headway analysis. In this paper, we have considered 14 road sections and determined their efficiency based on headway analysis. We have developed a novel interval fuzzy-rough-number decision-making model consisting of DEA (data envelopment analysis), IFRN SWARA (interval-valued fuzzy-rough-number stepwise weight-assessment-ratio analysis), and IFRN WASPAS (interval-valued fuzzy-rough-number weighted-aggregate sum–product assessment) methods. The main contribution of this study is a new extension of WASPAS method with interval fuzzy rough numbers. Firstly, the DEA model was applied to determine the efficiency of 14 road sections according to seven input–output parameters. Seven out of the fourteen alternatives showed full efficiency and were implemented further in the model. After that, the IFRN SWARA method was used for the calculation of the final weights, while IFRN WASPAS was applied for ranking seven of the road sections. The results show that two sections are very similar and have almost equal efficiency, while the other results are very stable. According to the results obtained, the best-ranked is a measuring segment of the Ivanjska–Šargovac section, with a road gradient = −5.5%, which has low deviating values of headways according to the measurement classes from PC-PC to AT-PC, which shows balanced and continuous traffic flow. Finally, verification tests such as changing the criteria weights, comparative analysis, changing the λ parameter, and reverse rank analysis have been performed. Full article

Many problems such as delamination, cracking, fiber tearing, ovality, and surface roughness are encountered in the drilling of glass-fiber-reinforced composite (GFRP) materials. In this study, the percentage of multi-walled carbon nano tube (MWCNT), cutting tool type, feed rate, and cutting speed were selected as control factors during the drilling of MWCNT-reinforced GFRP nanocomposites. The quality characteristics of the drilling process were determined as surface roughness, delamination, torque, and thrust force. The experiments were carried out in accordance with the Taguchi L27 orthogonal array. The lowest values obtained because of the experiments were Ra = 4.95 µm, Dm = 1.099, T = 14.78 N, and F = 44.24 N, respectively. However, since each of these outputs were obtained from different experimental trials, different multi-criteria decision-making (MCDM) methods were used to optimize all outputs at the same time. First, the criteria were weighted using the fuzzy AHP method, and then the outputs were optimized using multi-criteria decision-making methods (i.e., GRA, WASPAS and VIKOR). Very close optimal ranking was obtained in all three methods. The best results were obtained for Ra = 4.86 µm, Dm = 1.13, T = 55.57 N, and F = 48.00 N. In the next step, the performance values obtained from each MCDM method were re-optimized using the Taguchi S/N ratio method. By comparing between these models, a single optimal condition for drilling is proposed. Accordingly, A₂B₃C₁D₁ (Ra = 4.86 µm, Dm = 1.10, T = 17.47 N and F = 48.33 N) for FAHP-GRA and FAHP-WASPAS and A₂B₃C₂D₂ (Ra = 5.02 µm, Dm = 1.09, T = 37.19 N and F = 45.01 N) for FAHP-VIKOR were determined as the best performing experiments. Finally, validation tests were conducted to compare the performance of the experiments. As a result, the FAHP-GRA and FAHP-WASPAS optimization with Taguchi S/N gave an unweighted improvement of 82.9% and a weighted improvement of 10.04% compared to the results of the experiment with MCDM. Compared to the results of the experiments with MCDM, S/N FAHP-VIKOR provided an unweighted improvement of 52.75% and a weighted improvement of 8.19%. According to the results obtained, for this study, FAHP-GRA and FAHP-WASPAS are more effective optimization methods than FAHP-VIKOR. Full article

Hard turning is an emerging machining technology that evolved as a substitute for grinding in the production of precision parts from hardened steel. It offers advantages such as reduced cycle times, lower costs, and environmental benefits over grinding. Hard turning is stated to be difficult because of the high hardness of the workpiece material, which causes higher tool wear, cutting temperature, surface roughness, and cutting force. In this work, a dual-nozzle minimum quantity lubrication (MQL) system’s performance assessment of ZnO nano-cutting fluid in the hard turning of AISI 52100 bearing steel is examined. The objective is to evaluate the ZnO nano-cutting fluid’s impacts on flank wear, surface roughness, cutting temperature, cutting power consumption, and cutting noise. The tool flank wear was traced to be very low (0.027 mm to 0.095 mm) as per the hard turning concern. Additionally, the data acquired are statistically analyzed using main effects plots, interaction plots, and analysis of variance (ANOVA). Moreover, a novel Weighted Aggregated Sum Product Assessment (WASPAS) optimization tool was implemented to select the optimal combination of input parameters. The following optimal input variables were found: depth of cut = 0.3 mm, feed = 0.05 mm/rev, cutting speed = 210 m/min, and flow rate = 50 mL/hr. Full article

A balance (symmetry) between socio-cultural and socio-economic benefits as a part of the economic, social, and cultural development policy of each city and country should be assured when converting built heritage. To anticipate building conversion priorities and opportunities, modern technologies can be employed. However, currently the activity of reconstruction of heritage buildings is part of the construction domain wherein modern digital technologies have been the least ever applied. Therefore, photogrammetry and the 3D modeling of existing heritage buildings was suggested. A case study of Sapieha Palace, built in the Baroque style in 1689–1691 in Vilnius, Lithuania was explored in this research. The applied technologies and software (Agisoft Photoscan, Autodesk ReCap and Autodesk Revit) allowed for the creation of a high quality and accurate model involving both the textured exterior of the building and the interior layout. In addition, the valuable features of a building were identified and marked in a three-dimensional digital model. Based on the model, the authors formulated possible conversion alternatives of the building and identified the associated decision-making criteria, as well as determined their relative significance by an expert survey method. The authors suggested the application of the multiple criteria decision making (MCDM) method under uncertainty, namely the rough weighted aggregated sum product assessment (WASPAS), for ranking alternatives according to multiple criteria. Therefore, the suggested integration of modern digital technologies and decision-making models helps to assure the rational conversion decision of built cultural heritage based on high accuracy data as well as contributing to the sustainable development of engineering processes. Full article

Sustainable development is one of the most important preconditions for preserving resources and balanced functioning of a complete supply chain in different areas. Taking into account the complexity of sustainable development and a supply chain, different decisions have to be made day-to-day, requiring the consideration of different parameters. One of the most important decisions in a sustainable supply chain is the selection of a sustainable supplier and, often the applied methodology is multi-criteria decision-making (MCDM). In this paper, a new hybrid MCDM model for evaluating and selecting suppliers in a sustainable supply chain for a construction company has been developed. The evaluation and selection of suppliers have been carried out on the basis of 21 criteria that belong to all aspects of sustainability. The determination of the weight values of criteria has been performed applying the full consistency method (FUCOM), while a new rough complex proportional assessment (COPRAS) method has been developed to evaluate the alternatives. The rough Dombi aggregator has been used for averaging in group decision-making while evaluating the significance of criteria and assessing the alternatives. The obtained results have been checked and confirmed using a sensitivity analysis that implies a four-phase procedure. In the first phase, the change of criteria weight was performed, while, in the second phase, rough additive ratio assessment (ARAS), rough weighted aggregated sum product assessment (WASPAS), rough simple additive weighting (SAW), and rough multi-attributive border approximation area comparison (MABAC) have been applied. The third phase involves changing the parameter ρ in the modeling of rough Dombi aggregator, and the fourth phase includes the calculation of Spearman’s correlation coefficient (SCC) that shows a high correlation of ranks. Full article

The success of any business depends fundamentally on the possibility of balancing (symmetry) needs and their satisfaction, that is, the ability to properly define a set of success indicators. It is necessary to continuously monitor and measure the indicators that have the greatest impact on the achievement of previously set goals. Regarding transportation companies, the rationalization of transportation activities and processes plays an important role in ensuring business efficiency. Therefore, in this paper, a model for evaluating performance indicators has been developed and implemented in three different countries: Bosnia and Herzegovina, Libya and Serbia. The model consists of five phases, of which the greatest contribution is the development of a novel rough additive ratio assessment (ARAS) approach for evaluating measured performance indicators in transportation companies. The evaluation was carried out in the territories of the aforementioned countries in a total of nine companies that were evaluated on the basis of 20 performance indicators. The results obtained were verified throughout a three-phase procedure of a sensitivity analysis. The significance of the performance indicators was simulated throughout the formation of 10 scenarios in the sensitivity analysis. In addition, the following approaches were applied: rough WASPAS (weighted aggregated sum product assessment), rough SAW (simple additive weighting), rough MABAC (multi-attributive border approximation area comparison) and rough EDAS (evaluation based on distance from average solution), which showed high correlation of ranks by applying Spearman's correlation coefficient (SCC). Full article

An adequately functionally located traffic infrastructure is an important factor in the mobility of people because it affects the quality of traffic, safety and efficiency of carrying out transportation activities. Locating a roundabout on an urban network is an imperative for road engineering to address traffic problems such as reduction of traffic congestion, enhancement of security and sustainability, etc. Therefore, this paper evaluates potential locations for roundabout construction using Rough BWM (Best Worst Method) and Rough WASPAS (Weighted Aggregated Sum Product Assessment) models. Determination of relative criterion weights on the basis of which the potential locations were evaluated was carried out using the Rough BWM method. In this paper, in order to enable the most precise consensus for group decision-making, a Rough Hamy aggregator has been developed. The main advantage of the Hamy mean (HM) operator is that it can capture the interrelationships among multi-input arguments and can provide DMs more options. Until now, there is no research based on HM operator for aggregating imprecise and uncertain information. The obtained indicators are described through eight alternatives. The results show that the fifth and sixth alternatives are the locations that should have a priority in the construction of roundabouts from the perspective of sustainable development, which is confirmed throughout changes of parameter k and with comparing to other methods in the sensitivity analysis. Full article

For companies active in various sectors, the implementation of transport services and other logistics activities has become one of the key factors of efficiency in the total supply chain. Logistics outsourcing is becoming more and more important, and there is an increasing number of third party logistics providers. In this paper, logistics providers were evaluated using the Rough SWARA (Step-Wise Weight Assessment Ratio Analysis) and Rough WASPAS (Weighted Aggregated Sum Product Assessment) models. The significance of the eight criteria on the basis of which evaluation was carried out was determined using the Rough SWARA method. In order to allow for a more precise consensus in group decision-making, the Rough Dombi aggregator was developed in order to determine the initial rough matrix of multi-criteria decision-making. A total of 10 logistics providers dealing with the transport of dangerous goods for chemical industry companies were evaluated using the Rough WASPAS approach. The obtained results demonstrate that the first logistics provider is also the best one, a conclusion confirmed by a sensitivity analysis comprised of three parts. In the first part, parameter ρ was altered through 10 scenarios in which only alternatives four and five change their ranks. In the second part of the sensitivity analysis, a calculation was performed using the following approaches: Rough SAW (Simple Additive Weighting), Rough EDAS (Evaluation Based on Distance from Average Solution), Rough MABAC (MultiAttributive Border Approximation Area Comparison), and Rough TOPSIS (Technique for Order of Preference by Similarity to Ideal Solution). They showed a high correlation of ranks determined by applying Spearman’s correlation coefficient in the third part of the sensitivity analysis. Full article

The decision-making process requires the prior definition and fulfillment of certain factors, especially when it comes to complex areas such as supply chain management. One of the most important items in the initial phase of the supply chain, which strongly influences its further flow, is to decide on the most favorable supplier. In this paper a selection of suppliers in a company producing polyvinyl chloride (PVC) carpentry was made based on the new approach developed in the field of multi-criteria decision making (MCDM). The relative values of the weight coefficients of the criteria are calculated using the rough analytical hierarchical process (AHP) method. The evaluation and ranking of suppliers is carried out using the new rough weighted aggregated sum product assessment (WASPAS) method. In order to determine the stability of the model and the ability to apply the developed rough WASPAS approach, the paper analyzes its sensitivity, which involves changing the value of the coefficient λ in the first part. The second part of the sensitivity analysis relates to the application of different multi-criteria decision-making methods in combination with rough numbers that have been developed in the very recent past. The model presented in the paper is solved by using the following methods: rough Simple Additive Weighting (SAW), rough Evaluation based on Distancefrom Average Solution (EDAS), rough MultiAttributive Border Approximation area Comparison (MABAC), rough Višekriterijumsko kompromisno rangiranje (VIKOR), rough MultiAttributiveIdeal-Real Comparative Analysis (MAIRCA) and rough Multi-objective optimization by ratio analysis plus the full multiplicative form (MULTIMOORA). In addition, in the third part of the sensitivity analysis, the Spearman correlation coefficient (SCC) of the ranks obtained was calculated which confirms the applicability of all the proposed approaches. The proposed rough model allows the evaluation of alternatives despite the imprecision and lack of quantitative information in the information-management process. Full article