Preference Selection Index Research Articles

Decision support system analysis for selecting a baby cream product with Preference Selection Index (PSI) Baby Sensitive Skin Under 3 Year

The aim of this study was to examine the technology for decision support in the selection of baby cream products for sensitive skin in children under three years of age. Babies’ skin sensitivity should be addressed in order to maintain the baby’s skin health, but parents should be more careful with product selection in the number of products to treat sensitive skin in babies on the market. Data sources obtained through random observations, interviews and questionnaires (parents who have babies). The solution provided is the Preference Selection Index (PSI) method, which is part of the support system for decision making. Five criteria are used as parameters when selecting sensitive skin product for children, namely: price (K1), type of skin (K2), feeling of brand (K3), interests (K4) and packaging (K5). While the alternatives used based on the interview results are cussons (alt1), johnson’s (alt2), zwitsal (alt3), pigeon (alt4), and sleek (alt5). The results of the Preference Selection Index could be used by analysis of the first recommendation of product alt1 (cussons), a value of 0.978584. The second recommendation of product alt3 (zwitsal) is a value of 0.976655. Research results are hoped to provide a wider awareness for babies when selecting sensitive skin products for three years old.

Synergic effect of metallic fillers as heat dissipaters in the tribological performance of a nonasbestos disk brake pad

Brake friction linings are made of materials with a highly complex formulation that helps in improving the braking performance. The selection of friction materials with good physical, mechanical, and thermal properties is vital, which will decide the braking performance. Apart from giving good physio-mechanical properties, metallic fillers act as heat dissipaters. The objective of this work is to study the synergetic effect of prominent heat dissipaters, namely copper fibers, brass fibers, and zinc powders. Three simplified formulations were developed with 10, 14, and 18 wt.% of these heat dissipaters and named DB1, DB2, and DB3, respectively. It was observed that the addition of heat dissipaters increased the thermal properties. Tribological properties are tested based on SAE J661 standards. It was observed that DB2 had a consistent and higher coefficient of friction of 0.503 with a higher wear rate (7.6%) while DB3 had adequate μ and lower wear rate. The same batches of brake pads were tested in an inertia brake dynamometer following JASO C406 and a wear test was carried out. It was observed that % fade and % recovery were better for DB2 in both cycles. The wear rate in terms of thickness was lesser for DB2 followed by DB1 and DB3. The wear mechanism was analyzed using a scanning electron microscope. The preference selection index method of optimization was used to evaluate the overall performance parameters of the brake friction composites. Heat dissipaters with 14 wt.% have proved to be the better performers, followed by 10 and 18 wt.%.

Evaluating the sustainable mining contractor selection problems: An imprecise last aggregation preference selection index method

The increasing complexity surrounding decision-making situations has made it inevitable for practitioners to apply ideas from a group of experts or decision makers (DMs) instead of individuals. In a large proportion of recent studies, not enough attention has been paid to considering uncertainty in practical ways. In this paper, a hesitant fuzzy preference selection index (HFPSI) method is proposed based on a new soft computing approach with risk preferences of DMs to deal with imprecise multi-criteria decision-making problems. Meanwhile, qualitative assessing criteria are considered in the process of the proposed method to help the DMs by providing suitable expressions of membership degrees for an element under a set. Moreover, the best alternative is selected based on considering the concepts of preference relation and hesitant fuzzy sets, simultaneously. Therefore, DMs' weights are determined according to the proposed hesitant fuzzy compromise solution technique to prevent judgment errors. Moreover, the proposed method has been extended based on the last aggregation method by aggregating the DMs' opinions during the last stage to avoid data loss. In this respect, a real case study about the mining contractor selection problem is provided to represent the effectiveness and efficiency of the proposed HFPSI method in practice. Then, a comparative analysis is performed to show the feasibility of the presented approach. Finally, sensitivity analysis is carried out to show the effect of considering the DMs' weights and last aggregation approach in a dispersion of the alternatives’ ranking values.

First and Second Law Evaluation of Multipass Flat-Plate Solar Air Collector and Optimization Using Preference Selection Index Method

In this paper, different flow configurations of multipass flat-plate air collectors are explored. Multiple passes are formed from glass cover, absorber plate, and back plate. Five types of air collectors were analysed and optimized with respect to maximum efficiencies and minimum cost. The analytical prediction of the heat exchanger, pressure loss, and efficiencies was presented. The effects of mass flow rate from 0.01 to 0.02 kg/s, air channel depth from 15 to 30 mm, and collector length from 1.5 to 2.5 m on different configurations were examined and compared. The results of the parametric study show that the triple-pass type has the greatest efficiency, whereas the smallest efficiency is of the single-pass type. Among double-pass types, the type with two glass covers and natural convection heat transfer achieved the highest effective and exergy efficiencies due to a reduction in the top loss. Double-pass type with single glass cover is not recommended from both energy and exergy standpoints. As the collector length increases, the effective efficiency decreases, but the exergy efficiency increases. The exergy performance of the triple-pass type can reach up to 5% at the air flow rate of 0.005 kg/s. Finally, multiobjective optimization using the preference selection index method is conducted with three targets including effective efficiency, exergy efficiency, and number of plates. Optimal results show that the triple-pass type with the lowest air flow rate and the longest length is the best. The effective and exergy efficiencies for the best case were found to be about 52.1% and 4.7%, respectively. However, this type with the highest flow rate and the shortest length is the worst.

Multiobjective Optimal Power Flow for Static Voltage Stability Margin Improvement

The prevailing economic and environmental pressures have pushed the operation of power systems to close to stability limits. In such situations, utilities are aiming to increase the network’s stability during system disturbances. Optimized generation scheduling in contingency and stressed conditions can improve system security while lowering losses and generation costs. This paper focuses on incorporating Voltage Collapse Proximity Index in the conventional optimal power flow problem for multiobjective optimization. Multiobjective Particle Swarm Optimization (MOPSO) algorithm is utilized for its fast convergence and strong exploration and exploitation capabilities. The minimization of three competing objective functions of generation cost, power loss, and voltage stability is assessed in different case studies to evaluate the impact on the control variables. To select the best case study for optimal system operation a Preference Selection index (PSI) is utilized. The effectiveness of the proposed approach is tested on standard IEEE 30-bus and IEEE 57-bus during normal, contingency, and stressed conditions using MATPOWER. The results indicate that an average voltage stability improvement of 53.80%, 66.90%, and 54.15% is achieved in normal, contingency, and stressed system conditions respectively when the three objective functions are optimized simultaneously. Additionally, a possible voltage collapse is prevented during system disturbances.

Optimization of sliding and mechanical performance Ti/NI metal powder particulate reinforced Al 6061 alloy composite using preference selection index method

Abstract In this study, Ti/ Ni reinforced in AA6061 composites were prepared via a high vacuum stir casting method. The fabricated composite specimens are prepared for experimental studies as per ASTM standard and then physical, mechanical, and sliding wear characterization was conducted on different equipment. The higher confidence level (95%) obtained via experimental studies. The experimental results of the specimen have been used for optimization, and the ranking order of composite are computed via using the preference selection index method. Many researchers’ results have been reported and easily computed to rank of composite composition using optimization properties such as void contents,density flexural strength, tensile strength, impact strength, wear resistance etc. The resultsreveal that the base matrix included with the equal presence of both particulates exhibits most excellent properties hence to obtained best ranked of composition using the PSI method. Therefore, the PSI method could be helpful for decision making triumphantly in the material selection.

The implementation of the preference selection index approach in ranking water desalination technologies

The implementation of the preference selection index approach in ranking water desalination technologies

A novel hybrid approach for product concept evaluation based on rough numbers, shannon entropy and TOPSIS-PSI

This work aims to help the designers to make decisions in the early stage of new product development. Design concept evaluation is very critical in design process, it may affect the later stages. However, facing to uncertain circumstance, mostly, the raw data in early stage are subjective and imprecise. This work proposes a novel approach to solve this problem. The whole work is based on rough numbers, Shannon entropy, technique for order performance by similarity to ideal solution method and preference selection index method. Firstly, rough numbers and Shannon entropy are integrated to determine the weight of evaluation criteria based on their interrelationships. After that, a novel technique for order performance by similarity to ideal solution method improved by rough numbers and preference selection index method is proposed to evaluate and rank the alternatives. Then, a comparative case is carried out with proposed method and two other methods in this study. The comparation of evaluation processes indicates that the proposed method’s advantage. Compared the other methods, proposed approach is objective, simple and do not need additional input. The results of three methods are similar. It means that the proposed method is not only effective and efficient in design concept evaluation, but also can save time and cost in the early stage of new product development.

Application of preference selection index method in performance (mechanical properties and sliding wear) based ranking of AA2024‐Al2O3/SiC alloy composites

AbstractIn this research work, alumina/silicon‐carbide ceramic particulates are used to reinforce AA2024 with the objective of improvement in its mechanical performance so that it could be successfully applied for sliding wear applications e. g. counter‐surface of drum/disc in automobiles. The designed formulation was fabricated via semi‐automatic stir casting technique following standard industrial practice. Thereafter, the sample specimens were prepared as per ASTM standard dimensions and the physical/mechanical/sliding wear performance were evaluated and discussed. Taguchi design‐of‐experiment method was applied for designing of experimental runs and input control parameter optimization. The worn surface morphology studies were analyzed for understanding prevalent wear mechanism using field emission scanning electron microscope along with energy‐dispersive x‐ray spectroscopy. Further, multi‐criteria‐decision‐making tool namely, preference selection index method (computationally simple and easy to understand) have been applied in‐order‐to rank the composites of the formulation. The obtained test results have ∼95 % confidence level. It has been observed that alloy‐matrix mechanical properties improve with reinforcement that enhances the sliding wear performance. It has been verified that the composite sample with equal amount of reinforcements shows superior mechanical as well as sliding wear performance and ranked highest by preference selection index method methods. This infers that design engineer may use multi‐criteria‐decision‐making technique like preference selection index in selection of materials reasonably.

An Approach to Develop a Sustainable Preference Index for Self Compacting Concrete

In construction industry, selecting a right material from the various alternatives is a critical task in contributing to promote sustainability. For evaluating performance of the material different conflicting attributes are considered which is very complex to make a decision. Focusing on that point, there is a necessity to implement an effective MCDM (Multi-Criteria Decision Making) technique in the building construction which helps the decision makers to choose the feasible sustainable material from the alternatives. The present study explores about the application of Preference Selection Index Method to develop an approach in selecting the optimum Supplementary Cementitious Materials which is called as Sustainable Preference Index (SPI). The foremost concern in the study is to optimize the use of SCM’s as a substitute for cement in Self Compacting Concrete (SCC) to assess sustainable performance by considering technical, environment and ecological traits. To illustrate an approach to develop a Sustainable Preference Index a case study has been considered by varying mineral admixtures such as Fly Ash and GGBS by 10%, 20%, 30%, 40% replacement of the mass of cement in SCC. From different available SCC mixes, the possible alternate in Self Compacting Concrete can be identified based on Sustainable Preference Index value which indicates sustainable performance. Among the FA and GGBS based Self Compacting Concrete mixes, 40GGBS-SCC has attained the highest Sustainable Preference Index (SPI) value. For 40GGBS-SCC the SPI value obtained is 0.891 whereas for 100OPC-SCC it is 0.740. From the SPI values attained, it can be concluded that 40GGBS-SCC is 20.4% more sustainable than the 100OPC-SCC.

3D Printing of automobile spoilers using MCDM techniques

Abstract The ultimate objective is to evaluate the efficacy of three-dimensional printers (3DP) for manufacturing a rear spoiler for radio-controlled (RC) racing cars. This research work focuses on the development of a multicritaeria decision making (MCDM) model for selecting a 3DP. The selection process includes multiple adverse criteria such as maximum print volume (E1), speed of operation (E2), minimum thickness (E3), extruder capacity (E4), printer cost (E5) and filament material cost (E6). To reduce this adverse nature of the assessment criteria, the preference selection index (PSI) method is anticipated as an MCDM technique for selecting the most suitable 3DP. In this work, ten alternative printers, Lulzbot TAZ 5 (A1), Ultimaker 2 (A2), Zortrax (A3), Wanhao duplicator 4 (A4), Airwolf 3D AW3D HD2X (A5), Flash forge creator X(A6), Makerbot replicator original (A7), Delta non-turbo WASP 2040(A8), Artifex duo 2 (A9), UP plus 2 (A10)are considered for the assessment process. From the suggested PSI models, the Wanhao duplicator 4 (A4) has emerged as a suitable 3DP for RC car application.

3D Printing of automobile spoilers using MCDM techniques

Abstract The ultimate objective is to evaluate the efficacy of three-dimensional printers (3DP) for manufacturing a rear spoiler for radio-controlled (RC) racing cars. This research work focuses on the development of a multicritaeria decision making (MCDM) model for selecting a 3DP. The selection process includes multiple adverse criteria such as maximum print volume (E1), speed of operation (E2), minimum thickness (E3), extruder capacity (E4), printer cost (E5) and filament material cost (E6). To reduce this adverse nature of the assessment criteria, the preference selection index (PSI) method is anticipated as an MCDM technique for selecting the most suitable 3DP. In this work, ten alternative printers, Lulzbot TAZ 5 (A1), Ultimaker 2 (A2), Zortrax (A3), Wanhao duplicator 4 (A4), Airwolf 3D AW3D HD2X (A5), Flash forge creator X(A6), Makerbot replicator original (A7), Delta non-turbo WASP 2040(A8), Artifex duo 2 (A9), UP plus 2 (A10)are considered for the assessment process. From the suggested PSI models, the Wanhao duplicator 4 (A4) has emerged as a suitable 3DP for RC car application.

Multi-criteria Decision-making of Vibration-aided Machining for High Silicon-carbon Tool Steelwith Taguchi–topsis Approach

The frequency-aided electrical erosion machining process can enhance the process mechanism and efficacy. It is time consuming to choose the optimal vibration-oriented parameters in the electrical discharge machining (EDM) process. In the present study, the technique for order of preference by similarity to ideal solution (TOPSIS) based multi-attribute optimization was proposed in the process on machining high silicon-carbon tool steel under low vibrational frequency of the workpiece material. The surface roughness, material removal rate, micro-hardness, and white layer thickness were chosen as quality measures. The experimental investigation was performed by comparing TOPSIS engineering optimization with Deng’s approach, preference selection index, grey relational analysis, the Visekriterijumsko–Kompromisino–Rangiranje (VKR) approach, simple additive weighting, and complex proportional assessmentto analyse the accuracy of the TOPSIS approach. From the experimental analysis, it was inferred that the low-frequency vibration-associated workpiece can considerably improve the quality factors in EDM. The Taguchi–TOPSIS approach can provide a better computational approach to resolve the multi-objective optimal problem.

Implementation of Preference Selection Index Method in Decision Support System for Selecting School Inventory Users

This study aims to solve the problem of using a limited inventory of supporting media for learning at SD 096782 Tumorang Huta Dua Tumorang school, Gunung Maligas District, Simalungun Regency. The limitations of school inventories in the use of instructional media must be distributed to teachers so that they can be used in teaching. Therefore, the difficulty of distributing school inventory was overcome by implementing a decision support system using the Preference Selection Index (PSI) method. This method uses 6 criteria consisting of: years of service, behavior, performance, attendance, responsibility, and last education. The results of the application of the DSS with the PSI method obtained alternatives that are priority recommendations for school inventory users. The recommendation results obtained from the application of the DSS with the PSI method are Teacher_3 alternative with a final value of 0.8506. The second alternative is Teacher_01 with a final score of 0.8190 and the third alternative is Teacher_07 with a final score of 0.7846.

Optimal design of needlepunched nonwoven fiber reinforced epoxy composites using improved preference selection index approach

Viscose and polypropylene fiber-based needlepunched nonwoven fabric mat reinforced epoxy composites with varying mass per unit area (200, 400 and 600g/m2) and varying fabric mat weight percentage (20, 30, and 40wt.%) were fabricated. The manufactured composites were characterized for physical (density, void content), mechanical (impact energy, flexural, tensile and inter-laminar shear strength) and erosive wear properties. The evaluated properties were considered as performance defining attributes (PDAs) for the assessment of the composites. The experimental results indicate that there was no single composite which satisfied all the selected PDAs. Therefore, the improved preference selection index (PSI) approach was proposed to select the best composite alternative which yielded optimized physico-mechanical and erosive wear properties by considering all the PDAs at a single time. It was found that the composite alternative containing 40wt.% of 600g/m2 polypropylene fiber displayed the optimal physico-mechanical and erosive wear properties.

Experimental Investigation on the Friction and Wear Characteristics of Palm Seed Powder Reinforced Brake Pad Friction Composites

In this research work, palm seed power (0–9 wt%, step of 3%; four composites sample, namely P0, P3. P6, P9) were used to reinforce master batch of friction composite materials containing phenolic resin binder, steel swarf fibre, cashew, alumina, graphite, copper and zinc. The fabrications were as per standard industrial practice via hot compression moulding route. Thereafter, samples were cut and characterized for their tribological characteristics on specifically designed braking dynamometer using grey cast iron disc as per TS 555 and TS 9076 standards. Physical and mechanical properties such as hardness and density of the samples were also determined. Further, multi-criteria-decision-making like Preference Selection Index methods are used to ascertain ranking of material alternatives based on performance criteria. Both the subjective analysis and PSI output are in agreement with each other. Hence, such techniques often found suitable for decision-making or ranking of materials alternatives when performance criteria are of conflicting in nature.

A Novel Fuzzy Evaluation Method on Teaching Quality of College English based on Preference Selection Index

The evaluation of teaching quality is an important part of the quality management of teaching in colleges and universities. Many evaluation systems exist shortcomings, which are not suitable for the evaluation of English class. Because English subject has its own characteristics, in which the evaluation subject taken on students is more suitable than on teachers. This paper will propose a college English evaluation index system on the basis of students as the evaluation subject. Since the evaluation indicators are mainly qualitative indicators, which makes the evaluation value fuzzy, this paper proposes a new evaluation method of college English classroom teaching evaluation based on linguistic terms, triangular fuzzy numbers and preference selection index method. Finally, an algorithm case is analyzed to illustrate the effectiveness and feasibility of the proposed method.

Recovery alternatives decision by using fuzzy based preference selection index method

Recovery alternatives decision by using fuzzy based preference selection index method

Penerapan CBIS Untuk Mendukung Keputusan Manajemen dalam Menghitung Index Kinerja Karyawan PT Devrindo Wydia Karawang Menerapkan Preference Selection Index

In this study, the authors applied a method in the computer information base system (CBIS), the Preference Selection Index, or known as the PSI method. It aims to produce a preference index of each employee, which later the index value is used as a measure of employee performance so it is known as the Employee Performance Index. Alternative data from the study the author uses 30 data as samples to be calculated Employee Performance Index. In addition to employee data, the author also uses several criteria in measuring the Employee Performance Index, such as discipline, loyalty, years of service, sanctions and reprimands, education. These criteria greatly affect the assessment of employee performance index. It is expected that the results of the measurement provide the right decision for employees in calculating the Employee Performance Index.

Decision support system for determining the activities of the study program using the Preference Selection Index

Each year the study program carries out activities that have been planned through departmental meetings. However, study program activities that are not on target will result in less accreditation scores. Accreditation is a government effort to guarantee the quality of educational institutions. The value of accreditation determines the main assets in the field of education, the quality of study programs and the feasibility of graduates. Therefore, this study tries to provide a ranking formula for study program activities based on the assessment of study program accreditation forms. The system is built using one of type multi-criteria decision making (MCDM), namely the Preference Selection Index (PSI). PSI method using statistical concepts until preference index as a reference for alternative ranking. This developed system can help the department to recommend the main activities that can be done to support the efforts of the study program in achieving optimal accreditation values. Finally, it was concluded that the PSI method is the right method for problems that require decision support with a large number of attributes, such as the criteria used in recommendations for study program activities that have been adapted to the study program accreditation form assessment matrix.