Decision Matrix Research Articles

Optimum selection of nature-inspired texture pattern for cutting tool surface using an integrated multi-criteria decision-making approach: a comparative analysis

Purpose This paper aims to focus on the selection of an appropriate nature-inspired texture pattern for cutting tool tribological surface. The selection process uses the recognized skin textures of different snakes scrolling on highly rough and projected surface conditions to analyze suitability of texture based on the texture geometry and machining conditions. The work also aims to propose a texture pattern selection process to incorporate on cutting tool tribological surface. Design/methodology/approach The selection of alternative nature-inspired texture patterns based on the texture pattern geometry and machining properties leads to a multi-criteria decision-making problem. Thirteen criteria are considered for selecting an appropriate texture pattern among 14 alternatives, i.e. nature-inspired texture patterns. In the present work, an integrated analytical hierarchy process (AHP)-TOPSIS, AHP-multi-objective optimization on the basis of ratio analysis (MOORA) and AHP-Vlse Kriterijumska Optimizacija Kompromisno Resenje (VIKOR) approaches have been proposed for the selection of an appropriate nature-inspired texture pattern. AHP is used for the formulation of decision-making matrix and criteria weight calculations and ranking of alternatives is done by three methods. Spearman’s correlation compared and found positive relations between rank assigned by methods. Experimental validation is done in Lathe for selected texture effects. Findings The texture parameters C-1 (Width of texture) and C-2 (Depth of texture) are found significant, while T-2 (Blended Krait) and T-6 (Banded Racer-1) texture is found optimal to generate on cutting tool surface. Research limitations/implications Only some nature-inspired texture patterns have been recognized before the selection; an infinite number of textures are available in nature. The size of the texture pattern is difficult to identify by the selection process because each texture pattern may have different effects on tribological surfaces. Practical implications The proposed selection methodology of nature-inspired texture patterns will help identify optimal texture geometry for specific tribological applications. The nature-inspired texture patterned tool has a significant impact on the cutting force and temperature due to its tribological effect on the cutting tool surface; it decreases the power required for machining. The machining characteristics like roughness are found to decrease by using nature-inspired texture patterned tools. Social implications Various nature-inspire texture studies to generate specific effects on the tribological surfaces may be started study for the surface of aircraft, ships, bearings, etc. Small and big fabrication industries may benefit by decreasing the cost of machining using nature-inspired texture-patterned tools. Research society will pay attention to nature’s inspiration. Originality/value Novel snake-skin-inspired texture patterns are recognized and hybrid MCDM methods are proposed to select optimal texture pattern. Proposed method used single time normalization to effectively rank the alternatives. The insights gained from this research can be extrapolated to address similar challenges in selecting nature-inspired textures for various applications. Peer review The peer review history for this article is available at: https://publons.com/publon/10.1108/ILT-05-2024-0163/

Comparative Analysis of Mutual Funds and Gold ETFs: A Study on Investment Performance

This project analysis the returns of specific large-cap equity mutual funds and Gold Exchange Traded Funds (ETFs) to determine the best investment options for investors looking to balance growth and stability. To create a well-rounded portfolio, the study assesses the performance metrics and risk factors of these investment options. Large-cap equity funds are examined for their ability to offer growth in investment value, while gold ETFs are evaluated for their function as protection against market fluctuations and rising prices. A Decision matrix framework is utilized to methodically assess every fund and ETF based on factors including past performance and level of risk. This method based on data allows for a comprehensive analysis, pointing out the advantages and drawbacks of equity and gold investments. The research provides information on strategic asset allocation, highlighting diversification to maximize profits and handle risk efficiently. The results are meant to assist investors in making knowledgeable, eco-friendly investment choices in a changing financial environment.

Development of a methodology for assessing the efficiency of an agribusiness enterprise in using digital technologies

The object of the study is the activity of an agribusiness enterprise in using digital technologies. The problem of the methodology for assessing the effectiveness of using digital technologies by an agribusiness enterprise is solved. The following results were obtained: – the author's methodology for assessing the effectiveness using of digital technologies by an enterprise of AIC based on expert evaluation and a system of indicators was developed. The assessment results are interpreted in accordance with the matrix of intersection of the digitalization index and the effect of digital technologies from Outsider (0–0.25; <1) to Leader (0.95–1; ≥1); – the obtained concordance coefficient (76 %, χ2=41.9) indicates high consistency of the expert group, consistency and qualitative assessment in the process of testing the methodology; – testing of the proposed methodology in Atameken-Agro JSC was successful and showed the validity and convenience of this methodology. The agro-enterprise became the leader in 2023 with the indicators of digitalization level – 0.83 and the effect of using digital technologies – 12.5. The above results are explained by assuming the possibility of using the expert judgment method to evaluate the efficiency of using digital technologies by an enterprise and applying a decision matrix based on two indices. A particular feature of the results obtained is the development of a methodology for assessing the level of digitalization in three main areas and its application in combination with the assessment of the economic effect of digital technologies. The proposed methodology can be used not only by enterprises wishing to evaluate the effectiveness of digital technologies but also by stakeholders.

Preview control for linear parameter‐varying discrete‐time systems using a linear fractional representation

AbstractIn order to create a mixed tracking controller for discrete‐time linear parameter‐varying (LPV) systems, this work introduces a unique control strategy employing a linear fractional representation (LFR). Under the premise that the reference signal can be previewable, a design strategy for a controller with preview compensations is suggested. First, a preview tracking control issue is changed into a regulator problem by adding two additional linked auxiliary parameters into the initial system state/input, which further creates more enhanced error systems incorporating future information of reference signals. The suggested conditions then depend on utilizing slack variables with decision matrices related to the LFR approach in order to give innovative preview controller designs. We also construct reduced conservative synthesis situations by taking into account parameter‐dependent Lyapunov functions and full‐block multipliers. In order to create state‐feedback and output‐feedback preview tracking controllers, design requirements are characterized as linear matrix inequalities. Two simulation studies are completed as the last step to highlight how successful the suggested control strategy is.

Comparative Analysis of Burn Injuries in Toddler and Preschool Children: Implications for Triage and Outcome Assessment.

This study aims to compare the demographic, clinical characteristics, and outcomes of burn injuries in toddler and preschool children, and to validate the American Burn Association (ABA) Burn Triage Decision Matrix in the Turkish pediatric population. A retrospective analysis was conducted on 684 pediatric burn patients (494 toddlers, 190 preschoolers) admitted to our burn center over a 5-year period. Variables including gender, burn etiology, burn area, depth, treatment modalities, complications, length of hospital stay, and mortality were analyzed. The performance of the ABA Burn Triage Decision Matrix was evaluated in both groups. Scalding was the predominant cause of burns in both groups, with a significant difference in the involvement of anterior trunk (p = 0.027). The mean Total Body Surface Area (TBSA) was comparable between the groups (p = 0.286). There was no significant difference in mortality rates (p = 0.385), treatment modalities, and complications. The ABA Burn Triage Decision Matrix demonstrated consistency in triaging the severity of burn injuries, with a notable discrepancy observed in the moderate risk category of toddler group. This study highlights the distinct characteristics and outcomes of burn injuries in different pediatric age groups. The ABA Burn Triage Decision Matrix's validation suggests its utility in enhancing triage accuracy and resource allocation in pediatric populations, especially in disaster-prone regions.

The TOPSIS method: Figuring the landslide susceptibility using Excel and GIS

The current study introduced Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to enhance landslide susceptibility. It determines the relative distance of each alternative from the ideal best and ideal worst value. The ArcGIS environment was used to prepare eleven landslide conditioning factors, while raster values were extracted for the decision matrix preparation. We utilized subjective expert judgment to create a weighted matrix that considers the roles of each conditioning component. In addition, a Euclidean distance was measured from each alternative to the ideal best and worst values. The relative closeness value (Ri) has been used to prepare the landslide susceptibility index by the inverse distance weighting (IDW) interpolation. Furthermore, the precision of the landslide susceptibility was justified by area under curve-receiver operating characteristic (AUC-ROC) which was 0.987. Hence, multi-criteria decision-making (MCDM) techniques like the TOPSIS method are very useful for natural hazard mapping.•The simplified TOPSIS approach described by Hwang and Yoon (1981) is applied in this study. The criteria have been categorized and assigned weights based on expert judgment and previously published material.•The TOPSIS approach and GIS integration has significantly enhanced the creation of a landslide susceptibility map for a sensitive area.•The method is easiest and suitable for short term operation research.

Biweight midcorrelation-based CRITIC method: a case study for electrification of BIPV in Iran

Criteria weights are essential in various multi-criteria decision-making (MCDM) approaches. The amount of weight indicates the criterion's importance, and the performance of MCDM techniques depends on the correct estimation of criteria weights and criteria amount in the decision matrix. The distance correlation-based CRiteria Importance Through Inter-criteria Correlation (CRITIC) technique is a modified version of the CRITIC method. Since Pearson's correlation is sensitive to noisy and outlier data, this paper proposes using the biweight midcorrelation as a robust alternative to Pearson's correlation. The weights obtained from the proposed biweight midcorrelation method make using the full range of MCDM techniques possible. This study examined the performance of the proposed method in comparison with eight criteria weighting techniques on the electric supply for a Building-Integrated PhotoVoltaic (BIPV) problem. Results from three different tests (i.e. distance correlation, Spearman rank-order correlation, and symmetric mean absolute percentage error (sMAPE)) indicated that the proposed method could produce more valid criteria weights and ranks than other methods. The value of the sMAPE criterion for the proposed method is 0.1096. Sensitivity analysis also revealed that the proposed method provides more robust criteria weights and ranks with a larger decision matrix.

Planning decentralized wastewater treatment systems by comparing through TOPSIS

ABSTRACT This study evaluates 10 case studies of decentralized wastewater treatment systems (DEWATS) and compares them based on their environmental and economic performance. The aim is to identify the best treatment system composed of specific treatment processes that can be used in the future for hospitals, universities/colleges, and small communities. The comparison was conducted using the Technique for Order Preference by Similarity to the Ideal Solution (TOPSIS) method of multiple criteria decision-making. According to the TOPSIS method, systems are ranked from 1 to 10 by normalizing and weighting the decision matrix criteria, measuring the alternative's distance from the ideal best to worst value, and then calculating the performance score of each system. The study found that the H4 system, which includes a septic tank, anaerobic baffled reactor, anaerobic filter, horizontal filter, and pond, achieved the highest performance score. Therefore, the processes of the H4 system are recommended as the best alternative for DEWATS. This study may therefore assist stakeholders on their decision to implement DEWATS in similar facilities.

Quantitative Analysis Toward Guidance for Implementing E-Ticketing for Asphalt Paving Operations

Previous research efforts into e-ticketing for asphalt paving operations have qualitatively identified benefits and concerns. However, there is minimal academic literature detailing the quantitative impact of e-ticketing in the post-COVID-19 pandemic era. This research addresses this gap by gathering information from the Kentucky Transportation Cabinet (KYTC) about e-ticketing practices to aid in determining potential implementation steps. Quantitative project information was collected from KYTC projects to compare the traditional weigh ticket collection process with e-ticketing processes for both project engineers and inspectors. The analysis shows statistically significant time savings for field employees but not project management personnel. Further, factors affecting e-ticketing implementation for both project engineers and inspectors were also investigated. For inspectors, the dataset was analyzed to determine how the project type and quality assurance responsibilities of the inspector altered the e-ticketing impact. For engineers, the dataset was analyzed to determine how the project type altered e-ticketing impacts and how e-ticketing affected the engineer reviewing and storing project data. Cluster analysis was completed for both project engineers and inspectors to group project types where e-ticketing impact was maximized, and a decision matrix was created to aid agencies in creating implementation plans. The primary contributions to the body of knowledge include a modified action research methodology applied to electronic bulk material tickets to incorporate practitioner expertise into implementation guidelines and quantitative findings indicating that state transportation agencies should first implement e-ticketing on large asphalt-resurfacing projects, such as interstate rehabilitations, where inspectors have strenuous quality assurance responsibilities to maximize benefit.

Application of a multi-criteria decision technique to assignation of acoustic classes

Acoustic performance evaluation of buildings prior to the acoustic classification, requires consideration of a number of factors with the corresponding quantitative criteria to be satisfied. It is of question how much the deviations can be compensated and whether all performance factors are equally important. This paper presents the results of a study on assigning priorities for each acoustic factor by using the analytic hierarchy process (AHP) - a multi-criteria decision technique - based on the expert evaluations. Eleven acoustic consultants rated seven acoustic factors, i.e. regulatory criteria of sound insulation, sound level and reverberation time, in pairwise comparisons. The data were aggregated after a consistency check and weights of each acoustic factor were calculated as well as weights of six acoustic performance classes ranging from A to F. The outcomes of this study resulted in a decision matrix, named as "acoustic scorecard" which can be used to obtain a single-number rating index for acoustic quality of buildings.

Solving MADM Problems based on Matrix Games with a New Defuzzification Method for Triangular Intuitionistic Fuzzy Numbers

Abstract: The paper discusses about a new defuzzification method called the Comprehensive Li-Samuel ranking for Triangular Intuitionistic Fuzzy Numbers (TrIFNs) which is improved from the Li-Samuel ranking method associated with membership function and Li-Samuel ranking method associated with non-membership function. The Comprehensive Li-Samuel ranking for TrIFNs is utilised to derive the weights for the Multiple Attribute Decision Making (MADM) problems under TrIFN. The MADM problem is solved based on two-person zero-sum game which is converted into a pair of LPP by using Comprehensive Li-Samuel ranking. The process of transforming decision matrix into a matrix game and deriving decision maker’s and attribute weights from the matrix game are discussed. Numerical illustration is given to justify the viability and effectiveness of the proposed method and comparisons are made with existing ranking methods. The comparison study reveals that the proposed method provides the best maximum optimal solution for the decision problem than the existing methods

Investigation of the Robust Integration of Distributed Fibre Optic Sensors in Structural Concrete Components.

In recent times, the value of data has grown. This tendency is also observeable in the construction industry, where research and digitalisation are increasingly oriented towards the collection, processing and analysis of different types of data. In addition to planning data, measurement data is a main focus. fibre optic measurements offer a highly precise and comprehensive approach to data collection. It is, however, important to note that this technology is still in research regarding concrete structures. This paper presents two methods of integrating filigree sensors into concrete structures. The first approach entails wrapping a fibre around a tendon duct and analysing the installation and associated measurements. The second method involves bonding polyimide and acrylate-coated fibres with 2K epoxy and cyanoacrylate in the grooves of rebars, exposing them to chemical environments. The resulting measurement data is evaluated qualitatively and quantitatively to ascertain its resilience to environmental factors. These developed criteria are consolidated in a decision matrix. Fibre-adhesive combinations necessitate protection from chemical and mechanical influences. The limitations of the solutions are pointed out, and alternative options are proposed.

Promoting health information system in guiding decisions for improving performance: an intervention study at the Research Institute of Ophthalmology, Giza, Egypt.

This study aims to design and test a platform of key performance indicators (KPIs) and indices emphasizing achievements and improvement and helping decision-making. An operations research study was designed to analyze data from the Hospital Management Information System (HMIS) from July 2017 to June 2018 at the Research Institute of Ophthalmology (RIO), Giza, Egypt. The HMIS data were submitted to reform covering parameters in service delivery and corresponding indicators and indices. Data were grouped into four themes: human resources and outpatient, inpatient, and surgical operations. A total of 14 performance indicators were deployed to four specific indices and total performance indices and applied to six teams of ophthalmologists at RIO. The decision matrices were deliberated to demonstrate achievements and provide recommendations for subsequent improvements. Throughout 1 year, six teams of ophthalmologists (n = 222) at RIO provided the following services: outpatient (n = 116,043), inpatient (n = 8,081), and surgical operations (n = 9,174). Teams 2, 1, and 6 were the top teams in the total performance index. Team 4 had plunges in the outpatient index, and Team 5 faced limitations in the inpatient index. The study provided a model for upgrading the performance of the management information system (MIS) in health organizations. The KPIs and indices were used not only for documenting successful models of efficient service delivery but also as examples of limitations for further support and interventions.

Integrated analytic hierarchy process and multi-criteria decision-making approach: An Application for Unmanned Underwater Vehicle Control Method Selection

Using Multi-Criteria Decision Analysis (MCDA) techniques, it is possible to thoroughly examine all available options and determine the most desirable ones. However, the prevalence of these methods, which employ various computational changes, can result in disparate outcomes. Therefore, the final rankings should be as dependable and consistent as possible. In this study, the consistency of the findings obtained from the TOPSIS, COPRAS, MAUT, and MOOSRA methodologies was investigated in the real-world problem of Unmanned Underwater Vehicle Control Method Selection by forming decision matrices through simulations.

A Quantitative Assessment Approach to Implement Pneumatic Waste Collection System Using a New Expert Decision Matrix Related to UN SDGs

An innovative decision matrix has been developed to guide the selection and implementation of Pneumatic Urban Solid Waste Collection Systems (PUSWCS) in smart city projects. This study comprehensively collects and analyzes data on the advantages and disadvantages of pneumatic collection systems from technical, economic, and social perspectives. A decision-making tool was created to address the complexities of evaluating the desirability of incorporating PUSWCS in municipalities or specific areas, using a holistic approach. The tool assesses the technical, economic, and social feasibility of implementing PUSWCS, aligning it with the United Nations’ Sustainable Development Goals (SDGs). Specific variables are measured to assess compliance with the SDGs, distinguishing technical aspects from economic and social aspects. The methodology includes surveys of system users and technicians, expert assessments, and the development of a decision matrix that cross-references study variables and SDGs. The matrix assigns numerical values to the Magnitude (M) and Impact (I) of each variable, enabling quantitative interpretation. This holistic approach accommodates the complexities of waste management and diverse stakeholder perspectives. The results demonstrate the matrix’s effectiveness in accurately assessing the desirability of implementing PUSWCS. This confirms the matrix’s ability to optimally integrate with innovative smart city concepts and align with long-term sustainability goals. The study concludes that the design of the decision matrix allows the collection of information from experts, users, and stakeholders about economic, social, and environmental variables and relates them to the SDGs, to obtain a numerical result that allows to decide whether in a given urban environment it is advisable to implement a PUSWCS.

Strategies for Performance Optimization: Risk Mitigation in Tourism Supply Chains of Indonesia

In the context of optimizing performance, the tourism industry has great potential as a source of income for regions and countries. One area that has great potential in the tourism industry is Rembang Regency, Central Java, Indonesia. However, this industry is also vulnerable to various risks, such as natural disasters, pandemics, and security issues. Therefore, this research aims to identify risks in the tourism industry supply chain in Rembang Regency and develop effective mitigation strategies. The research method used is decision matrix risk assessment (DMRA), which involves supply chain mapping, risk identification, risk assessment, risk response development, and risk response control. The results of identifying risks that need to be mitigated from travel agents to tourist activities include fluctuating products/services, incompatibility with tourist destinations, and failure in promotional programs. Meanwhile, stakeholder activities in the tourism industry include failure in formulating policies and promotional programs. Proposed mitigation measures include diversifying supply chains, improving communication between suppliers and the tourism industry, and developing flexible policies. Implementation of this strategy is expected to strengthen the tourism industry supply chain in Rembang Regency, improve the tourist experience, and support sustainable economic growth. Risk mitigation in the tourism industry also contributes to the performance of the tourism industry and the achievement of sustainable development goals (SDGs) by providing benefits to the environment, economy, and local communities.

Research on the design of growable children’s beds based on combined hierarchical analyses

Although the market share of domestic children’s furniture is increasing annually, some potential problems limit its long-term and stable development, and there is still a gap in China compared with foreign countries. This study focused on the demand preferences for growable children’s beds and examined the design features that influence these preferences. This study introduces a combination of Hierarchical Analyses (AHP), Quality Function Development (QFD), and the Platts Conceptual Decision Matrix (PUGH) into the innovative design of a research model for children’s furniture (AHP-QFD-PUGH). This study screened and classified the decision-making indicators obtained from the research, ranked their importance by quantitative calculation, and finally proposed an optimal design solution. Additionally, to further study the structural characteristics, the function-behavior-structure (FBS) model served as a supplementary analysis tool to effectively circumvent subjective factors in product design. This integrated model accurately explored user needs and product characteristics, providing substantial guidance and new ideas for optimizing the design of growable children’s beds and enhancing growth of the children’s furniture industry.

A behavior three-way decision approach under interval-valued triangular fuzzy numbers with application to the selection of additive manufacturing composites

Additive manufacturing composites, also recognized as three-dimensional (3D) printing composites, are highly anticipated for their potential to replace industrial materials due to the availability of multiple printing processes and optional materials. However, research gaps exist in cognitive deficiencies and psychological behaviors of decision-makers, as well as experimental error effects caused by material testing, resulting in material selection as a challenging issue. Therefore, this study proposes a novel behavior three-way decision model under the interval-valued triangular fuzzy number (IVTFN) to settle the selection issue of 3D printing composites. The research contributions are summarized as follows. First, the IVTFN is presented to account for the impacts of cognitive deficiency and experimental errors, based on which the concepts of information entropy and fuzzy measure are further developed to conduct the criterion weights. In addition, by integrating the prospect theory and regret theory, a framework for constructing the behavioral decision matrix is presented. Moreover, a novel behavior three-way decision model with the perspectives of objective and preference is proposed to classify the decision region. This study presents a comprehensive methodology integrating the three-way decision model and multi-criteria decision-making method to achieve both alternative ranking and alternative classifying. Finally, a research case of 3D printing composites reinforced by continuous hybrid fibers is adopted to illustrate the validity of the methodology. Comparative analysis and sensitivity analysis are also performed. This study offers valuable insights and tools for systematically tackling the 3D printing composite material selection issues.

Dual strategies consensus reaching process for ranking consensus based probabilistic linguistic multi-criteria group decision-making method

Group consensus is critical in multi-criteria group decision-making (MCGDM). However, the extant consensus reaching process (CRP) methods focus on the consensus on the decision matrices rather than the rankings of alternatives. This paper proposes the dual strategies CRP for ranking consensus based probabilistic linguistic MCGDM. According to the decision matrices provided by decision makers, the rankings of alternatives are generated. Then, we define ranking similarity degree based on the individual alternative rankings and opinion similarity degree based on the decision matrices, respectively. Based on the ranking similarity degrees, the group consensus index (GCI) is defined and the dual strategies CRP are proposed. In the proposed CRP method, the first strategy pays attention to DMs with low ranking similarity degree but high opinion similarity degree, while the second strategy in CRP concentrates on DMs with low ranking similarity degree and low opinion similarity degree. The first strategy constructs minimum adjustment programming model while the second strategy directly provide adjustment advice according to the reference evaluation. These two strategies both aims to change the rankings of alternatives by adjusting the evaluations in the decision matrices. At length, an actual example is presented to demonstrate the effectiveness of the erected method and comparison analyses clarify its advantages and superiorities.

Strategic selection of metal-cutting processes for thick steel plates using a hybrid decision methodology

Metal-cutting is indispensable in manufacturing, enabling precise component fabrication for industries like construction, automotive, aerospace, and shipbuilding, where accurate, efficient cutting of thick steel plates is crucial. This paper introduces a novel case study to strategically determine the optimal metal-cutting process for thick steel plates utilizing a hybrid MOORA-PSI approach. The use of the hybrid MOORA-PSI method simplifies decision-making by integrating weight assignment and ranking of alternatives. Five prominent metal-cutting processes, including oxygen flame, plasma arc, laser, wire EDM (wire electro-discharge machining), and abrasive water jet cutting, are commonly used for cutting thick steel plates, each with unique capabilities and limitations, and are considered potential alternatives. Eight evaluation criteria, capital cost, running cost, accuracy, edge quality, kerf width, maximum thickness, production flexibility, and production rate, are used to assess these metal-cutting alternatives. Wire EDM ranks as the optimal choice for cutting thick steel plates based on defined evaluation criteria, with laser cutting closely trailing, followed by oxygen flame, abrasive water jet, and plasma cutting successively. The results are validated by comparing them with those of other MCDM approaches and by conducting a Spearman’s rank correlation coefficient test, yielding consistent results. Additionally, sensitivity analysis, employing criteria weight exchange and dynamic variations in the decision-making matrix, further confirms the accuracy and reliability of the findings.