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1

Zastosowanie metod wielokryterialnego wspomagania decyzji EIPICI i SAW w wyborze zrównoważonej receptury mieszanki betonowej

Dobaczewska Wioletta

Przegląd Budowlany

|

2026

|

R. 97, nr 3

180--184

PL

Budownictwo jako dział gospodarki narodowej o dużym znaczeniu społecznym i gospodarczym, a także o znaczącym wpływie na środowisko naturalne, jest wpisane w zasady zrównoważonego rozwoju. W kontekście technologii betonu najistotniejszym wyzwaniem, przed którym stoją producenci betonu, jest osiągnięcie możliwie najniższego śladu węglowego przy produkcji mieszanki betonowej. W artykule przedstawiono możliwość zastosowania metod wielokryterialnego wspomagania decyzji – SAW i EIPICI w celu wyboru receptury mieszanki betonowej w oparciu o kryteria techniczne, ekologiczne oraz ekonomiczne.

EN

Civil engineering as a division of natural economy with a great social and economic meaning, as well as with signifitcant influence on the natural environment embedded in the concept of sustainable development. In the context of concrete technology, the most significant challenge facing concrete producers is achieving the lowest possible carbon footprint in the production of the concrete mix. The article presents possibility of appling a multi-criteria decision suport SAW and EIPICI with the aim of choicing concrete mix according to the technical, ecological and economic criteria.

2

Human reliability management in industrial maintenance

Tabor Joanna

Zeszyty Naukowe Politechniki Morskiej w Szczecinie

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2025

|

nr 84 (156)

46--55

EN

The purpose of this study is to propose and verify the feasibility of using gray relative analysis (GRA) to identify key characteristics of an industrial maintenance system and key factors for managing human reliability in this system. The developed approach is verified using qualitative and quantitative data obtained from seven companies in the furniture industry. Through the approach used, the following maintenance characteristics are identified as key: scheduling intensity index, work scheduling intensity index, and work request response index. In addition, the following human reliability management factors are identified as key: analysis of error reduction measures, implementation of error reduction measures, and evaluation of the effectiveness of implemented human error reduction measures. The approach verified in this paper is computationally simple and beneficial in cases of imprecise and incomplete information and small sample size, while the results obtained are easy to interpret. This approach can, therefore, be a crucial tool for improving enterprises in maintenance and in terms of improving human reliability. The application of GRA in human reliability management in industrial maintenance is original.

3

Risks associated with the selection of a designer in a tender process

Jurczak Marlena Anna

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska

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2025

|

z. 225

239--250

EN

Purpose: The main objective of this article is an attempt to define the risk factors associated with the selection of a designer in a tender procedure on the example of a biogas plant in Olsztyn. The study aims to understand what risks may arise in the process of selecting a designer and what actions can be taken to minimize them. The results are expected to provide practical guidance for decision-makers and tender participants to increase the efficiency and safety of the entire process. Design/methodology/approach: The theoretical part of the study is based on a review of the literature and familiarization with the tender procedure of the discussed investment. The empirical part, on the other hand, consists of a seminar and a survey. In order to analyse the results obtained, risk assessments were carried out according to the classical approach as a product of the probability of their occurrence and the effects to which they may lead. Findings: Choosing the right designer is crucial for the success of the entire investment. The decision made is not always optimal, despite the use of different selection methods, also taking into account computer tools supporting this process. Research limitations/implications: The limitations of the research are related to conducting the analysis among a selected, small group of designers. Future studies should be extended to include a larger group of experts and for another biogas plant investment in order to compare the results. Also, the interpretation of expert data could have been carried out in many different ways. Practical implications: So far, no similar survey has been carried out, which may be helpful for further tender procedures of this type to raise the investor's awareness when making decisions. Originality/value: The article attempts to identify risk factors, thus showing how complex and ambiguous the decision-making process is, especially in tender proceedings, where many criteria are evaluated, and the choice made is not always optimal. Particular attention should be paid to the important aspects of risk in order to reduce them in the future. The article is mainly addressed to decision-makers of tender processes, but it is also universal in nature, because risk and decision-making accompany people at every step.

4

Application of multi-criteria optimization for feature selection in machine learning based risk classification supporting supply chain management

Topolska Katarzyna

Zeszyty Naukowe. Organizacja i Zarządzanie / Politechnika Śląska

|

2025

|

z. 221

581--599

EN

Purpose: The aim of this research is to develop a multi-criteria optimization method for supply chains operating under uncertain conditions. The study addresses the impact of supply chain disturbances (drifts) and proposes an AI-driven approach to enhance risk classification and stability. Design/methodology/approach: The research employs multi-criteria optimization techniques, specifically the NSGA-II genetic algorithm, to optimize feature selection in supply chain risk classification. The methodology includes experiments on global and local optimization of supply chain links, analyzing classification accuracy under different levels of drift. Machine learning models, including deep learning (DNN, CNN), Random Forest, and SVM, are used to assess the effectiveness of the proposed method. Findings: (mandatory) The study confirms that multi-criteria optimization improves supply chain stability and enhances the accuracy of drift classification models. The best feature selection strategies contributed to classification accuracy improvements, particularly in deep learning models, where performance gains of up to 2.5% were observed. The results demonstrate that both global and local optimization contribute to maintaining classification quality even under significant drift conditions. Research limitations/implications: While the study provides strong evidence for the effectiveness of multi-criteria optimization, it does not explore real-time adaptation to evolving risks. Future research should focus on integrating reinforcement learning and real-time monitoring for adaptive optimization. Additionally, extreme drift conditions (above 70%) still challenge classification accuracy, suggesting the need for further improvements in feature selection methods. Practical implications: The research has significant implications for supply chain management, enabling enterprises to improve risk detection and enhance resilience against supply chain disruptions. The proposed optimization approach can support automated decision-making systems in logistics, reducing operational risks and improving efficiency in dynamic environments. Social implications: By enhancing supply chain stability, the research contributes to economic resilience, reducing the negative impact of supply chain disruptions on businesses and consumers. Improved risk classification methods can support sustainable supply chain strategies, minimizing delays and reducing waste. Originality/value: This study introduces a novel application of multi-criteria optimization in supply chain risk classification, integrating feature selection with machine learning techniques. The findings provide valuable insights for researchers and practitioners in AI-driven supply chain management, offering new strategies for mitigating risk drift.

5

Evaluating Supply Chain Risks in The Moroccan Automotive Industry: A Multi-Criteria Decision-Making Approach

Kayouh Nabil, Dkhissi Btissam

Management Systems in Production Engineering

|

2025

|

nr 1 (33)

123--135

EN

Supply chain resilience is a critical determinant of success in the automotive industry, particularly in emerging markets like Morocco. This research employs a comprehensive approach to identify and prioritize external logistical risks threatening automotive supply chains in Morocco. Through interviews with logistics specialists of multinational automotive companies, we utilized the fuzzy Analytic Hierarchy Process (AHP) and the fuzzy Technique for Order Preference by Similarity to Ideal Solution (TOPSIS) to assess the weights of evaluation factors and rank the identified risks, respectively. Our findings reveal that catastrophic events in the factory, extreme weather conditions, and workers’ strikes/labor union issues are the top three risks posing the greatest threat to supply chains in Morocco. Additionally, challenges such as agitated political situations, high maintenance costs, and infrastructure limitations demand attention to enhance supply chain resilience. This research contributes to the understanding of supply chain risk management in emerging markets and offers practical insights for industry practitioners and policymakers aiming to fortify automotive supply chains in Morocco and similar contexts.

6

Evaluating Supplier Supply Chain Performance Using a Multi-Criteria Decision-Making Approach: Case Study in the Automotive Industry

Kayouh Nabil, Dkhissi Btissam

Management and Production Engineering Review

|

2025

|

Vol. 16, No. 2

[nr art. 2], s. 1--17

EN

Effective supply chain management is essential for business success and continuity. A key component of this management is supplier evaluation, which plays a vital role in mitigating logistical risks, optimizing value, and fostering long-term, mutually beneficial relationships within the supply chain. Although extensive research has been conducted, significant gaps re main in addressing sustainable supply chain risks and integrating them into supplier assessment frameworks. This study addresses this gap by proposing an integrated approach for evaluating and managing supplier-related logistics risks. The approach combines the Best-Worst Method (BWM) to assign relative weights to various sustainable supply chain risks with the fuzzy TOPSIS method to rank suppliers based on their risk profiles. A focus group is used to identify appropriate strategies to mitigate the identified risks. To demonstrate the practicality and effectiveness of the proposed framework, a real-world case study involving a multinational automotive company is presented. The results indicate that two specific suppliers require immediate attention and targeted risk mitigation strategies. This research provides supply chain managers with a robust evaluation methodology and actionable insights for improving supplier risk management in the automotive sector.

7

Evaluating resilience and sustainability in global supply chains: Multi-criteria decision-making approach for post-pandemic challenges

Akpınar Muhammet Enes

LogForum

|

2025

|

Vol. 21, no 1

63--72

EN

Background: The COVID-19 pandemic exposed vulnerabilities in global supply chains, highlighting the urgent need for resilience and sustainability. As businesses recover and adapt, selecting sustainable suppliers has become crucial to ensure long-term environmental, social, and economic stability. Sustainable supplier selection not only supports these goals but also enhances competitive advantage in a rapidly changing business landscape. This study was initiated to address these post-pandemic challenges, providing a systematic evaluation of suppliers based on sustainability using multi-criteria decision-making (MCDM) methods. It aims to assess the effectiveness of MEREC and CoCoSo methods in supporting sustainable supplier selection, offering insights and strategic guidance for businesses. To this end, it develops a novel approach integrating these methods that facilitates effective and sustainable supplier selection in the context of post-pandemic supply chain challenges. Methods: The study evaluates seven suppliers against five key criteria relevant to sustainable supply chains: environmental sustainability, social responsibility, cost, delivery time, and supplier reliability. The MEREC method is employed to assign weights to each criterion, establishing their relative importance in the supplier selection process. Following this, the CoCoSo method ranks the suppliers based on these weighted criteria, facilitating the identification of the most suitable supplier for sustainability-focused objectives. The combined use of MEREC and CoCoSo enables a robust and balanced approach to multi-criteria decision-making. Results: The MEREC analysis indicates that environmental sustainability and cost are the most critical criteria in sustainable supplier selection. Using the CoCoSo method, suppliers are ranked according to their performance across the criteria, with the top supplier offering the optimal sustainability balance. The findings support the use of these methods to prioritize suppliers aligned with sustainability goals, emphasizing the flexibility of CoCoSo in supplier ranking and the accuracy of MEREC in weight calculation. Conclusion: This study demonstrates the advantages of integrating the MEREC and CoCoSo methods in sustainable supplier selection processes. Its findings could guide businesses looking to optimize sustainability-focused decision-making processes in supply chain management. Future studies could expand the scope of this research by including more criteria and alternatives, and the approach could be adapted for sustainable supply chain practices in various industries. Such studies would contribute to global supply chain sustainability by supporting companies in fulfilling their environmental and social responsibilities.

8

Aggregating evaluation metrics for anomaly detection: A unified scoring approach

Rachwał Alicja, Gałka Łukasz, Rachwał Albert, Karczmarek Paweł

Advances in Science and Technology. Research Journal

|

2025

|

Vol. 19, no. 12

402--419

EN

This paper introduces a procedure that transforms multiple evaluation metrics into a single aggregated score, providing a comprehensive and interpretable summary of machine learning performance. The approach is demonstrated on a set of metrics obtained from various anomaly detection algorithms based primarily on Isolation Forest. Seven relevant performance metrics are aggregated using diverse techniques, including the arithmetic mean, weighted mean, Choquet integral, the OWA operator, and several Smooth OWA variants based on different interpolation Newton-Cotes quadratures. For methods requiring them, two distinct sets of weights are used. The results show that, particuraly in anomaly detection tasks where individual metrics may lead to inconsistent evaluations, the aggregated score effectively reflects metric preferences and enables quick identification of the best-performing algorithm for a given dataset.

9

Multicriteria assessment of green logistics in taiwan’s maritime freight tansport: green packaging and green transportation as driving aspects

Sujanto R. Y., Kao S. L., Yang M. F.

TransNav : International Journal on Marine Navigation and Safety of Sea Transportation

|

2024

|

Vol. 18 No. 1

35--44

EN

This study aims to establish a multicriteria-based model for understanding green logistics in Taiwan's maritime freight transport industry. Prior studies have emphasized certain successful results from using green measures on the operational logistics operations, including establishing a competitive advantage and economic benefits. However, the literature tends to be inadequate and fragmented when discussing how green logistics relate to environmental sustainability. This study proposes a framework containing 5 aspects and 35 criteria. The fuzzy Delphi and best-worst methods are adopted to evaluate the validity and reliability. A decision-making trial and evaluation laboratory method is used to examine how the attributes’ interrelationships. The results reveal that green packaging and green transportation become the determining aspects to enhance green logistics. The top five criteria to prioritize is presented including product life cycle impact, green packaging material, use of energy at facilities, intermodal transport, emissions of transporting vehicles within the area of facilities.

10

Aplikacyjność i wrażliwość wybranych metod wielokryterialnych przy wyborze sposobu realizacji Szczecińskiej Kolei Metropolitalnej

Kotecki Krzysztof, Dziadosz Agnieszka

Przegląd Budowlany

|

2024

|

R. 95, nr 4

72--77

PL

Współczesne inwestycje budowlane, w tym inwestycje kolejowe lub drogowe poprzedza szereg analiz warunkujących wybór optymalnego wariantu ich wykonania. Wielokryterialne analizy porównawcze stanowią doskonałe wsparcie procesu podejmowania decyzji wykorzystując zarówno dane ilościowe, jak i jakościowe. Zakres artykułu obejmuje analizę porównawczą przy wykorzystaniu różnych metod wielokryterialnego podejmowania decyzji, m.in. AHP, TOPSIS, COPRAS, VIKOR, PROMETHEE w celu minimalizacji subiektywności ostatecznej oceny rozpatrywanych wariantów. W artykule podjęto próbę uwypuklenia wartości poznawczej wykorzystanych metod i możliwości implementacji wyników w praktyce na przykładzie Szczecińskiej Kolei Metropolitalnej.

EN

Modern construction investments, including railway or road investments, are preceded by a series of analyzes determining the optimal variant of their implementation. Multi-criteria comparative analyzes provide excellent support for the decision-making process using both quantitative and qualitative data. The scope of the paper includes a comparative analysis using various multi-criteria decision-making methods, including: AHP, TOPSIS, COPRAS, VIKOR, PROMETHEE in order to minimize the subjectivity of the final assessment of the considered variants. The paper attempts to highlight the cognitive value of the methods used and the possibilities of implementing the results in practice based on Szczecin Metropolitan Railway.

11

A decision support model for mitigating supply chain risks based on a modified fmea, multi-objective optimization and multi-criteria decision-making approach

Kayouh Nabil, Dkhissi Btissam

Management Systems in Production Engineering

|

2024

|

nr 1 (32)

87--102

EN

Recent years have seen a huge development in the subject of supply chain risk management. In this increasingly uncertain world, the use of practical and effective tools for decision making and risk mitigation has become more necessary than ever. In this research, mitigation strategies for a tier one multinational company operating in the automotive industry and providing an assembly operation to final customer Renault Tanger and Renault SOMACA were prioritized according to their effectiveness, as well as their implementation costs. Based on research in the literature and the opinions of experts in the field. 44 risks and 55 mitigation strategies were identified. FMEA (Failure Modes and Effects Analysis) method was used based on the latest AIAG 2019 edition to filter and identify the risks to be prioritized, we used then a multi-objective optimization approach to identify the mitigation strate-gies that constitute the Pareto front for each of the risks and finally used the EDAS method for the final ranking of the strategies. Our case revealed that strategies like ensuring elaborating a contingency planning and defining the responsibilities, imposing contractual obligations on subcontractors, applying a flexible supply contract were found to be relevant risk mitigation strategies for the company. Managers interested in mitigating risk can deploy this model to prioritize risk mitigation strategies.

12

Z-numbers based modeling of group decision making for supplier selection in manufacturing systems

Aliyeva Kamala

Informatyka, Automatyka, Pomiary w Gospodarce i Ochronie Środowiska

|

2024

|

T. 14, nr 3

61--67

EN

The health of the supply chain, the company's performance, and the quality of the production as well as the success of the entire enterprise, directly depends on the reliability of the company's existing suppliers. Processing enterprises that depend on suppliers are trying to find the best option that will satisfy all customer requirements. With high-quality and inexpensive raw materials, the products produced by the enterprise will largely determine its economic indicators such as revenue, profit, and profitability. Therefore, this enterprise is especially faced with the issue of choosing the most appropriate supplier of resources. Basically, for processing enterprises it is very important to consider the parameters such as quality of incoming materials, terms of supply of raw materials, price of received raw materials, terms of contracts. The challenge in determining of supplier is how to choose reliable suppliers that can maintain supply chain continuity in an environment of ever-increasing instability and uncertainty. For this purpose, a methodology for selecting suppliers using Z-numbers was proposed. Using fuzzy Z numbers in supplier selection, decision-makers can assign values to various criteria in a way that reflects both the uncertainty and the confidence associated with those values. This can lead to more nuanced and robust supplier selection processes, considering a wider range of factors and uncertainties.

PL

Zdrowie łańcucha dostaw, wydajność firmy i jakość produkcji, a także sukces całego przedsiębiorstwa, zależą bezpośrednio od niezawodności obecnych dostawców firmy. Przedsiębiorstwa przetwórcze zależne od dostawców starają się znaleźć najlepszą opcję, która spełni wszystkie wymagania klientów. Dzięki wysokiej jakości i niedrogim surowcom produkty wytwarzane przez przedsiębiorstwo będą w dużej mierze determinować jego wskaźniki ekonomiczne, takie jak przychody, zyski i rentowność. W związku z tym przedsiębiorstwo to stoi przed szczególnym wyzwaniem, jakim jest wybór najbardziej odpowiedniego dostawcy zasobów. Zasadniczo dla przedsiębiorstw przetwórczych bardzo ważne jest uwzględnienie takich parametrów, jak jakość przychodzących materiałów, warunki dostaw surowców, cena otrzymanych surowców, warunki umów. Wyzwaniem przy określaniu dostawcy jest wybór wiarygodnych dostawców, którzy mogą utrzymać ciągłość łańcucha dostaw w środowisku stale rosnącej niestabilności i niepewności. W tym celu zaproponowano metodologię wyboru dostawców przy użyciu liczb Z. Wykorzystując rozmyte liczby Z w wyborze dostawców, decydenci mogą przypisywać wartości do różnych kryteriów w sposób, który odzwierciedla zarówno niepewność, jak i zaufanie związane z tymi wartościami. Może to prowadzić do bardziej dopracowanych i solidnych procesów wyboru dostawców, biorąc pod uwagę szerszy zakres czynników i niepewności.

13

Optimizing the Surface Parameters of Titanium (Ti-6Al-4V) Alloy Specimens Using WEDM Process Based on Taguchi-DEAR Algorithm

Thangaraj Muthuramalingam, Moiduddin Khaja, Annamalai Ramamurthy, Mian Syed Hammad, Almutairi Zeyad, Machnik Ryszard

Advances in Science and Technology. Research Journal

|

2024

|

Vol. 18, no. 6

422--431

EN

Because of its excellent mechanical qualities and weldability, titanium alloy is used in many different biomedical applications. Wire electrical discharge machining may be used to machine materials with such greater strengths and intricate forms. Using Taguchi-Data Envelopment Analysis-based Ranking (DEAR) approach and zinc-diffused coated brass wire electrode to improve Titanium alloy machining was the goal of this research project. The quality metrics that were taken into consideration were sur-face roughness, kerf width, and material removal rate. Among the selected factors, with an error of 2.7%, the optimal configuration of input factors was determined to be 130 µs (Ton), 40 µs (Toff), 50 V (SV), 6 A (IP), and 8 Kg (WT). Due to its relevance in the process of deionization, the Ton is the high-est influential parameter for creating quality measurements.

14

Fuzzy Multi-criteria Decision Model to Support Product Quality Improvement

Siwiec Dominika, Gawlik Remigiusz, Pacana Andrzej

Management and Production Engineering Review

|

2023

|

Vol. 14, No. 2

134--149

EN

Improving product quality while making decisions remains a challenge. The objective of this research was to develop a model that supports the precise enhancement of product quality through comprehensive analysis of possibilities, product incompatibilities, root causes, and recommended improvement actions. The model incorporated various tools and methods such as the SMARTER method, expert team selection, brainstorming, Ishikawa diagram, 5M+E rule, FAHP, and FTOPSIS methods. The study demonstrated that integrating quality management tools and decision-making methods into a unified model enables the accurate prioritization of activities for product quality management. This integrated approach represents the novelty of this research. The model was evaluated using a mechanical seal made of 410 alloy. The research findings can be valuable to enterprises seeking to enhance product quality at any stage of production, particularly for modified or new products.

15

Application of the spherical fuzzy dematel model for assessing the drone apps issues

Pandey Mamta, Litoriya Ratnesh, Pandey Prateek

Journal of Automation Mobile Robotics and Intelligent Systems

|

2023

|

Vol. 17, No. 2

36--50

EN

During the past few years, the number of drones (unmanned aerial vehicles, or UAVs) manufactured and purchased has risen dramatically. It is predicted that it will continue to spread, making its use inevitable in all walks of life. Drone apps are therefore expected to overrun the app stores in the near future. The UAV’s software is not being studied/researched despite several active research and studies being carried out in the UAV’s hardware field. A large‐scale empirical analysis of Google Play Store Platform apps connected to drones is being done in this direction. There are, however, a number of challenges with drone apps because of the lack of formal and specialized app development procedures. In this paper, eleven drone app issues have been identified. Then we applied the DEMATEL (Decision Making Trial and Evaluation Laboratory) method to analyze the drone app issues (DIs) and divide these issues into cause and effect groups. First, multiple experts assess the direct relationships between influential issues in drone apps. The evaluation results are presented in spherical fuzzy numbers (SFN). Secondly, we convert the linguistic terms into SFN. Thirdly, based on DEMATEL, the cause‐effect classifications of issues are obtained. Finally, the issues in the cause category are identified as DI’s in drone apps. The outcome of the research is compared with the other variants of DEMATEL, like rough‐Z‐number‐ based DEMATEL and spherical fuzzy number, and the comparative results suggest that spherical fuzzy DEMA‐ TEL is the most fitting method to analyze the interrela‐ tionship of different issues in drone apps. The findings revealed that highest influenced values feature request (DI9 ) 3.12, Customer support (DI6) 2.91, Connection/Sync ((DI4) 2./72, Cellular Data Usage ((DI3) 2.51, Battery (DI2) 2.31, Advertisements ((DI1) – 0.3, Cost (DI5) – 0.5, Additional cost (D11) – 0.5, Device Compatibility (DI7) – 0.96, and Functional Error (DI10) – 1.2. The outcome of this work definitely assists the software industry in the successful identification of the critical issues where professionals and project managers could really focus.

16

Evaluation of the Smart Cities Listed in Smart City Index 2021 by Using Entropy Based Copras and Aras Methodology

Gelmez Emel, Özceylan Eren

Foundations of Computing and Decision Sciences

|

2023

|

Vol. 48, No. 2

153--180

EN

Smart cities are included in the literature as a technology-based concept that has been on the agenda in recent years and whose framework is constantly changing with the changes in technology. There are different frameworks and indexes to define the smartness of a city. Smart City Index 2021 published by Institute for Management Development (IMD) and Singapore University of Technology and Design (SUTD) is one of the accepted studies in the world. In the report of Smart City Index 2021, 118 cities are evaluated in five criteria namely health & safety, mobility, activities, opportunities (work & school) and governance. To re-evaluate the cities and compare the results, a Multi-Criteria Decision Making (MCDM) process including Entropy based Complex Proportional Assessment (COPRAS) and Addivite Ratio Assessment (ARAS) methodology is applied in this paper. To prioritize the criteria, entropy weight method is used. 118 cities are ranked both technologically and structurally using the COPRAS and ARAS method. As a result of the analyses, according to these methods, the rankings of the smart cities are the same. Also, when technologically smart cities are listed, it is determined that the first three countries are Zhuhai, Shenzhen, Nanjing, and at the same time, Abu Dhabi, Chongqing, Hangzhou in terms of structurally.

17

Use of integrated AHP-topsis method in selection of optimum mine planning for open-pit mines

Ozdemir Ali Can

Archives of Mining Sciences

|

2023

|

Vol. 68, no. 1

35--53

EN

Successful mine planning is necessary for the sustainability of mining activities. Since this process depends on many criteria, it can be considered a multi-criteria decision making (MCDM) problem. In this study, an integrated MCDM method based on the combination of the analytic hierarchy process (AHP) and the technique for order of preference by similarity to the ideal solution (TOPSIS) is proposed to select the optimum mine planning in open-pit mines. To prove the applicability of the proposed method, a case study was carried out. Firstly, a decision-making group was created, which consists of mining, geology, planning engineers, investors, and operators. As a result of studies performed by this group, four main criteria, thirteen sub-criteria, and nine mine planning alternatives were determined. Then, AHP was applied to determine the relative weights of evaluation criteria, and TOPSIS was performed to rank the mine planning alternatives. Among the alternatives evaluated, the alternative with the highest net present value was selected as the optimum mine planning alternative. It has been determined that the proposed integrated AHP-TOPSIS method can significantly assist decision-makers in the process of deciding which of the few mine planning alternatives should be implemented in open-pit mines.

18

Material Selection of Collapsible Pot Hauler and Finite Element Analysis Simulation Applied to the Selected Material

Surya Hadi Saputra Rahmad, Iskandar Budhi Hascaryo, Kurniawati Vita Rumanti, Desrial Desrial, Purbayanto Ari

Advances in Science and Technology. Research Journal

|

2023

|

Vol. 17, no. 2

289--298

EN

The current collapsible pot hauler uses a wooden frame, thus making much space in the working area of the fishing boat and also at this time challenging to find the best quality wood at this time. In this study, the wood material would replace by metal; the selection of the proper material is critically needed. A suitable material means the applied material has to deal with environmental conditions. Finding the appropriate material applied to the collapsible pot hauler; can be determined using a Multi-Criteria Decision Making (MCDM) approach. After selecting the proper material, the collapsible pot hauler simulates the material stress using the Finite Element Analysis (FEA) simulation. The material for the new model of collapsible pot hauler was selected using the WSM method. The material with the highest rank (selected) is AISI 304, with a preference value of 3.58. The static strength simulation using the FEA method utilizing Solidworks Software shows that the yield strength value is still below the material properties, which a maximum value is 200. MPa, the material safety factor is the minimum value above one, which is 1.24 on the line spool plate shafts. It means that the material AISI 304 is safe to be applied to the collapsible pot hauler.

19

Use of the grey incidence analysis in the inland waterway transport system assessment

Tabor Joanna

Zeszyty Naukowe Akademii Morskiej w Szczecinie

|

2022

|

nr 72 (144)

57--64

EN

Inland waterway transport (IWT) is currently in focus for EU countries due to a shift in policy towards a more sustainable and green economy. The aim of this article is to analyze the possibility of using a grey incidence analysis (GIA) to identify key factors related to the functioning of the IWT system. GIA is classified as a multi-criteria decision-making method and is one of the key applications of grey systems theory (GTS), i.e., systems with incomplete and uncertain information about structure and behavior. GIA identifies the most favorable (or quasi-preferred) system characteristics and the most favorable (or quasi-preferred) system factors. The identification of such characteristics and factors enables a reduction in the inconsistencies in decision making on the functioning of the system. The application of the GIA to the assessment of the IWT system is an original concept.

20

Użyteczność analizy LCCA do oceny efektywności ekonomicznej robót dociepleniowych ścian zewnętrznych budynku zabytkowego

Dziadosz Agnieszka, Siejek Ewelina, Rejment Mariusz

Materiały Budowlane

|

2022

|

nr 10

18--20

PL

Celem artykułu jest ocena efektywności ekonomicznej trzech sposobów wykonania robót dociepleniowych ścian zabytkowego budynku wg analizy LCCA (ang. Life Cycle Cost Analysis) oraz metody wielokryterialnej PROMETHEE. Na podstawie uzyskanych wyników określono najkorzystniejsze rozwiązanie, potwierdzając wybór wariantu docieplenia ścian zewnętrznych, który w rzeczywistości został zrealizowany w przypadku zabytkowego budynku dworku w Skrzynkach k. Poznania.

EN

The aim of the article is to assess the economic efficiency of three ways of performing wall insulation works for a historic building based on the LCCA (Life Cycle Cost Analysis) analysis and the PROMETHEE multi-criteria method. On the basis of the obtained results, the most favorable solution was determined, thus confirming the selection of the external wall insulation variant, which was in fact implemented for the historic manor house in Skrzynki near Poznań.