The prioritization of criteria for the selection of radar for the air traffic control and protection by multi-criteria decision: Making application in the fuzzy environment

The prioritization of criteria for the selection of radar for the air traffic control and protection by multi-criteria decision - making is presented in the paper. By analyzing the content of the available literature, the criteria and attributes of the criteria, on whose basis it is possible to evaluate the radar for the air traffic control, have been separated. The mutual influence of the criteria and attributes has been exerted by testing a group of experts using a questionnaire (the AHP questionnaire). The obtained values are fuzzificated in triangular fuzzy numbers. The processing of the gathered data - triangular fuzzy numbers and the prioritization of the criteria and attributes has been carried out by the AHP method. The consistency of the results has been tested by the ratio of consistency. On the basis of the results, the model that enables the selection of optimal radar for the air traffic control and protection has been proposed

Selection of industrial robots using the Polygons area method

Selection of robots from the several proposed alternatives is a very important and tedious task. Decision makers are not limited to one method and several methods have been proposed for solving this problem. This study presents Polygons Area Method (PAM) as a multi attribute decision making method for robot selection problem. In this method, the maximum polygons area obtained from the attributes of an alternative robot on the radar chart is introduced as a decision-making criterion. The results of this method are compared with other typical multiple attribute decision-making methods (SAW, WPM, TOPSIS, and VIKOR) by giving two examples. To find similarity in ranking given by different methods, Spearman’s rank correlation coefficients are obtained for different pairs of MADM methods. It was observed that the introduced method is in good agreement with other well-known MADM methods in the robot selection problem

Identifying and Prioritising Future Robot Control Research with Multi-Criteria Decision-Making

The gap between researchers who carry out scientific exploration and practitioners who can make use of the research results is well known. In addition, while practitioners place a high value on research, they do not read many research papers. This paper attempts to define and prioritise future research in robotics using the analytical hierarchy process (AHP). Fifteen research alternatives and gaps, five performance criteria, eight industry types, and six production processes, investigated by both academics and practitioners, are filtered to six alternatives, four performance criteria, three industry types, and three production processes, respectively, based on the most important factors in decision-making. Subsequently, they are analysed by the Expert Choice software. This research aims at bridging the gap between academics and practitioners in robotics research and at conducting research that is relevant to industry. The results indicate that the research in multi-robot control ranked first with 26.8%, followed by the research in safe control with 23.3% and the research in remote robot supervision with 19.0%. The research in force control ranked fourth with 17.8%, followed by the research in 3D vision and wireless communication with 8.4% and 6.4%, respectively. Based on the results, the academics involved in robotics research should direct their effort to the research activities that received the highest priority in the AHP model

Selection of Projects for Project Portfolio Using Fuzzy TOPSIS and Machine Learning

Project portfolio management (PPM) is extremely important nowadays due to the increasing severe competitions, accelerated product developments, project complexity, uncertainty, and challenges from global competitors. Therefore, businesses involved in many (dozens or even hundreds) projects need to formulate tactics and strategies to secure firms’ competencies and, most importantly, increase their productivities. Under this globalization context, PPM is to opti-mize the value provided to the customers while minimizing risks and the resources committed to the projects, while critical success factors (CSFs) is applied to anticipate the project’s risk and financial value by early assessment thus to help from the organizational level to predict the per-formance. Despite its importance, the literature on PPM and CSFs at a project level is rather limited, which demands a more profound knowledge about the assessment, ranking, and prior-itization of projects in the early stage. This study seeks to address the following two research questions: Do CSFs vary according to the project category, and how a supportive method can be established to help portfolio managers to select the project for portfolio. As a result, this re-search focuses on the multi-project context in order to fill the above-mentioned research gaps. As the contributions of this study, this study intends to (1) verify the hypothesis that different project category has different CSFs, and (2) contribute to explore how machine learning technol-ogy can be utilized for project selection. Projektisalkun hallinta (PPM) on nykyään erittäin tärkeää lisääntyvien kovien kilpailujen, nopeutuneen tuotekehityksen, projektien monimutkaisuuden, epävarmuuden ja globaalien kilpailijoiden haasteiden vuoksi. Siksi moniin (kymmeniin tai jopa satoihin) hankkeisiin osallistuvien yritysten on laadittava taktiikat ja strategiat, joilla varmistetaan yritysten osaaminen ja mikä tärkeintä, lisää tuottavuuttaan. Tässä globalisaatiokehyksessä PPM: n on optimoitava asiakkaille tarjottu arvo minimoiden riskit ja hankkeisiin sitoutuvat resurssit, kun taas kriittisiä menestystekijöitä (CSF) käytetään ennakoimaan projektin riski ja taloudellinen arvo varhaisella arvioinnilla, jotta apua organisaatiotasolta suorituskyvyn ennustamiseksi. Tärkeydestään huolimatta kirjallisuus PPM: stä ja CSF: stä projektitasolla on melko rajallinen, mikä vaatii syvällisempää tietoa hankkeiden arvioinnista, luokittelusta ja ennakoinnista varhaisessa vaiheessa. Tässä tutkimuksessa pyritään käsittelemään kahta seuraavaa tutkimuskysymystä: vaihtelevatko CSF: t projektikategorian mukaan ja kuinka voidaan luoda tukeva menetelmä salkunhoitajien auttamiseksi valitsemaan projekti salkkuun. Tämän seurauksena tämä uudelleenhaku keskittyy moniprojektiyhteyteen edellä mainittujen tutkimuksen aukkojen täyttämiseksi. Tämän tutkimuksen myötä tämän tutkimuksen tarkoituksena on (1) tarkistaa hypoteesi, että eri projektikategorioilla on erilaiset CSF: t, ja (2) myötävaikuttaa siihen, kuinka koneoppimisen tekniikkaa voidaan hyödyntää projektin valinnassa

An integrated model for supplier evaluation in supply chains

U ovom radu predložen je model za vrednovanje i izbor dobavljača koji je razmatran u više od deset različitih proizvodnih oblasti. Model se sastoji od dvadeset kvantitavnih i kvalitativnih kriterijuma koji su primenom fuzzy AHP (Analitičko Hijerarhijski Proces) metode, a na osnovu ocenjivanja menadžera proizvodnih kompanija smanjeni na ukupno devet. Verifikacija datog modela predstavljena je kroz vrednovanje i izbor dobavljača u tri kompanije koje se bave različitom delatnošću. Pored doprinosa koji se ogleda u primenjivosti razvijenog modela u različitim lancima snabdevanja, veliki doprinos ovog rada je razvoj novih pristupa u oblasti višekriterijumskog odlučivanja koji može biti primenjen u svim lancima snabdevanja, naročito u procesima u kojima vladaju neizvesnosti i nejasnoće što je detaljno objašnjeno kroz rad.In this paper, a model for evaluation and supplier selection has been proposed, which has been considered in more than ten different production areas. The model consists of twenty quantitative and qualitative criteria which are reduced to a total of nine by the application of the fuzzy AHP (Analytic Hierarchy Process) method and the assessment of managers in production companies. The verification of the given model is presented through the evaluation and supplier selection in three companies that deal with different activities. In addition to the contribution reflected in the applicability of the developed model in various supply chains, the great contribution of this paper is the development of new approaches in the field of multi-criteria decision making that can be applied in all supply chains, especially in processes that are subject to uncertainty and vagueness, which is explained in detail through the work

The modeling of the risk factors at workplaces in production processes with a predominantly female labor force

Zaštita zdravlja i bezbednosti na radu pripada multidisciplinarnoj oblasti, koja osim proučavanja tehničkih faktora i karakteristika radne okoline, teži i razvoju nivoa svesti zaposlenih i povećanju odgovornosti svih subjekata u oblasti bezbednosti na radu. Protekle decenije karakterišu stalna ispitivanja i identifikovanja metoda i mera u cilju poboljšanja uslova rada. U vezi s tim postavljeni cilj u okviru ove disertacije je formiranje modela bezbednosti i definisanje faktora rizika na radnim mestima, u proizvodnim procesima sa pretežno ženskom radnom snagom. Počevši od analize dosadašnjih istraživanja u oblasti bezbednosti na radu, kroz praktičnu analizu karakterističnih uticajnih faktora radne okoline, određene su poziciji na kojima su zaposlene žene u procesu rada izložene štetnim uticajima radne okoline i gde je njihovo zdravlje najviše ugroženo. Na osnovu analiziranih podataka u daljem toku istraživanja utvrđeni su najznačajniji uticajni faktori bezbednosti na radu, primenom višekriterijumskih metoda. Istraživanje u ovoj disertaciji je rezultovalo razvojem modela klime bezbednosti na radu koji se može koristiti za identifikovanje najuticajnijih faktora rizika na radnim mestima, koji svojim direktnim ili indirektnim uticajem mogu biti indikatori bezbednosti zaposlenih. Iz izvršenih analiza stavova zaposlenih u sistemu menadžmenta bezbednosti i zdravlja na radu utvrđeni su uticajni faktori klime bezbednosti koji mogu služiti za procenu stanja bezbednosti na radu u proizvodnim organizacijama sa pretežno ženskom radnom snagom. Na osnovu dobijenih rezultata utvrđeno je da je „Modelovanje faktora rizika na radnim mestima u proizvodnim procesima sa pretežno ženskom radnom snagom“ moguće sprovesti primenjujući predstavljene metode u ovom radu.Occupational health i safety at work belongs to the multidisciplinary field, which, apart from studying the technical factors i characteristics of the working environment, aims at developing the level of employee awareness i increasing the responsibility of all subjects, in the field of occupational safety. The last decades have been marked by continuous research i development of many methods i measures in order to improve the working conditions. Therefore, the aimed of this dissertation is to develop the safety climate model at workplace i to define the risk factors at workplaces, in manufacturing processes with predominantly female labor force. Starting from the analysis of previous work safety surveys, through practical analysis of the influencing factors of the working environment, has been determined the positions in production processes where women are mostly at risk in the work process. In the further course of the research, the most important influential factors of safety at work were determined using multicriterial methods. The research in this dissertation resulted in the development of an occupational safety model that can be used to determine the most influential factors of the risks in the workplaces, which by their direct or indirect impact can be indicators of the safety of employees. From the conducted analyzes of the attitudes of responsible people in the occupational health i safety management system they were determined influential factors of the safety climate that can serve to evaluate the occupational safety in production organizations. Finally, it has been concluded that "The modeling of the risk factors at workplaces in manufacturing processes with predominantly female labor" can be implemented using the presented methods

Models for supporting development of mobility in line with the sharing economy concept : doctoral dissertation

Предмет истраживања ове докторске дисертације су концепти дељења вожње и дељења возила, при чему је акценат на истраживању могућности економичнијег коришћењa путничког аутомобила, кроз услуге carsharing и carpooling. Полазећи од тога да ове опције мобилности, као и економију дељења уопште, покрећу пре свега сами корисници циљ дисертације је да се истраживањем корисничких захтева, ставова и степена поверења, изграде модели за подршку одлучивању и ширу имплементацију дељења мобилности. Поред модела који има за циљ утврђивање потенцијала за промену образаца мобилности у градовима/подручјима на бази утврђеног скупа индикатора, у дисертацији је развијен и оригинални модел који служи за предвиђање потражње за услугама дељења мобилности на бази понашања корисника, али и на бази њихових међусобних интеракција, као и модел који врши вредновање мера које подстичу концепт дељења вожње. Модел предвиђања потражње за опцијама дељења мобилности има за циљ да утврди како понашање корисника, али и њихове међусобне интеракције, утичу на опредељење за коришћење услуге carsharing-а. Овај модел полази од претпоставке да су за одлуку о коришћењу carsharing-а, на тржиштима где услуга није успостављена, важне интеракције и размена искустава везаних за услуге економије дељења, као и поверење које корисник стиче коришћењем других услуга економије дељења. Модел омогућава предвиђање потражње (на бази кључних атрибута корисника) и момента засићења тржишта carsharing услуга. Додатно, кроз анализу осетљивости на промене улазних параметара, могуће је пратити промене потражње за carsharing услугама у односу на промене услова понуде.The research subject of this doctoral dissertation are the concepts of ride sharing and vehicle sharing, with an emphasis on exploring the possibility of economical use of a passenger car through carsharing and carpooling services. Given that these mobility options, as well as sharing economy in general, are driven primarily by users themselves, the aim of the dissertation is to develop decision support models for broad implementation of shared mobility, by researching user requirements, attitudes and levels of trust. In addition to the indicator-based model for appraisal potentials for changing mobility patterns in cities/areas, an original model for shared mobility demand prediction based on users behavior and their mutual interactions is developed. Besides, the model that evaluates incentive measures for ride sharing is developed. The demand forecasting model for shared mobility services aims to determine how users behavior and their mutual interactions affect the decision to join carsharing program. The model is based on the assumption that where carsharing has not yet been established, interactions and exchange of experiences related to sharing economy, as well as trust that users acquire using other sharing economy services, have a great impact on their decision for carsharing. The outcomes are demand prediction (based on user attributes) and expected saturations on the market In addition, sensitivity analysis enables to monitor interdependences between supply and demand side of the carsharing market. Respecting requirements and motives of employees for joining company-based carpooling, a model for evaluating those company incentives that would encourage broad implementation of ride sharing is developed. A special procedure is built to iv determine the overall impact of each company's action on the demands of its employees. As a result, the company's management can, according to the available resources, identify those actions that could run the largest wave of carpoolers

Studies on Risk and Occupational Health Hazards in Industrial Context: Some Case Research

This work articulates few case empirical studies on some aspects of risk management and occupational health hazards in the context of Indian Industries. Empirical research is research using empirical evidence. It is a way of gaining knowledge by means of direct and indirect observation or experience. The study focuses on five important domains investigating (i) the interrelationships among critical risk factors associated with software engineering project, (ii) risk management for IT outsourcing, (iii) risk management in metropolitan construction project, (iv) health hazard risk management, and (v) appropriate safety measure system selection for improving workers’ safety in an underground coal mining industry. In this research, an ISM approach has been applied to understand the significant interrelationships among the twenty three identified risk factors associated with the software engineering projects. In relation to IT outsourcing project, a hierarchical risk-breakdown structure has been proposed comprising sixty eight risk influencing factors under eleven risk dimensions. A case study has been conducted in a famous IT sector located at the eastern part of India. An improved fuzzy based decision making approach has been proposed for assessing overall IT outsourcing project risks. The degree of risk of identified risk factors have been shown in crisp values rather than the fuzzy numbers. A logical risk categorization framework has been proposed to categorize the risk factors into different risk levels. A unique action requirement plan has been suggested for effectively controlling the risks towards IT outsourcing project success. In the later part, total twenty one occupational health hazards have been identified and assessed their risk extent based on the exposure assessment procedure. Consequently, a constructive control measure plan has been suggested for different health hazards in view of their risk extent level. A novel risk-based decision making framework has been proposed for selecting the appropriate safety measure system in an underground coal mining industry. In addition to this, a case study has been conducted using twenty potential risk factors associated with five risk dimensions for assessing metropolitan construction project risks. Decision-makers’ risk bearing attitude has also been considered in this study. This study also explores the concept of risk matrix for categorizing the risk factors in different risk levels which would provide guidelines towards controlling risks for enhancing the overall project performance. Risk analysis models delignated herein have been case studied in relation to Indian industries. However, the model or hierarchy of various risk dimensions, risk sources; and classification of health hazards can be applicable to appropriate industries all over the globe. Some alteration may incur depending on the geographic situation of coal mining industry in analyzing occupational health hazards and associated risks. The framework for analyzing risks and occupational health hazards based on fuzzy based decision making approach can be applied in industrial context of different countries. Apart from the case studies mentioned above, the work also proposes a risk based decision support framework for selection of safety measure system for underground coal mines. In this case, occupational risks and alternative safety measure systems have been identified through literature survey. This part is a purely a theoretical formulation followed by analysis of assumed data which has not been case studied in reality. The novelty of the proposed framework is to analyze various risk dimensions in software engineering projects, IT Outsourcing, construction projects; also occupational health hazards in underground coal mining industry in a fuzzy based decision making framework. Instead of exploring historical data, survey report of the company; an experienced decision making group has been appointed to provide subjective judgement in regards of likelihood of occurrence and impact of various risks; consequence of exposure, period of exposure, and probability of exposure of various health hazards. Subjective decision making data have been transformed into appropriate fuzzy number sets to quantify overall risks extent. Thus, the proposed framework provides a platform to quantify extent of risk in industrial context

Supply Chain Performance Appraisement and Benchmarking for Manufacturing Industries: Emphasis on Traditional, Green, Flexible and Resilient Supply Chain along with Supplier Selection

Supply chain represents a network of interconnected activities starting from raw material extraction to delivery of the finished product to the end-user. The main constituents of supply chain are supplying/purchasing, inbound logistics, manufacturing, outbound logistics, marketing and sales. In recent times, the traditional supply chain construct is being modified to embrace various challenges of present business needs. Today’s global market has become highly volatile; customers’ expectations are ever-changing. Fierce competition amongst business sectors necessitates adapting modern supply chain management philosophies. Agility, greenness, flexibility as well as resilience have become the key success factors in satisfying global business needs. In order to remain competitive in the turbulent marketplace, industries should focus on improving overall performance of the supply chain network. In this dissertation, supply chain performance assessment has been considered as a decision making problem involving various measures and metrics (performance indicators). Since most of the performance indices are subjective in nature; decisionmaking relies on active participation of a group of decision-makers (DMs). Subjective human judgment often bears some sort of ambiguity as well as vagueness in the decision making; to overcome uncertainty in decision making, adaptation of grey/fuzzy set theory seems to be fruitful. To this end, present work deals with a variety of decision support tools to facilitate supply chain performance appraisement as well as benchmarking in fuzzy/grey context. Starting from the traditional supply chain, this work extends appraisement and benchmarking of green supply chain performance for a set of candidate case companies (under the same industry) operating under similar supply chain construct. Exploration of grey-MOORA, fuzzy-MOORA, IVFN-TOPSIS, fuzzy-grey relation method has been illustrated in this part of work. Apart from aforementioned empirical studies, two real case studies have been reported in order to estimate a quantitative performance metric reflecting the extent of supply chain flexibility and resilience, respectively, in relation to the case company under consideration. Performance benchmarking helps in identifying best practices in perspectives of supply chain networking; it can easily be transmitted to other industries. Organizations can follow their peers in order to improve overall performance of the supply chain. vi Supplier selection is considered as an important aspect in supply chain management. Effective supplier selection must be a key strategic consideration towards improving supply chain performance. However, the task of supplier selection seems difficult due to subjectivity of supplier performance indices. Apart from considering traditional supplier selection criteria (cost, quality and service); global business scenario encourages emphasizing various issues like environmental performance (green concerns), resiliency etc. into evaluation and selection of an appropriate supplier. In this context, the present work also attempts to explore fuzzy based decision support systems towards evaluation and selection of potential suppliers in green supply chain as well as resilient supply chain, respectively. Fuzzy based Multi-Level Multi-Criteria Decision Making (MLMCDM) approach, fuzzy-TOPSIS and fuzzy-VIKOR have been utilized to facilitate the said decision making

Supply Chain Performance Appraisement and Benchmarking for Manufacturing Industries: Emphasis on Traditional, Green, Flexible and Resilient Supply Chain along with Supplier Selection

Supply chain represents a network of interconnected activities starting from raw material extraction to delivery of the finished product to the end-user. The main constituents of supply chain are supplying/purchasing, inbound logistics, manufacturing, outbound logistics, marketing and sales. In recent times, the traditional supply chain construct is being modified to embrace various challenges of present business needs. Today’s global market has become highly volatile; customers’ expectations are ever-changing. Fierce competition amongst business sectors necessitates adapting modern supply chain management philosophies. Agility, greenness, flexibility as well as resilience have become the key success factors in satisfying global business needs. In order to remain competitive in the turbulent marketplace, industries should focus on improving overall performance of the supply chain network. In this dissertation, supply chain performance assessment has been considered as a decision making problem involving various measures and metrics (performance indicators). Since most of the performance indices are subjective in nature; decisionmaking relies on active participation of a group of decision-makers (DMs). Subjective human judgment often bears some sort of ambiguity as well as vagueness in the decision making; to overcome uncertainty in decision making, adaptation of grey/fuzzy set theory seems to be fruitful. To this end, present work deals with a variety of decision support tools to facilitate supply chain performance appraisement as well as benchmarking in fuzzy/grey context. Starting from the traditional supply chain, this work extends appraisement and benchmarking of green supply chain performance for a set of candidate case companies (under the same industry) operating under similar supply chain construct. Exploration of grey-MOORA, fuzzy-MOORA, IVFN-TOPSIS, fuzzy-grey relation method has been illustrated in this part of work. Apart from aforementioned empirical studies, two real case studies have been reported in order to estimate a quantitative performance metric reflecting the extent of supply chain flexibility and resilience, respectively, in relation to the case company under consideration. Performance benchmarking helps in identifying best practices in perspectives of supply chain networking; it can easily be transmitted to other industries. Organizations can follow their peers in order to improve overall performance of the supply chain. vi Supplier selection is considered as an important aspect in supply chain management. Effective supplier selection must be a key strategic consideration towards improving supply chain performance. However, the task of supplier selection seems difficult due to subjectivity of supplier performance indices. Apart from considering traditional supplier selection criteria (cost, quality and service); global business scenario encourages emphasizing various issues like environmental performance (green concerns), resiliency etc. into evaluation and selection of an appropriate supplier. In this context, the present work also attempts to explore fuzzy based decision support systems towards evaluation and selection of potential suppliers in green supply chain as well as resilient supply chain, respectively. Fuzzy based Multi-Level Multi-Criteria Decision Making (MLMCDM) approach, fuzzy-TOPSIS and fuzzy-VIKOR have been utilized to facilitate the said decision making