Using Pythagorean Fuzzy Sets (PFS) in Multiple Criteria Group Decision Making (MCGDM) Methods for Engineering Materials Selection Applications

The process of materials’ selection is very critical during the initial stages of designing manufactured products. Inefficient decision-making outcomes in the material selection process could result in poor quality of products and unnecessary costs. In the last century, numerous materials have been developed for manufacturing mechanical components in different industries. Many of these new materials are similar in their properties and performances, thus creating great challenges for designers and engineers to make accurate selections. Our main objective in this work is to assist decision makers (DMs) within the manufacturing field to evaluate materials alternatives and to select the best alternative for specific manufacturing purposes. In this research, new hybrid fuzzy Multiple Criteria Group Decision Making (MCGDM) methods are proposed for the material selection problem. The proposed methods tackle some challenges that are associated with the material selection decision making process, such as aggregating decision makers’ (DMs) decisions appropriately and modeling uncertainty. In the proposed hybrid models, a novel aggregation approach is developed to convert DMs crisp decisions to Pythagorean fuzzy sets (PFS). This approach gives more flexibility to DMs to express their opinions than the traditional fuzzy and intuitionistic sets (IFS). Then, the proposed aggregation approach is integrated with a ranking method to solve the Pythagorean Fuzzy Multi Criteria Decision Making (PFMCGDM) problem and rank the material alternatives. The ranking methods used in the hybrid models are the Pythagorean Fuzzy TOPSIS (The Technique for Order of Preference by Similarity to Ideal Solution) and Pythagorean Fuzzy COPRAS (COmplex PRoportional Assessment). TOPSIS and COPRAS are selected based on their effectiveness and practicality in dealing with the nature of material selection problems. In the aggregation approach, the Sugeno Fuzzy measure and the Shapley value are used to fairly distribute the DMs weight in the Pythagorean Fuzzy numbers. Additionally, new functions to calculate uncertainty from DMs recommendations are developed using the Takagai-Sugeno approach. The literature reveals some work on these methods, but to our knowledge, there are no published works that integrate the proposed aggregation approach with the selected MCDM ranking methods under the Pythagorean Fuzzy environment for the use in materials selection problems. Furthermore, the proposed methods might be applied, due to its novelty, to any MCDM problem in other areas. A practical validation of the proposed hybrid PFMCGDM methods is investigated through conducting a case study of material selection for high pressure turbine blades in jet engines. The main objectives of the case study were: 1) to investigate the new developed aggregation approach in converting real DMs crisp decisions into Pythagorean fuzzy numbers; 2) to test the applicability of both the hybrid PFMCGDM TOPSIS and the hybrid PFMCGDM COPRAS methods in the field of material selection. In this case study, a group of five DMs, faculty members and graduate students, from the Materials Science and Engineering Department at the University of Wisconsin-Milwaukee, were selected to participate as DMs. Their evaluations fulfilled the first objective of the case study. A computer application for material selection was developed to assist designers and engineers in real life problems. A comparative analysis was performed to compare the results of both hybrid MCGDM methods. A sensitivity analysis was conducted to show the robustness and reliability of the outcomes obtained from both methods. It is concluded that using the proposed hybrid PFMCGDM TOPSIS method is more effective and practical in the material selection process than the proposed hybrid PFMCGDM COPRAS method. Additionally, recommendations for further research are suggested

A fuzzy logic micro-controller enabled system for the monitoring of micro climatic parameters of a greenhouse

Motivation behind this master dissertation is to introduce a novel study called " A fuzzy logic micro-controller enabled system for the monitoring of micro-climatic parameters of a greenhouse" which is capable of intelligently monitoring and controlling the greenhouse climate conditions in a preprogrammed manner. The proposed system consists of three stations: Sensor Station, Coordinator Station, and Central Station. To allow for better monitoring of the climate condition in the greenhouse, fuzzy logic controller is embedded in the system as the system becomes more intelligent with fuzzy decision making. The sensor station is equipped with several sensor elements such as MQ-7 (Carbon monoxide sensor), DHT11 (Temperature and humidity sensor), LDR (light sensor), grove moisture sensor (soil moisture sensor). The communication between the sensor station and the coordinator station is achieved through XBee wireless modules connected to the Arduino Mega and the communication between coordinator station and the central station is also achieved via XBee wireless modules connected to the Arduino Mega. The experiments and tests of the system were carried out at one of IKHALA TVET COLLEGE’s greenhouses that is used for learning purposes by students studying agriculture at the college. The purpose of conducting the experiments at the college’s green house was to determine the functionality and reliability of the designed wireless sensor network using ZigBee wireless technology. The experiment result indicated that XBee modules could be used as one solution to lower the installation cost, increase flexibility and reliability and create a greenhouse management system that is only based on wireless nodes. The experiment result also showed that the system became more intelligent if fuzzy logic was used by the system for decision making. The overall system design showed advantages in cost, size, power, flexibility and intelligence. It is trusted that the results of the project will give the chance for further research and development of a low cost greenhouse monitoring system for commercial use.Electrical and Mining EngineeringM. Tech. (Electrical Engineering

Automation and computer integrated manufacturing in food processing industry: an appraisal

This study is concerned with a research programme on automation and computer integrated manufacturing (CIM) in food processing industry, culminating in an implementation framework detailing the extent of automation and application of computer based technologies in Irish food processing industries. This work involved with designing of a postal survey questionnaire and mailing it to 221 manufacturing companies, and designing a web-based survey and emailing it to 31 manufacturing companies in the Republic of Ireland. Questions were designed to capture information about the level of automation, envisaged level of automation, motivation and obstacles to implement computer-based technology, and the extent of implementation of CIM environments at plants. The key findings point to the existence of a linear relationship between practice and performance. From the perspective of competitive advantage, the traditional postal survey gives a higher response rate than web-based survey, but on the other hand the web based survey takes shorter response time and cost s less than a traditional postal survey. The results of this study show variable levels of automation. A large number of the manufacturing plants are applying automation, and are trying to increase the automation level m their plants. This work has demonstrated that the manufacturers have the desire to adopt CIM systems at different levels, despite the cost obstacle of implementing them

Production planning mechanisms in demand-driven wood remanufacturing industry

L'objectif principal de cette thèse est d'étudier le problème de planification de la production dans le contexte d'une demande incertaine, d’un niveau de service variable et d’approvisionnements incontrôlables dans une usine de seconde transformation du bois. Les activités de planification et de contrôle de production sont des tâches intrinsèquement complexes et difficiles pour les entreprises de seconde transformation du bois. La complexité vient de certaines caractéristiques intrinsèques de cette industrie, comme la co-production, les procédés alternatifs divergents, les systèmes de production sur commande (make-to-order), des temps de setup variables et une offre incontrôlable. La première partie de cette thèse propose une plate-forme d'optimisation/simulation permettant de prendre des décisions concernant le choix d'une politique de planification de la production, pour traiter rapidement les demandes incertaines, tout en tenant compte des caractéristiques complexes de l'industrie de la seconde transformation du bois. À cet effet, une stratégie de re-planification périodique basée sur un horizon roulant est utilisée et validée par un modèle de simulation utilisant des données réelles provenant d'un partenaire industriel. Dans la deuxième partie de cette thèse, une méthode de gestion des stocks de sécurité dynamique est proposée afin de mieux gérer le niveau de service, qui est contraint par une capacité de production limitée et à la complexité de la gestion des temps de mise en course. Nous avons ainsi développé une approche de re-planification périodique à deux phases, dans laquelle des capacités non-utilisées (dans la première phase) sont attribuées (dans la seconde phase) afin de produire certains produits jugés importants, augmentant ainsi la capacité du système à atteindre le niveau de stock de sécurité. Enfin, dans la troisième partie de la thèse, nous étudions l’impact d’un approvisionnement incontrôlable sur la planification de la production. Différents scénarios d'approvisionnement servent à identifier les seuils critiques dans les variations de l’offre. Le cadre proposé permet aux gestionnaires de comprendre l'impact de politiques d'approvisionnement proposées pour faire face aux incertitudes. Les résultats obtenus à travers les études de cas considérés montrent que les nouvelles approches proposées dans cette thèse constituent des outils pratiques et efficaces pour la planification de production du bois.The main objective of this thesis is to investigate the production planning problem in the context of uncertain demand, variable service level, and uncontrollable supply in a wood remanufacturing mill. Production planning and control activities are complex and represent difficult tasks for wood remanufacturers. The complexity comes from inherent characteristics of the industry such as divergent co-production, alternative processes, make-to-order, short customer lead times, variable setup time, and uncontrollable supply. The first part of this thesis proposes an optimization/simulation platform to make decisions about the selection of a production planning policy to deal swiftly with uncertain demands, under the complex characteristics of the wood remanufacturing industry. For this purpose, a periodic re-planning strategy based on a rolling horizon was used and validated through a simulation model using real data from an industrial partner. The computational results highlighted the significance of using the re-planning model as a practical tool for production planning under unstable demands. In the second part, a dynamic safety stock method was proposed to better manage service level, which was threatened by issues related to limited production capacity and the complexity of setup time. We developed a two-phase periodic re-planning approach whereby idle capacities were allocated to produce more important products thus increasing the realization of safety stock level. Numerical results indicated that the solution of the two-phase method was superior to the initial method in terms of backorder level as well as inventory level. Finally, we studied the impact of uncontrollable supply on demand-driven wood remanufacturing production planning through an optimization and simulation framework. Different supply scenarios were used to identify the safety threshold of supply changes. The proposed framework provided managers with a novel advanced planning approach that allowed understanding the impact of supply policies to deal with uncertainties. In general, the wood products industry offers a rich environment for dealing with uncertainties for which the literature fails to provide efficient solutions. Regarding the results that were obtained through the case studies, we believe that approaches proposed in this thesis can be considered as novel and practical tools for wood remanufacturing production planning

SHMD \u272024 – Book of abstracts

Book of abstracts of the 17th International Symposium of the Croatian Metallurgical Society - SHMD \u272024 - Materials and metallurgy, Zagreb, Croatia, April 18-19 2024

Sustainable Supply Chain Management

The book is a collection of studies dedicated to different perspectives of three dimensions or pillars of the sustainability of supply chain and supply chain management - economic, environmental, and social - and other aspects related to performance evaluation, optimization, and modelling of and for sustainable supply chain management, and thus presents another valuable contribution to sustainable development and sustainable way of life

Proceeding Of Mechanical Engineering Research Day 2016 (MERD’16)

This Open Access e-Proceeding contains a compilation of 105 selected papers from the Mechanical Engineering Research Day 2016 (MERD’16) event, which is held in Kampus Teknologi, Universiti Teknikal Malaysia Melaka (UTeM) - Melaka, Malaysia, on 31 March 2016. The theme chosen for this event is ‘IDEA. INSPIRE. INNOVATE’. It was gratifying to all of us when the response for MERD’16 is overwhelming as the technical committees received more than 200 submissions from various areas of mechanical engineering. After a peer-review process, the editors have accepted 105 papers for the e-proceeding that cover 7 main themes. This open access e-Proceeding can be viewed or downloaded at www3.utem.edu.my/care/proceedings. We hope that these proceeding will serve as a valuable reference for researchers. With the large number of submissions from the researchers in other faculties, the event has achieved its main objective which is to bring together educators, researchers and practitioners to share their findings and perhaps sustaining the research culture in the university. The topics of MERD’16 are based on a combination of fundamental researches, advanced research methodologies and application technologies. As the editor-in-chief, we would like to express our gratitude to the editorial board and fellow review members for their tireless effort in compiling and reviewing the selected papers for this proceeding. We would also like to extend our great appreciation to the members of the Publication Committee and Secretariat for their excellent cooperation in preparing the proceeding of MERD’16

Multi-Objective and Multi-Attribute Optimisation for Sustainable Development Decision Aiding

Optimization is considered as a decision-making process for getting the most out of available resources for the best attainable results. Many real-world problems are multi-objective or multi-attribute problems that naturally involve several competing objectives that need to be optimized simultaneously, while respecting some constraints or involving selection among feasible discrete alternatives. In this Reprint of the Special Issue, 19 research papers co-authored by 88 researchers from 14 different countries explore aspects of multi-objective or multi-attribute modeling and optimization in crisp or uncertain environments by suggesting multiple-attribute decision-making (MADM) and multi-objective decision-making (MODM) approaches. The papers elaborate upon the approaches of state-of-the-art case studies in selected areas of applications related to sustainable development decision aiding in engineering and management, including construction, transportation, infrastructure development, production, and organization management