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This book covers the area of unpaced, unbalanced production lines. You will find an up-to-date discussion of how designing these lines can be made more efficient by taking advantage of inherent imbalance--for example, operators who work at different speeds--a concept that has traditionally been seen as an obstacle to efficient production. A series of experiments are presented to illustrate the issues involved in improving performance through production line imbalance. This is of interest to postgraduate and executive-level students interested in the area of production, and to managers of manual or semi-automated production lines who are interested in innovative approaches to line design. In this book you will find some surprisingly easy ways to improve performance with low or zero costs. Emphasis is placed on reducing the amount of time production lines lie idle, and on reducing work in process. This is a timely contribution to the field when managers are casting around for new ways to cut waste and reduce their use of natural resources.
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L’entreprise Eloy Water basée à Sprimont en Belgique conçoit, fabrique et commercialise des solutions de traitement d’eaux usées et de récupération d’eau. En 2016, elle lance un filtre compact révolutionnaire : Le X-Perco. Depuis sa mise sur le marché, les ventes de ce produit ne cessent d’augmenter, au point d’atteindre la capacité de production maximale de l’usine. Ce travail de fin d’étude décrit et analyse le projet de réorganisation de la production dans les halls de fabrication des cuves en béton de grande taille. Cela se traduit tout d’abord par l’analyse du contexte de l’entreprise et la définition des objectifs du projet. Pour atteindre ces objectifs, une nouvelle ligne de production sera développée : ses caractéristiques techniques, l’organisation du travail qui y sera appliquée, sa rentabilité ainsi que les impacts transversaux de cette réorganisation seront étudiés Enfin, la méthode de gestion du changement de ce projet sera analysée sous le prisme de la théorie de l’acteur-réseau.
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Assembly-line balancing. --- Uncertainty (Information theory) --- Balancing of assembly-lines --- Line balancing (Assembly-lines) --- Measure of uncertainty (Information theory) --- Shannon's measure of uncertainty --- System uncertainty --- Information measurement --- Probabilities --- Questions and answers
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This book introduces several mathematical models in assembly line balancing based on stochastic programming and develops exact and heuristic methods to solve them. An assembly line system is a manufacturing process in which parts are added in sequence from workstation to workstation until the final assembly is produced. In an assembly line balancing problem, tasks belonging to different product models are allocated to workstations according to their processing times and precedence relationships among tasks. It incorporates two features, uncertain task times, and demand volatility, separately and simultaneously, into the conventional assembly line balancing model. A real-life case study related to the mask production during the COVID-19 pandemic is presented to illustrate the application of the proposed framework and methodology. The book is intended for graduate students who are interested in combinatorial optimizations in manufacturing with uncertain input.
Methodology of economics --- Numerical methods of optimisation --- Operational research. Game theory --- Mathematics --- Engineering sciences. Technology --- Planning (firm) --- Production management --- Business management --- Business economics --- Computer. Automation --- financieel management --- automatisering --- mathematische modellen --- productie --- wiskunde --- ingenieurswetenschappen --- Assembly-line balancing. --- Models matemàtics --- Optimització matemàtica --- Enginyeria de producció
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Models matemàtics --- Optimització matemàtica --- Enginyeria de producció --- Enginyeria dels procediments --- Tècnica de la producció --- Enginyeria industrial --- Enginyeria mecànica --- Fabricació --- Sistemes de producció flexibles --- Mètodes de simulació --- Jocs d'estratègia (Matemàtica) --- Optimització combinatòria --- Programació dinàmica --- Programació (Matemàtica) --- Anàlisi de sistemes --- Models (Matemàtica) --- Models experimentals --- Models teòrics --- Mètode de Montecarlo --- Modelització multiescala --- Models economètrics --- Models lineals (Estadística) --- Models multinivell (Estadística) --- Models no lineals (Estadística) --- Programació (Ordinadors) --- Simulació per ordinador --- Teoria de màquines --- Models biològics --- Assembly-line balancing. --- Balancing of assembly-lines --- Line balancing (Assembly-lines)
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This book was established after the 6th International Workshop on Numerical and Evolutionary Optimization (NEO), representing a collection of papers on the intersection of the two research areas covered at this workshop: numerical optimization and evolutionary search techniques. While focusing on the design of fast and reliable methods lying across these two paradigms, the resulting techniques are strongly applicable to a broad class of real-world problems, such as pattern recognition, routing, energy, lines of production, prediction, and modeling, among others. This volume is intended to serve as a useful reference for mathematicians, engineers, and computer scientists to explore current issues and solutions emerging from these mathematical and computational methods and their applications.
model predictive control --- bulbous bow --- improvement differential evolution algorithm --- evolutionary multi-objective optimization --- location routing problem --- flexible job shop scheduling problem --- basic differential evolution algorithm --- metric measure spaces --- NEAT --- genetic algorithm --- multiobjective optimization --- improved differential evolution algorithm --- performance indicator --- rubber --- averaged Hausdorff distance --- mixture experiments --- U-shaped assembly line balancing --- Genetic Programming --- Local Search --- driving events --- surrogate-based optimization --- single component constraints --- crop planning --- Pareto front --- numerical simulations --- shape morphing --- genetic programming --- economic crops --- local search and jump search --- model order reduction --- optimal solutions --- EvoSpace --- risky driving --- intelligent transportation systems --- optimal control --- IV-optimality criterion --- Bloat --- decision space diversity --- modify differential evolution algorithm --- power means --- driving scoring functions --- open-source framework --- evolutionary computation --- differential evolution algorithm --- vehicle routing problem --- multi-objective optimization
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This book, as a Special Issue, is a collection of some of the latest advancements in designing and scheduling smart manufacturing systems. The smart manufacturing concept is undoubtedly considered a paradigm shift in manufacturing technology. This conception is part of the Industry 4.0 strategy, or equivalent national policies, and brings new challenges and opportunities for the companies that are facing tough global competition. Industry 4.0 should not only be perceived as one of many possible strategies for manufacturing companies, but also as an important practice within organizations. The main focus of Industry 4.0 implementation is to combine production, information technology, and the internet. The presented Special Issue consists of ten research papers presenting the latest works in the field. The papers include various topics, which can be divided into three categories—(i) designing and scheduling manufacturing systems (seven articles), (ii) machining process optimization (two articles), (iii) digital insurance platforms (one article). Most of the mentioned research problems are solved in these articles by using genetic algorithms, the harmony search algorithm, the hybrid bat algorithm, the combined whale optimization algorithm, and other optimization and decision-making methods. The above-mentioned groups of articles are briefly described in this order in this book.
Technology: general issues --- History of engineering & technology --- flexible job-shop scheduling problem --- combinatorial optimization --- genetic algorithm --- candidate order-based genetic algorithm --- multichromosome --- facility layout --- optimization --- metaheuristic algorithm --- cell formation --- design of experiments --- digital platforms --- decision-making --- insurance --- Baltic --- customization --- personalization --- assembly line balancing --- group technology --- cluster algorithm --- bottleneck station --- output rate --- tolerance allocation --- machine and process selection --- heuristic approach --- univariate search method --- whale optimization algorithm --- selective assembly --- overrunning clutch assembly --- harmony search algorithm --- Hastelloy X --- turning --- cutting force --- surface roughness --- liquid nitrogen --- grass-hooper optimization algorithm --- moth-flame optimization algorithm --- hybrid bat algorithm --- optimization problem --- the distributed assembly permutation flowshop scheduling problem --- variable neighborhood descent --- multi-criteria assessment --- cell manufacturing design --- operational complexity --- makespan --- production line balancing rate --- electrochemical machining (ECM) --- material removal rate (MRR) --- nickel presence (NP) --- grey wolf optimizer (GWO) --- moth-flame optimization algorithm (MFO) --- Monel 400 alloys --- n/a
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This book, as a Special Issue, is a collection of some of the latest advancements in designing and scheduling smart manufacturing systems. The smart manufacturing concept is undoubtedly considered a paradigm shift in manufacturing technology. This conception is part of the Industry 4.0 strategy, or equivalent national policies, and brings new challenges and opportunities for the companies that are facing tough global competition. Industry 4.0 should not only be perceived as one of many possible strategies for manufacturing companies, but also as an important practice within organizations. The main focus of Industry 4.0 implementation is to combine production, information technology, and the internet. The presented Special Issue consists of ten research papers presenting the latest works in the field. The papers include various topics, which can be divided into three categories—(i) designing and scheduling manufacturing systems (seven articles), (ii) machining process optimization (two articles), (iii) digital insurance platforms (one article). Most of the mentioned research problems are solved in these articles by using genetic algorithms, the harmony search algorithm, the hybrid bat algorithm, the combined whale optimization algorithm, and other optimization and decision-making methods. The above-mentioned groups of articles are briefly described in this order in this book.
flexible job-shop scheduling problem --- combinatorial optimization --- genetic algorithm --- candidate order-based genetic algorithm --- multichromosome --- facility layout --- optimization --- metaheuristic algorithm --- cell formation --- design of experiments --- digital platforms --- decision-making --- insurance --- Baltic --- customization --- personalization --- assembly line balancing --- group technology --- cluster algorithm --- bottleneck station --- output rate --- tolerance allocation --- machine and process selection --- heuristic approach --- univariate search method --- whale optimization algorithm --- selective assembly --- overrunning clutch assembly --- harmony search algorithm --- Hastelloy X --- turning --- cutting force --- surface roughness --- liquid nitrogen --- grass-hooper optimization algorithm --- moth-flame optimization algorithm --- hybrid bat algorithm --- optimization problem --- the distributed assembly permutation flowshop scheduling problem --- variable neighborhood descent --- multi-criteria assessment --- cell manufacturing design --- operational complexity --- makespan --- production line balancing rate --- electrochemical machining (ECM) --- material removal rate (MRR) --- nickel presence (NP) --- grey wolf optimizer (GWO) --- moth-flame optimization algorithm (MFO) --- Monel 400 alloys --- n/a
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This book, as a Special Issue, is a collection of some of the latest advancements in designing and scheduling smart manufacturing systems. The smart manufacturing concept is undoubtedly considered a paradigm shift in manufacturing technology. This conception is part of the Industry 4.0 strategy, or equivalent national policies, and brings new challenges and opportunities for the companies that are facing tough global competition. Industry 4.0 should not only be perceived as one of many possible strategies for manufacturing companies, but also as an important practice within organizations. The main focus of Industry 4.0 implementation is to combine production, information technology, and the internet. The presented Special Issue consists of ten research papers presenting the latest works in the field. The papers include various topics, which can be divided into three categories—(i) designing and scheduling manufacturing systems (seven articles), (ii) machining process optimization (two articles), (iii) digital insurance platforms (one article). Most of the mentioned research problems are solved in these articles by using genetic algorithms, the harmony search algorithm, the hybrid bat algorithm, the combined whale optimization algorithm, and other optimization and decision-making methods. The above-mentioned groups of articles are briefly described in this order in this book.
Technology: general issues --- History of engineering & technology --- flexible job-shop scheduling problem --- combinatorial optimization --- genetic algorithm --- candidate order-based genetic algorithm --- multichromosome --- facility layout --- optimization --- metaheuristic algorithm --- cell formation --- design of experiments --- digital platforms --- decision-making --- insurance --- Baltic --- customization --- personalization --- assembly line balancing --- group technology --- cluster algorithm --- bottleneck station --- output rate --- tolerance allocation --- machine and process selection --- heuristic approach --- univariate search method --- whale optimization algorithm --- selective assembly --- overrunning clutch assembly --- harmony search algorithm --- Hastelloy X --- turning --- cutting force --- surface roughness --- liquid nitrogen --- grass-hooper optimization algorithm --- moth-flame optimization algorithm --- hybrid bat algorithm --- optimization problem --- the distributed assembly permutation flowshop scheduling problem --- variable neighborhood descent --- multi-criteria assessment --- cell manufacturing design --- operational complexity --- makespan --- production line balancing rate --- electrochemical machining (ECM) --- material removal rate (MRR) --- nickel presence (NP) --- grey wolf optimizer (GWO) --- moth-flame optimization algorithm (MFO) --- Monel 400 alloys --- flexible job-shop scheduling problem --- combinatorial optimization --- genetic algorithm --- candidate order-based genetic algorithm --- multichromosome --- facility layout --- optimization --- metaheuristic algorithm --- cell formation --- design of experiments --- digital platforms --- decision-making --- insurance --- Baltic --- customization --- personalization --- assembly line balancing --- group technology --- cluster algorithm --- bottleneck station --- output rate --- tolerance allocation --- machine and process selection --- heuristic approach --- univariate search method --- whale optimization algorithm --- selective assembly --- overrunning clutch assembly --- harmony search algorithm --- Hastelloy X --- turning --- cutting force --- surface roughness --- liquid nitrogen --- grass-hooper optimization algorithm --- moth-flame optimization algorithm --- hybrid bat algorithm --- optimization problem --- the distributed assembly permutation flowshop scheduling problem --- variable neighborhood descent --- multi-criteria assessment --- cell manufacturing design --- operational complexity --- makespan --- production line balancing rate --- electrochemical machining (ECM) --- material removal rate (MRR) --- nickel presence (NP) --- grey wolf optimizer (GWO) --- moth-flame optimization algorithm (MFO) --- Monel 400 alloys
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