1,721,065 research outputs found
How to define a business-specific smart manufacturing solution
No full textThe chapter covers methodologies and tools supporting the of concept engineering development with focus on small and medium sized enterprises. We describe Industry 4.0 maturity assessment models, value proposition definition techniques considering strategic considerations, and the identification and selection of solutions. In addition, a real case study illustrating the application of some of the after mentioned tools is developed. The case is based on a production plant of soft drinks and beverages.Fil: Sanchez, Marisa. Universidad Nacional del Sur. Departamento de Ciencias de la Administración; ArgentinaFil: Rossit, Daniel Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; ArgentinaFil: Carbone, Agustín. Coca Cola Andina; Argentin
Introduction to—evolution and trends of sustainability
No full textThis book aims to provide different trends and approaches within the sustainability framework to evaluate their impact and offer possible solutions to the problems facing the global sustainability paradigm. Sustainability assessment approaches support different levels of both decision-making and policy processes, thereby improving the management of natural and human systems. Additionally, there are many different approaches to quantifying and estimating sustainability. Among the most notable are sustainability indicators (SI), as they are widely used to measure and communicate progress toward sustainable development. Additionally, another option for assessing sustainability based on the industry's life cycle is the life cycle sustainability assessment (LCSA), which balances the three dimensions of sustainability (environmental, social, and economic). This book brings together different facets and approaches of sustainable production, as well as the impact of new technologies and different climate phenomena on the processes. In the different parts of this book, there is a comprehensive and orderly approach to current problems.Fil: Rossit, Daniel Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; ArgentinaFil: Hussain, Chaudhery Mustansar. New Jersey Institute of Technology; Estados Unido
Closed-loop supply chain and extended producer responsibility (EPR): A literature review
No full textEnvironmental impact problems from industrial activities imply a great risk for the sustainability of societies and ecosystems of the future. In this sense, in recent years have grown the awareness and the need to generate concrete actions that improve this panorama. That is why many countries in their regulations and international treaties have focused on promoting these actions in pursuit of more environmentally friendly industrial activity. One of these rules is extended producer responsibility (EPR), in which the producer, as well as other relevant actors in the supply chain, are required to take responsibility for the impact of their industrial activities on the environment. In this way, companies must devise different strategies to minimize the impact or to mitigate it if it cannot be avoided, so that the market prices of the products represent not only the manufacturing and distribution of the products, but the entire life cycle of the product, such as the resulting waste management costs. In this work, a review of the literature in this regard is proposed. This review analyzes the literature on the subject with special emphasis on how the loop is closed in supply chains and how operations are planned with a view to reducing waste and environmental impacts.Fil: Marizcurrena, Milagros. Universidad de la República; UruguayFil: Morás, Victoria. Universidad de la República; UruguayFil: Ulery, Guillermo. Universidad de la República; UruguayFil: Rossit, Daniel Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; ArgentinaFil: Piñeyro, Pedro. Universidad de la República; Urugua
Effective heuristics for permutation and non-permutation flow shop scheduling with missing operations
No full textIn recent years, thanks to the fourth industrial revolution, there have been significant increases in the flexibility and agility of industrial processes. In this way, business models based on mass customization of production have gained presence in the industry. In terms of production scheduling in flow shop systems, customization affects production operations, in many cases giving rise to the problem of missing operations, that is, there are jobs that do not perform all operations. Modeling missing operations as zero-time operations, allows to find schedules, but wastes efficiency since zero-time operations lead to unnecessary waiting times. In this paper, we demonstrate that even in permutation flow shops treating missing operations as zero-time operations can make the makespan or the total flow time of optimal schedules arbitrarily worse. We show that a promising way to address missing operations is to consider limited non-permutation solutions over the sub-jobs of a job composed of regular operations. We introduce an efficient representation for such schedules and propose algorithms that allow to solve the problem based on iterated greedy methods. The computational results show that the proposed algorithms are superior to the state-of-the-art algorithms.Fil: Ritt, Marcus. Universidade Federal do Rio Grande do Sul; BrasilFil: Rossit, Daniel Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; Argentin
Simultaneous lot-sizing and scheduling with recovery options: problem formulation and analysis of the single-product case
No full textWe address an extension of the discrete lot-sizing and scheduling problem in which the demand of products can be also satisfied by remanufacturing used products returned to the origin. A mixed-integer linear programming formulation is provided for the problem, assuming dynamic demand and returns values, and time-invariant costs of setup and holding inventory. We then present a numerical experimentation carried out with the mathematical model for the case of a single product, in order to evaluate the efficiency in both costs and solving times compared to the traditional problem without returns. From the results obtained we conclude that the problem with recovery options can lead to economic benefits only under certain assumptions on the costs and amounts of returns. In addition, according to the runtimes obtained for large instances of the problem, it seems to be much more difficult to solve than its traditional version without returns.Fil: Piñeyro, Pedro. Universidad de la República; UruguayFil: Rossit, Daniel Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; ArgentinaInternational Conference of Production Research-AmericasBahía BlancaArgentinaUniversidad Nacional del Su
Lot streaming Permutation Flow shop with energy awareness
Get PDFIn this work, the flow shop scheduling problem with energy awareness is approached with lot-streaming strategies. Energy consumption is modeled within the objective function, together with the makespan, by means of a normalized and weighted sum. Thus, reducing energy consumption guides the optimization process. For lot streaming approaches mathematical models are provided and assessed. The results showed that lot-streaming is an efficient strategy to address this problem, allowing to improve both makespan and total energy consumption compared to the problem without lot-streaming. In turn, the selection of processing speeds for each sublot was incorporated, which improved the strategy yielding the best quality solutions.Fil: Florencia D'Amico. Universidad Nacional del Sur. Departamento de Ingeniería; ArgentinaFil: Rossit, Daniel Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; ArgentinaFil: Frutos, Mariano. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Investigaciones Económicas y Sociales del Sur. Universidad Nacional del Sur. Departamento de Economía. Instituto de Investigaciones Económicas y Sociales del Sur; Argentin
Enhancing Mass Customization Manufacturing: Multiobjective Metaheuristic Algorithms for flow shop Production in Smart Industry
Get PDFThe current landscape of massive production industries is undergoing significant transformations driven by emerging customer trends and new smart manufacturing technologies. One such change is the imperative to implement mass customization, wherein products are tailored to individual customer specifications while still ensuring cost efficiency through large-scale production processes. These shifts can profoundly impact various facets of the industry. This study focuses on the necessary adaptations in shop-floor production planning. Specifically, it proposes the use of efficient evolutionary algorithms to tackle the flowshop with missing operations, considering different optimization objectives: makespan, weighted total tardiness, and total completion time. An extensive computational experimentation is conducted across a range of realistic instances, encompassing varying numbers of jobs, operations, and probabilities of missing operations. The findings demonstrate the competitiveness of the proposed approach and enable the identification of the most suitable evolutionary algorithms for addressing this problem. Additionally, the impact of the probability of missing operations on optimization objectives is discussed.Fil: Rossit, Diego Gabriel. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; ArgentinaFil: Rossit, Daniel Alejandro. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; ArgentinaFil: Nesmachnow, Sergio. Facultad de Ingeniería; Urugua
Estudio de capacidad de producción en sistemas de producción de calzado basado en simulación
No full textEn este trabajo se aborda un caso de estudio de la industria manufacturera del calzado. Particularmente, se analiza el caso de una PyME de calzado de cuero de Argentina. El estudio se focaliza en la variabilidad de rendimiento que implica trabajar con materias primas de origen animal, y su consiguiente impacto en la capacidad de producción. Para ello se modeló el proceso de producción respetando todos los factores que incorporaban incertidumbre al problema. Se generaron simulaciones de eventos discretos para analizar el sistema, y se detectó el cuello de botella. Al analizar las potenciales alternativas para salvar la limitación en la capacidad, se optó por la incorporación de un nuevo trabajador. Los resultados de la propuesta de solución permitieron mostrar que incorporar un trabajador aumentaba la productividad más que proporcionalmente al incremento directo de mano de obra.Fil: Dornes, Florencia. Universidad Nacional del Sur. Departamento de Ingeniería; ArgentinaFil: Rossit, Daniel Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; ArgentinaFil: López, Nancy. Universidad Nacional del Sur. Departamento de Ingeniería; ArgentinaInternational Conference of Production Research-Americas (ICPR-Americas)Bahía BlancaArgentinaUniversidad Nacional del Su
Personalized production in Industry 4.0: a CONWIP approach
No full textProduction technologies based on Industry 4.0 allow the capacity and flexibility of production systems to be increased, enabling mass customization of production. In this work, a production problem is considered where the customization of production is extreme, resulting in unique products. This type of production is known as One-of-a-Kind Production (OKP). Naturally, this type of production places great demands on the planning system, since the standardization of production is reduced to a minimum. In this sense, it is proposed to use a production control strategy based on CONWIP, which seeks to maintain the level of work-in-progress at constant levels. In turn, to improve the performance of the CONWIP strategy, new dispatch rules are studied and designed to improve the level of service provided to the client.Fil: Vinci Carlavan, Guido. Universidad Nacional del Sur. Departamento de Ingeniería; ArgentinaFil: Rossit, Daniel Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; Argentina2022 International Conference on Decision Aid Sciences and ApplicationsChiangraiTailandiaMahe Fah Luang Universit
Scheduling in additive manufacturing problems
Get PDFScheduling problems in additive manufacturing is a problem that can involve considerably morecomplexity than single-stage scheduling problems, since machines can process more than one partwith different geometries simultaneously [1]. To achieve efficiency in terms of the used capacity of themachine, it is necessary to group as many parts as possible in a single job. Since the use of themachines in terms of time depends on the job being processed, how parts are grouped within eachjob comes critical. This implies that the resolution of the nesting problem will have a direct impact onthe objective function of the jobs Schedule. In this work, the objective function to be minimized is theTotal Completion time, wich is obtained by the sum of the completion time of each job. The biggestdifficulty is that the problem is NP-Hard [2], so a purely mathematical approach is insufficient. For thisreason, a hybrid method is proposed that allows linking the benefits of an approach based onmathematical programming but enhanced by heuristic methods. In this way, heuristics are developedthat address the nesting problem incorporating knowledge about the nature of the problem, such asthe influence of the parameters “height” and volume” of the parts in the definition of the Jobs; and thestructure of its solutions. Then, using mathematical programming, solve the scheduling in paralleladditive manufacturing machines. For the nesting stage, several heuristics were proposed andcompared, showing that those heuristics that best captured the influence of the parameterscontributed more to solving the problem.Fil: Rodriguez, Jeanette. Universidad Nacional del Sur. Departamento de Ingeniería; ArgentinaFil: Rossit, Daniel Alejandro. Consejo Nacional de Investigaciones Científicas y Técnicas. Centro Científico Tecnológico Conicet - Bahía Blanca. Instituto de Matemática Bahía Blanca. Universidad Nacional del Sur. Departamento de Matemática. Instituto de Matemática Bahía Blanca; Argentina. Universidad Nacional del Sur. Departamento de Ingeniería; ArgentinaXXI Latin Ibero-American Conference on Operations Research CLAIO 2022Buenos AiresArgentinaUniversidad de Buenos Aires. Facultad de Ciencias Exactas y Naturale
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