Programación de la producción para la sección de formado y lijado en una empresa de fabricación de cepillos profesionales para peluquerías

La programación de la producción se entiende como el proceso que tiene una empresa para la toma de decisiones respecto a la fabricación de sus productos. En este proyecto se estudiará el problema de programación de la producción para la Etapa 2: formado y lijado, la cual se identificó como cuello de botella en la empresa Irca Ltda. Como principal objetivo, se desarrollará un aplicativo en Microsoft Excel ®. El cual se apoyará en un algoritmo genético que logre reducir la sumatoria de las diferencias entre el tiempo de terminación de un trabajo y la fecha de entrega del mismo; entendida como la minimización de la tardanza total. Se tomaron restricciones propias del sistema, las cuales están relacionadas con máquinas en paralelo, elegibilidad de máquina, permutación e interrupción de las órdenes de producción. Este algoritmo genético aplica un enfoque de variabilidad logrando hallar una solución factible y de calidad para el problema. Este enfoque comienza utilizando reglas de despacho como SPT, LPT, EDD y LIFO para el caso de la población inicial, para la selección de padres una probabilidad asociada al de menor tardanza, para el cruce se utiliza aleatoriedad en las particiones a intercambiar y en la mutación se presenta la probabilidad que los tipos de cabo se agrupen para reducción de tiempos de alistamiento. Respecto a los resultados obtenidos es posible evidenciar como el algoritmo propuesto mejora la tardanza en un rango entre el 40-90%, además de mejor solución en comparación con la programación actual de la compañía, al igual que con las reglas de despacho evaluadas.Scheduling is understood as the decision process that a company has to make regarding the manufacture of its products. This project will study the production scheduling problem for Stage 2: formed and sanding, which was identified as a bottleneck in the company Irca Ltda. As an objective, an application will be developed in Microsoft Excel ®. Which will be based on a genetic algorithm that reduces the sum of the differences between the time of completion of a work and the date of delivery of the same, Understood as the minimization of total tardiness. The constraints of this system were applied, this are related to parallel machines, machine eligibility, permutation and interruption of production orders. This genetic algorithm applies a variability approach to find a feasible and quality solution for the problem. This approach starts using dispatch rules such as SPT, LPT, EDD and LIFO for the initial population case, for the selection of parents a probability associated to the lesser delay, for the crossing is used randomness in the partitions to be exchanged and in the Mutation we present the probability that the types of cable are grouped for reduction of enlistment times. Regarding the results obtained, it is possible to show how the proposed algorithm improves the Total Tardiness in a range between 40-90%, as well as a better solution in comparison with the current schedule of the company, as well as with the dispatch rules evaluated.Ingeniero (a) IndustrialPregrad

Otimização Adaptativa Baseada em Simulação para a programação da produção em sistemas flow shop: um estudo comparativo

TCC(graduação) - Universidade Federal de Santa Catarina. Centro Tecnológico. Engenharia de ProduçãoO planejamento e controle da produção é uma atividade essencial para todos os sistemas produtivos, uma vez que seu desempenho afeta diretamente critérios importantes como custo, qualidade, tempo e disponibilidade, fatores fundamentais para a competitividade empresarial. O problema de programação do flow shop é um dos problemas mais comuns envolvendo o planejamento de sistemas produtivos, sendo altamente aplicado no mundo real. A solução para este problema não pode ser encontrada facilmente devido à sua complexidade, o que impossibilita a utilização de métodos que retornem resultados ótimos a um baixo tempo de execução computacional. Assim, a Otimização Adaptativa Baseada em Simulação é uma ferramenta com potencial aplicação pois considera a estocasticidade do problema, buscando soluções que estejam alinhadas com o cenário real por meio de uma simulação e otimizando as variáveis desejadas. O objetivo geral do presente trabalho é avaliar comparativamente diferentes modelos de otimização adaptativa baseada em simulação para sistemas de produção flow shop. Foram considerados dois métodos para comparação, ambos aplicando um algoritmo genético integrado com uma simulação de eventos discretos. O primeiro método busca encontrar a melhor regra de sequenciamento para cada máquina do sistema produtivo, enquanto o segundo busca encontrar diretamente o melhor sequenciamento de ordens de produção sem uma regra pré-determinada. Os resultados mostram que um sequenciamento direto de ordens de produção retorna resultados melhores que as regras de despacho, tanto o makespan quanto o tempo de execução.Production planning and control is an essential activity for all production systems, since its performance directly affects important criteria such as cost, quality, time and availability, factors that are fundamental for business competitiveness. The flow shop scheduling problem is one of the most common problems involving the planning of production systems, being highly applied in the real world. The solution to this problem cannot be easily found due to its complexity, which makes it impossible to use methods that return optimal results at a low computational execution time. Thus, Adaptive Simulation-Based Optimization is a tool with potential application as it considers the stochasticity of the problem, seeking solutions that are aligned with the real scenario through a simulation and optimizing the desired variables. The general objective of the present work is to comparatively evaluate different adaptive simulation-based optimization models for flow shop production systems. Two methods for comparison were considered, which apply a genetic algorithm integrated with a simulation of discrete events. The first method seeks to find the best dispatching rule for each machine in the production system, while the second seeks to directly find the best sequencing of production orders without a pre-determined rule. The results show that the rule-free sequencing of production orders returns better results than dispatch rules, both makespan and execution tim

MRP and Scheduling integration: A case study for the food industry

En este proyecto, se estudió una empresa encargada de elaborar productos alimenticios, con un proceso de producción complejo. Esta empresa no dispone de herramientas o metodologías para analizar el comportamiento de las variables, que en la literatura son consideradas importantes para planificar adecuadamente un determinado período de tiempo. Por esta razón, el foco del proyecto está en la planificación y ejecución del proceso productivo de la empresa. Para solucionar este problema, se propone una secuencia que vincula la metodología de planeamiento con la metodología de ejecución, donde ambas tienen objetivos diferentes, pero sus resultados son utilizados para retroalimentar el proceso en general, logrando un mejor desempeño en la utilización de materias primas y la reducción de posibles faltantes, que al final influyen en la reducción de los costos de producción, generando mayores ganancias para la empresa. La secuencia parte del desarrollo por separado de herramientas, que en primer lugar dan solución a la planificación del abastecimiento de materias primas para atender la demanda prevista, y en segundo lugar, la creación de herramientas que establecen un plan de producción, indicando el orden de los trabajos a realizar y proporcionando una idea de la capacidad productiva actual de la empresa. Para comprobar la eficacia de las metodologías, se utilizaron los datos de la empresa relacionados con los tiempos de procesamiento de los puestos, las máquinas, las cantidades producidas para cada día y las demandas históricas de la empresa. Se analizaron todos esos datos y se construyó un modelo de simulación para ajustar la metodología final. De hecho, una parte importante del proceso fue el trabajo en colaboración con la empresa, ya que se recibió feedback a través de la comunicación de los resultados.In this project, a company in charge of producing food products, with a complex production process, was studied. This company does not have tools or methodologies to analyze the behavior of variables, which in the literature are considered important to adequately plan a specific period of time. For this reason, the focus of the project is on the planning and execution of the company's production process. To solve this problem, a sequence is proposed that links the planning methodology with the execution methodology, where both have different objectives, but their results are used to feed back the process in general, achieving a better performance in the use of raw materials and the reduction of possible shortages, which in the end influence the reduction of production costs, generating more profits for the company. The sequence starts from the separate development of tools, which firstly provide a solution to the planning of the supply of raw materials to meet the forecasted demand, and secondly, the creation of tools that establish a production plan, indicating the order of the work to be done and providing an idea of the current production capacity of the company. To test the effectiveness of the methodologies, company’s data related to processing times of the stations, machines, quantities produced for each day and the historical demands of the company was used. All those data were analyzed, and a simulation model was built to adjust the final methodology. Indeed, an important part of the process was the collaborative work with the company, since feedback was received through the communication of the results.Ingeniero (a) IndustrialPregrad

Bi-criteria group scheduling with learning in hybrid flow shops

In this research, a bi-criteria group scheduling problem is investigated in hybrid flow shop (HFS) environments, where the parallel machines in each stage are unrelated, meaning not identical. The objective of the problem is to minimize a linear combination of the total weighted completion times as a means of complying with the interests of the producer, and the total weighted tardiness as a means of complying with the interests of customers. The underlying assumptions of the problem include the group technology assumptions (GTA) that require all jobs within a group to be processed successively and on the same machine. The runtime of these jobs are dynamic and progressively decrease as the worker learns how to perform similar jobs. A sequence-dependent setup time is considered for switching between different groups on the same machine. Although all jobs have to move in unidirectional paths through the HFS, some may skip some of the stages. Furthermore, in order to capture more realistic features of the scheduling problems, the jobs are assumed to be released into the system at dynamic times, and the machines, as well, are assumed to be available at dynamic times. The problem is formulated as a mixed-integer linear programming (MILP) model. The MILP model for small sizes of the problem is solved to optimality using CPLEX. However, since the problem is strongly NP-hard, it is not possible to find its optimal solution within a reasonable time as the problem size increases to medium to large. Several meta-heuristic algorithms based on tabu search (TS), simulated annealing (SA), and genetic algorithm (GA) are developed to find the optimal/near optimal solutions for this problem. Three alterations of algorithms are developed for TS and SA-based algorithms (referred to as local search algorithms) i.e. non-permutation, partial permutation and local searches with embedded progressive perturbations. Two alternatives are also considered for GA-based algorithms (referred to as population-based algorithms) i.e. simple GA and bi-level GA. The performances of these algorithms are compared to each other in order to identify which algorithm, if any, outperforms the others. Nevertheless, the performances of all algorithms are evaluated with respect to a tight lower bound (LB) obtained based on a branch-and-price (B&P) technique developed in this research. The B&P technique uses Dantzig-Wolfe decomposition to divide the original problem into a master problem and several sub-problems. Although, the sub-problems are smaller than the original problem, they are still strongly NP-hard and cannot be optimally solved within a reasonable amount of time. However, an optimal dispatching rule is proposed that drastically reduces the number of variables and constraints in these sub-problems, and enables the B&P algorithm to find tight lower bounds even for large-size instances of the problem. A comparison between these lower bounds and the ones obtained from CPLEX reveals the impressive performance of the B&P algorithm, i.e. an average of 233% improvement for the largest size of the problems that have been tested. Evaluation of the proposed algorithms with respect to these tight lower bounds uncovers the outstanding performance of all the proposed algorithms, while identifying the bi-level GA as the best performing algorithm in dealing with the HFS scheduling problem. This algorithm reports a remarkable performance with an average deviation of only 2% from the optimal solution for small-size sample problems, and an average gap of 23% from the lower bound for the largest sizes of the tested problems. The largest problem tested in this research consists of a total of 1858 binary variables and 14654 constraints

A study on flexible flow shop and job shop scheduling using meta-heuristic approaches

Scheduling aims at allocation of resources to perform a group of tasks over a period of time in such a manner that some performance goals such as flow time, tardiness, lateness, and makespan can be minimized. Today, manufacturers face the challenges in terms of shorter product life cycles, customized products and changing demand pattern of customers. Due to intense competition in the market place, effective scheduling has now become an important issue for the growth and survival of manufacturing firms. To sustain in the current competitive environment, it is essential for the manufacturing firms to improve the schedule based on simultaneous optimization of performance measures such as makespan, flow time and tardiness. Since all the scheduling criteria are important from business operation point of view, it is vital to optimize all the objectives simultaneously instead of a single objective. It is also essentially important for the manufacturing firms to improve the performance of production scheduling systems that can address internal uncertainties such as machine breakdown, tool failure and change in processing times. The schedules must meet the deadline committed to customers because failure to do so may result in a significant loss of goodwill. Often, it is necessary to reschedule an existing plan due to uncertainty event like machine breakdowns. The problem of finding robust schedules (schedule performance does not deteriorate in disruption situation) or flexible schedules (schedules expected to perform well after some degree of modification when uncertain condition is encountered) is of utmost importance for real world applications as they operate in dynamic environments

Diseño de una metodología de programación de producción para la reducción de costos en un flow shop híbrido flexible mediante el uso de algoritmos genéticos. Aplicación a la industria textil

La industria textil posee configuración productiva flow shop híbrido flexible, además de una serie de particularidades que hacen que los modelos estándares de programación de producción no sean aplicables. Se ha demostrado la naturaleza N-P completo del problema, por lo que el uso de meta heurísticas está bien justificado. Considerando la importancia de la reducción de los costos de fabricación en la industria textil colombiana, se propone una nueva metodología de programación de producción basada en algoritmos genéticos, que tiene presente algunas de las complejidades de la industria textil (tiempos de montaje dependientes de la secuencia, máquinas paralelas no relacionadas, cumplimiento de fechas de entrega) y permite la reducción de sus costos de producción. Al aplicarla a un problema basado en la industria textil colombiana se obtuvo una mejora promedio del 22,39% y 22,36% con respecto al método SPT y a un método aleatorio, respectivamente. Asimismo se reduce casi en un 100% el incumplimiento de fechas de entrega. Se concluye que la metodología es efectiva y que puede extenderse su aplicación a otros sectores industriales con configuración flow shop híbrido flexible. Futuros trabajos podrían considerar otras complejidades como los lotes de transferencia variables, la entrada dinámica y la maleabilidad, o aplicar la metodología a otro tipo de industrias con esta configuración productivaAbstract : Textile industry can be described by the productive configuration denominated Hybrid Flow Shop, and has a number of characteristics that make the standard scheduling models not applicable. It has been proved the NP-complete nature of the problem, so that the use of meta-heuristics is well justified. Considering the importance of reducing manufacturing costs in Colombian textile industry, a new production scheduling methodology based on genetic algorithms is proposed, which take into account some of the complexities presented in the textile industry (sequence dependent setup times, unrelated parallel machines, compliance with due dates) and allows the reduction of production costs. When the methodology was applied to a Colombian textile industry-based problem, an average improvement of 22.39% and 22.36% in comparison with the SPT method and random method, respectively, were obtained. It was also reduced almost in 100% the failure to due dates. It is concluded that the methodology is effective and can extend its application to other industries with a hybrid flow shop configuration. Future work could consider other complexities such as variable transfer batches, dynamic input and malleability, or apply the methodology to other industries in this productive configurationMaestrí

Mejora de tiempos de entrega en un flow shop híbrido flexible usando técnicas inteligentes. Aplicación en la industria de tejidos técnicos

Se busca aportar herramientas útiles para la programación de producción en la industria de tejidos técnicos. Se parte de las condiciones actuales de la programación de producción en este tipo de industria y de los antecedentes en la literatura científica sobre modelos aplicables a estos entornos. Se propone un modelo de solución por técnicas inteligentes a la problemática de la secuenciación y asignación de tareas en los entornos flow shop híbrido flexible considerando situaciones como: paralelismo entre máquinas no relacionadas, tiempos de montaje dependientes de la secuencia, entrada dinámica de trabajos, restricción de elegibilidad, maleabilidad y lotes de transferencia variables entre etapas. De allí se construye la propuesta de solución que involucra simultáneamente todas las condiciones de entorno real mencionadas y aplica un algoritmo genético modificado de acuerdo a las características del problema. Se concluye que el modelado considerando condiciones realistas es posible, que los algoritmos genéticos son una opción práctica para entornos reales y que las empresas pueden obtener mejoras en su capacidad de respuesta con este tipo de solucionesAbstract : It seeks to provide useful tools for production scheduling in the technical textiles industry. It begins in the current conditions of production scheduling in this type of industry and the background in scientific literature, applicable to these environments models. The mathematical model to solve the problem of sequencing and assigning jobs in Flexible hybrid flow shop environments is developed considering: unrelated parallel machines, sequence dependent setup time, dynamic entry of jobs, availability constrain, malleability and variable transfer batches between stages. The solution proposal is build including all actual environment features considered together and applying a modified genetic algorithm modeled according to the problem. It is concluded that the model of scheduling problems considering realistic conditions is possible, that genetic algorithms are a practical option for real environments, and that companies can achieve improvements in their responsiveness with this kind of solutionsDoctorad

A real-time simulation-based optimisation environment for industrial scheduling

n order to cope with the challenges in industry today, such as changes in product diversity and production volume, manufacturing companies are forced to react more flexibly and swiftly. Furthermore, in order for them to survive in an ever-changing market, they also need to be highly competitive by achieving near optimal efficiency in their operations. Production scheduling is vital to the success of manufacturing systems in industry today, because the near optimal allocation of resources is essential in remaining highly competitive. The overall aim of this study is the advancement of research in manufacturing scheduling through the exploration of more effective approaches to address complex, real-world manufacturing flow shop problems. The methodology used in the thesis is in essence a combination of systems engineering, algorithmic design and empirical experiments using real-world scenarios and data. Particularly, it proposes a new, web services-based, industrial scheduling system framework, called OPTIMISE Scheduling System (OSS), for solving real-world complex scheduling problems. OSS, as implemented on top of a generic web services-based simulation-based optimisation (SBO) platform called OPTIMISE, can support near optimal and real-time production scheduling in a distributed and parallel computing environment. Discrete-event simulation (DES) is used to represent and flexibly cope with complex scheduling problems without making unrealistic assumptions which are the major limitations of existing scheduling methods proposed in the literature. At the same time, the research has gone beyond existing studies of simulation-based scheduling applications, because the OSS has been implemented in a real-world industrial environment at an automotive manufacturer, so that qualitative evaluations and quantitative comparisons of scheduling methods and algorithms can be made with the same framework. Furthermore, in order to be able to adapt to and handle many different types of real-world scheduling problems, a new hybrid meta-heuristic scheduling algorithm that combines priority dispatching rules and genetic encoding is proposed. This combination is demonstrated to be able to handle a wider range of problems or a current scheduling problem that may change over time, due to the flexibility requirements in the real-world. The novel hybrid genetic representation has been demonstrated effective through the evaluation in the real-world scheduling problem using real-world data

Sessenta anos de Shop Scheduling : uma revisão sistemática da literatura

Orientador : Prof. Dr. Cassius Tadeu ScarpinDissertação (mestrado) - Universidade Federal do Paraná, Setor de Tecnologia, Programa de Pós-Graduação em Engenharia de Produção. Defesa: Curitiba, 09/02/2017Inclui referências : f. 449-492Resumo: Desde o seminal artigo de Johnson em 1954, a Programação da Produção em Shop Scheduling tem se tornado uma área relevante dentro da Pesquisa Operacional e, atualmente, duzentos trabalhos tangentes à temática são publicados anualmente. Dentre os artigos aqui citados tem-se aqueles que se dedicam à apresentação e síntese do estado da arte desse assunto, intitulados artigos de revisão. Quando tais artigos são elaborados a partir de um conjunto objetivo de critérios, relativos à categorização dos artigos selecionados, tem-se a Revisão Sistemática da Literatura (RSL). O presente trabalho realiza uma RSL em Shop Scheduling, a partir da análise de cada ambiente fabril que o compõe. Fez-se o escrutínio de 560 artigos, à luz de um conjunto de métricas, que constitui a estrutura basilar da proposta de nova taxonomia do Shop Scheduling, complementar à notação de Graham, objetivo fulcral do presente trabalho. Além disso, utilizou-se uma representação em redes dos resultados obtidos em algumas das métricas empregadas, como a característica dos itens, algo outrora inaudito em estudos de revisão desse assunto. Ademais, outro ponto relevante desse estudo repousa na identificação de campos pouco explorados, de modo a colaborar com a pesquisa futura neste tomo. Palavras-chave: Shop Scheduling. Revisão Sistemática da Literatura. Taxonomia. Representação em Redes.Abstract: Since Johnson's seminal article in 1954, Shop Scheduling in Production Scheduling has become a relevant area within Operational Research, and currently hundreds of tangential works on the subject are published annually. Among the articles cited here are those dedicated to the presentation and synthesis of the state of the art of this subject, which are entitled review articles. When these articles are elaborated from an objective set of criteria, regarding the categorization of the selected articles, we have the Systematic Review of Literature (SLR). The present work performs a SLR in Shop Scheduling, based on the analysis of each manufacturing environment that composes it. There were 560 articles scrutinized based on a set of metrics, which is the basic structure of the proposed new Taxonomy of Shop Scheduling, complementary to Graham's notation, the main objective of this work. In addition to that a network representation of the results was obtained in some of the metrics used, such as the job characteristics, something previously unheard of in review studies of this subject. Moreover, another relevant point of this study lies in the identification of less explored fields in order to collaborate with future research in this matter. Keywords: Shop Scheduling. Systematic Literature Review. Taxonomy. Network Representation