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Modelos y algorítmos de secuenciación en líneas de ensamble de productos mixtos
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The object of this thesis is the Mixed-model Assembly-line Sequencing problem, Assembly lines have become a core component in modern repetitive manufacturing systems, especially in Just in Time production systems. Sequencing problems are important for the efficient use of mixed-model assembly lines. The sequencing for such lines entails the determination of the order in which the products are to be assembled in the line, in relation to specific criteria. In this work, load leveling is considered to be the sequencing criteria. Various objectives have been considered by researchers to measure leveling of the load. The objective used depends on the company management policies and on the productive system constraints. The main sequencing objective is to minimize the work overload. Work overload can be understood as the work which would not be completed if the assembler were to work at a normal pace and stay within the boundaries of the station. The problem is studied assuming paced line, closed stations, deterministic processing times, fixed launching, and operator schedule has an early start. Due to the computational effort required for optimally solving the problem, three different heuristic methodologies are explored in this thesis: constructive procedures (CP), local search and the combination of priority rules and neighborhood search. Concerning the CP, three algorithms are taken from literature. These procedures consider one station and two kinds of products . Two procedures are proposed for this problem. One of them is greedy (Ud1). The other (Ud2) is based in the fact that prior values of compulsory work overload and idle time can be obtained and can be used to guide previously existing procedures. Five procedures are compared in two computational experiments. In experiment one, procedures are compared on a testbed of 750 instances with single station. Multiple stations are considered in experiment two with 2250 instances .
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... Modelo de secuenciación se miden variables para la toma de decisiones de tres tipos, planificación de operaciones, cálculo de necesidades de materiales y recursos, programación de la producción con subfunciones carga (loading), secuenciación (sequencing), temporización (scheduling) [11]. Este modelo logra nivelar la carga en cada proceso dentro de las líneas de trabajo y mantener un ritmo constante de consumo requerido. ...
... Se aplica un método de mejora por reinserción de segmentos [22]. Dada una solución S, su vecindario N (S) es el conjunto de todas las soluciones alcanzables desde S realizando un movimiento move. ...
Se presenta una hiperheurística para el problema de secuenciación de modelos mixtos en líneas de montaje. El criterio de secuenciación es la minimización de la sobrecarga producida en las estaciones de la línea de montaje debido a las diferentes cantidades de trabajo necesarias para procesar diferentes versiones de los productos. Secuencias largas de productos ricos en contenido de trabajo pueden producir sobrecarga cuando en las estaciones no se tiene la capacidad de terminar los trabajos en el espacio temporal destinado para ello. El nivel superior de la hiperheurística esta basado en la metodología de búsqueda dispersa (SS), mientras que el nivel inferior trabaja con combinación de reglas de prioridad. Se proponen dos esquemas generales de la hiperheurística y se prueban diferentes niveles de mejoramiento. Los resultados experimentales muestran que mejoras locales en las secuencias del conjunto de referencia final o pequeñas mejoras en las secuencias obtenidas por combinación de reglas producen buenas soluciones.
Nowadays, there are many production systems in which the manufacture of all or part of the production takes place in assembly lines. In addition, the current demand of the market, makes necessary that companies provide a wide range of products with different options. This situation can easily be found in the automobile sector, where different product types, despite belonging to the same family, have different characteristics and require, therefore, different component consumptions and resource use. Indeed, not all vehicles carry the same type of engine, and not all vehicles are equipped with the same components, both indoors and outdoors.
A clear example of this type of assembly lines with mixed products (MMAL, Mixed-Model Assembly Lines), is found in the engine lines or in assembly lines, where different components (seats, steering wheel and pedals) are incorporated into the body of the vehicle. This variety of the product range, leads to the need for the current production or assembly lines are flexible and , therefore, the lines can adapt to the diversity of product types that are manufactured in them, without incurring excessive costs.
Thus, with the aim of making flexible and reducing costs by labor, handling and storage, the mixed product lines have two basic problems: (1) the balancing assembly line and (2) the sequencing of units of mixed-products.
Among the latter problems, we find the study object of this thesis, known as MMSP (Mixed-Model Sequencing Problem) in the literature. This problem consist of establishing a manufacturing order of the products with the aim of: minimising the product and component stock levels; (2) minimising the work overload or the uncompleted work; or (3) minimising the sub-sequence number with special options.
Specifically, in this thesis we study the mixed-model sequencing problem, in assembly lines, with the minimisation of the uncompleted work or work overload (MMSP-W: Mixed-Model Sequencing Problem with Workload Minimisation). Indeed, with the focus of addressing the literature problem, not only to the improvement of productivity, but also to the improvement of the working conditions of the operators of the line, we study four variants, in which we incorporate aspects of the real-life situations that occur in the current production systems.
In the first studied variant, in addition to consider workstations arranged in series and, therefore, interlinked, we consider that in a same workstation may coincide different homogeneous processors, as well as the possibility that all stations can hold all product units a time longer than the cycle time, in order to complete the required work. This variant will result in two equivalent mathematical models, whose objectives will be based on the optimization of the work overload or the completed work and which will serve as the starting point of the following studied variants.
The second variant, incorporates concepts from the management ideology JIT (Just In Time), since, in addition to minimise the work overload or maximise the completed work, this extension considers the convenience of obtaining product sequences that distribute evenly over time the required work, the completed work or the work overload corresponding to all work stations in a workday. This study will give rise to new multi and mono-objectives mathematical models, whose purpose will be to minimize the workload avoiding undesirable excess efforts for human resources.
In the third variant, are considered variable processing times of operations according to the rhythm of activity of operators throughout their workday. Thus, based on the idea that the activity of operators is not maintained constant along the time, different profiles for the factor of activity or work pace are defined. These profiles will force an increase of the working speed of the operators, at certain times of the workday, thus completing more required work and, therefore, reducing the overall work overload.
At last, taking into account, also, the presence of human resources on workstations, we consider the working conditions agreed between the company and trade unions with respect to saturation or level of employment of the workers of the line. Thus, we formulate new mathematical models for the MMSP-W, which, in addition to minimise the amount of lost work, respect the maximum values, laid down by collective agreements, in terms of average and maximum saturation of workstation processors.
Finally, note that all studied extensions for the MMSP-W are evaluated through a case study linked to the plant of engines from Nissan in Barcelona. In this way, we can compare the results obtained with the reference models, with those obtained with the proposed models throughout this thesis, from a computational, economic, social and legal point of view.
The problem of sequencing mixed model assembly lines is characterized by a set of parameters whose values are dictated by the actual manufacturing environment. In some cases, it may be desirable to minimize the size of the facility, while in others, the throughput time is paramount. Important design considerations include operator schedules, the product mix, station boundaries, and the launching discipline. The intent of this paper is to present a common mathematical framework in which each possible variant can be addressed. By implication, a solution technique developed for one can be readily adopted for the others.Virtually all of the previous work on mixed model sequencing has focused on the development of heuristics. While these may work well in specific instances, it is difficult to assess their performance without a frame of reference. Moreover, they cannot be universally applied. In this paper, we show that it is possible to obtain optimal solutions at very little cost. The presentation is concerned with sequencing the minimum part set; however, experience indicates that much larger problems can be solved.
Las líneas de fabricación de productos mixtos, muy frecuentes en los entornos JIT (Just-in-Time) y DS (Douki Seisan), permiten tratar diversas variantes de uno o más productos. Esta flexibilidad condiciona el orden en que se han de tratar las unidades, al que llamaremos secuencia, para conseguir una reducción drástica de inventarios intermedios y para aprovechar al máximo el tiempo destinado a la fabricación.
En estos entornos podemos encontrar dos categorías de objetivos básicos: (A) Reducir el sobreesfuerzo o el trabajo perdido y (B) Reducir al mínimo los niveles de inventario.
También se distinguen en este contexto tres tipos de problemas de secuencias:
(1) Mixed-Model Sequencing Problem (MMSP): Secuencias que implican completar el máximo trabajo requerido por el programa de producción
(2) Car sequencing problem (CSP): Secuencias condicionadas por la limitación sobre la frecuencia con que pueden aparecer en éstas algunas opciones especiales.
(3) Level Scheduling (LS): Secuencias que implican trabajar con unas tasas de producción y de consumo de materiales lo más regulares a lo largo del tiempo.
La presente tesis se enmarca en la categoría B de objetivos y en la tipología 3 de problemas, y está estructurada en 7 capítulos.
- Tras una breve introducción a la planificación y programación de operaciones, en §1 se establece un marco general sobre la secuenciación de unidades de productos mixtos en contexto JIT.
- En §2 se formula un modelo general de secuenciación de productos con un solo nivel de componentes en la lista de materiales.
- Los criterios de valoración de dichas secuencias se establecen en §3, donde se propone una taxonomía de modelos, en función del objetivo, que permite clasificar los modelos presentes en la literatura.
- En §4 se explica el método Goal chasing, empleado por Toyota y propuesto por Monden, para resolver el problema ORV (Output Rate Variation).
- En el capítulo §5 se mejora el método Goal chasing con una drástica reducción de los tiempos de computación (usando la matriz de afinidad secuencial) y con la propuesta de 7 procedimientos heurísticos, cuyas eficiencias se contrastan mediante dos experiencia computacionales.
- El capítulo §6 está dedicado a la descripción y formalización de un procedimiento exacto basado en la programación dinámica, BDP (Bounded Dynamic Programming), para resolver el problema ORV. Aquí también se realizan dos experiencias computacionales que permiten estudiar el comportamiento de la BDP en función de sus parámetros algorítmicos.
- El capítulo §7 se centra en nuevas extensiones a los problemas de secuencias en contexto JIT. Se proponen modelos y procedimientos: (1) incorporando al problema ORV las restricciones del CSP relativas a la frecuencia de aparición de opciones especiales en la secuencia, (2) ponderando la regularidad en el consumo de componentes, (3) regularizando la producción y el consumo de componentes en sistemas con múltiples etapas productivas (caso multinivel), y (4) unificando las extensiones anteriores a través de la matriz de afinidad secuencial.
- La tesis finaliza con la síntesis y las conclusiones.
Mixed-model assembly lines are widely used in just-in-time (JIT) production systems. One of the commonly used goals in sequencing mixed-model assembly lines in JIT production systems is to maintain nearly constant rates of part usage on the line. In this paper the sequencing problem is generalized to consider weights for different models in evaluating their influence on the part usage rate. The existing methods for sequencing mixed-model assembly lines are modified for the generalized problem. Computational comparisons are made between the modified heuristic methods and an optimal procedure for the squared variation objective. The computational results show that the modified heuristic methods obtain nearly optimal solutions and require moderate CPU times.
AbstractA mixed‐model multilevel manufacturing facility running under a just‐in‐time (JIT) production system is controlled by setting the production schedule for the highest level in the facility, which is usually a mixed‐model final assembly line. The schedule is set to achieve the goals of the organization, which under JIT are (1) to keep a constant rate of part usage, and (2) to maintain a smooth production load. In this article we extend earlier work in the literature, which focused on the first goal, by developing scheduling procedures which satisfy both goals. Properties of the resulting production schedules are analyzed and illustrative examples are presented.
The sequencing of products for final assembly in JIT mixed-model manufacturing systems is sometimes based on multiple criteria. The two main criteria that have been discussed in the literature are: the smoothing of parts utilization and the smoothing of the product load. Product rate variation smoothing and sub-assembly load variation smoothing may also be considered. One procedure for treating these multiple criteria is by the use of a weighted multi-attribute cost function, which is an aggregation of the respective objective functions. However, one difficulty which may be associated with this approach is in obtaining proper estimates for the weights. In this paper, we propose an alternative approach (a parametric procedure), which utilizes only the relative preference information for the criteria. A numerical example is presented to illustrate the procedure.
A dynamic programming procedure for determining the optimal just-in-time (JIT) production schedule for a mixed-model facility is presented. Compared to previously available optimization methods it substantially reduces computation and storage requirements, enabling practical-sized problems to be solved. However, there are still difficulties for solving very large problems. Heuristics, which have been proposed for these large problems, can now be evaluated by generating problems and comparing the schedules produced by the heuristics with the optimal schedule. This is done for two heuristics.
The commonly accepted objective for sequencing a mixed-model assembly line in a just-in-time (JIT) production system is to maintain a near-constant production rate for every model in the line. This article provides an extremely simple algorithm to solve this problem. The repeating property of the new algorithm is also given.
Here a paced automobile assembly line is considered with no buffers between stations. Setup costs are incurred each time sequence of jobs switches colour in the paint shop, and utility work costs are incurred when some amount of work on a job cannot be completed within the boundary of a trim station. Although there has been a concerted effort to reduce setup costs, the nature of the changeovers makes it difficult to reduce to zero. Thus, there is a need for procedures that systematically consider both setup and utility costs, not only to improve current operations, but also to evaluate the economic benefit of investments in setup cost reduction. First, an algorithm with a look-ahead provision is developed to determine sequences for trim stations only. Later, setup cost is included and solution approaches are developed based on the previous algorithm. Extensive empirical study is done by using real as well as random data to evaluate performances of procedures.
Many companies are using Just-In-Time (JIT) control systems in their mixed-model multi-level production facilities. When scheduling these facilities the most important objective is to keep a constant rate of usage for every part used by the system. In this paper a mathematical model for scheduling these facilities is studied and techniques for determining good schedules are developed. Procedures for solving very large problems are given.
The commonly accepted objective of sequencing a mixed‐model assembly line for a Just‐In‐Time (JIT) production system is to keep part usage rates at the assembly line close to constant. Sumichrast and Russell evaluated four existing sequencing methods and showed that the best method in achieving this objective is Miltenburg's algorithm 3 using heuristic 2 (M‐A3H2).
This paper presents a much simpler heuristic procedure compared to M‐A3H2. The experiment on 9 problem sets conducted by Sumichrast and Russell is repeated for the new heuristic procedure and M‐A3H2. The results show that the new heuristic procedure is as good as M‐A3H2 in solution quality regarding the mean squared and absolute deviations and much more efficient in computation time. It is further noticed that the computation time required by M‐A3H2 increases much faster than the new heuristic procedure as the number of products increases. Nevertheless, the most important benefit of this new heuristic procedure is its simplicity which should make it very desirable for practitioners.