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In this note, we introduce a surrogate objective for utility work at a single station on a paced assembly line. We show that it is asymptotically equal to utility work as the number of jobs increases, and provide expressions for the worst-case difference between the two objectives. We also derive closed form expressions for the surrogate objective when a simple sequencing procedure, which provides optimal solutions with respect to utility work under certain conditions, is applied. This circumvents the need to solve dynamic programs in instances where only the value of the objective function is needed, such as in heuristics for multi-station problems.

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... hace a velocidad constante. Básicamente, existen dos enfoques para este problema, uno de ellos lo toma [2] al minimizar el número de unidades ricas en contenido de trabajo que exceden a una cantidad k permitida en segmentos de secuencia de tamaño l, el otro enfoque, el cual adoptamos también, es el propuesto por Yano y Rachamadugu en [3], donde proponen un modelo de programación lineal para el problema, teniendo como objetivo maximizar el trabajo completado (equivalente a la minimización del trabajo perdido o sobrecarga). Los autores se centran en ejempla res con dos tipos de productos (básicos y con opción). ...

... En el presente texto nos centraremos en las aportaciones de Yano y Rachamadugu [3], de Bolat y Yano [2,4] y Tsai [5], extendiéndonos sobre ellas. Nuestras propuestas contemplan procedimientos para varios productos y varias estaciones . ...

... Se proponen cuatro procedimientos inspirados en trabajos encontrados en la literatura [2], [3] y [4]. Las propuestas asumen múltiples productos y una sola estación. ...

Resumen—Se consideran una variante del problema de secuenciación de unidades en líneas de montaje en contexto JIT. El criterio es la minimización de la sobrecarga. Se proponen algunas heurísticas que buscan el orden en que se introducirán los diferentes variantes de un mismo producto en una estación. Se toma de la literatura un procedimiento para varias estaciones para probar las heurísticas greedy propuestas.

... Inspired on procedures from [4] and [9], four procedures are proposed, which also consider multiple products and multiple stations. We use local search with different neighborhoods for improving the solutions obtained with constructive procedures. ...

... In this section, four procedures are proposed inspired on the works from [3], [4] y [9]. Our proposals assume multiple products and only one station. ...

... Originally, instead of weak lower bounds, the objective function values wo * h of the best known solution for an instance h is used when comparing procedures. Since this measure is not defined for wo * h = 0, the following aggregated relative deviation is used: (9) We have added two more indexes for aggregated relative deviation. The original index (9) is represented by rel.wo2. ...

There are different approaches for the mixed model sequencing problem on assembly lines. In this paper the goal of minimizing work overload is treated. Since solve this problem optimally is difficult, we test c onstructive procedures, local search and a new hiperheuristic procedure.

... The existing literature which deals with the car sequencing problem assume that the spacing constraints are given and correctly defined. However, the quality of the car sequence is highly dependent on a correct definition of the spacing constraints (Bolat and Yano, 1992b). In practice, the criteria of the spacing constraints are defined based on experience and the ratios, N/P, are often deduced by the number of vehicles to produce. ...

... In the current context of the automobile industry, the diversity of vehicles which can be produced on a mixed model assembly line is tremendous and the definition of spacing constraints is a very complicated task (Lesert and al., 2007). To the best of our knowledge, no work exists in the literature on the selection of the criteria of the spacing constraints and very few studies have been reported on the calculation of N/P (Giard and Jeunet, 2006), (Yano and Rachamadugu, 1991), (Bolat and Yano, 1992a), (Bolat and Yano, 1992b). ...

... Nevertheless, the method can be refined on several points: (i)For the calculation of N/P, the multiple temporization workstations are approximated by a two temporization workstation under optimistic, pessimistic and average scenarios. This approach is similar to the one-option-two-temporization hypothesis considered in earlier works (Giard and Jeunet, 2006), (Yano and Rachamadugu, 1991), (Bolat and Yano, 1992a), (Bolat and Yano, 1992b). ...

A car sequencing problem deals with the ordering of a list of vehicles to be produced on an assembly line so that the overall capacity of each work station is not exceeded. Some types of vehicles require several time-consuming operations to be done on a work station and will naturally overload that work station. Such vehicles are spaced out in the sequence, by means of a set of spacing constraints, in order to cope with the momentary increase of workload that they create. Two questions arise: which type of vehicles should be subject to the spacing constraints and by which distance should they be spaced out in the sequence. In practice as well as in the car sequencing literature, there does not exist a methodical way to answer the first question and the existing methods for the second one is no longer adequate due to the increased diversity of cars produced in an assembly line. In this paper, we propose two new methods to answer these questions with a special emphasis on the first one. The performance of the proposed methods is illustrated using a real case study.

... Later on [5], Bolat and Yano propose as an objective, the minimization of the number of total special units exceeding the k permitted in sequential parts of size l. ...

... Both boundaries of stations are closed, and we assume that, the displacement time the worker need to go from one product in to the next, is negligible. We compiled some procedures founded in literature: Yano y Rachamadugu [9], Bolat y Yano [4] y [5], and we propose the procedure Ud1 and Ud1-ex, based on the previous procedures. Procedures considering more than two different products and multi stations are also proposed. ...

A variant of the mixed-model sequencing problem on assembly lines is the one proposed by Yano and Rachamadugu. They consider time windows in workstations and the work overload concept (sum of differences between real completion time in the workstation and due dates, which depends on the time window value). This paper proposes some procedures for solving the problem, and compares them with others taken from literature using a computational experience.

... En Bolat y Yano (1992b) se propone una función objetivo distinta a la de los trabajos anteriores: minimizar el número total de unidades especiales que exceden a las k permitidas en cada esquema de tamaño l, con ello se reducen los cálculos. ...

... Other literature related with the problem is [5], [6], [7] and recently [8]. Inspired on procedures from [4] and [9], in [10] constructive procedures in proposed, which consider multiple products and multiple stations. We use local search with different neighbourhoods for improving the solutions obtained with constructive procedures from [10]. ...

There are different approaches for the mixed-model assembly-lines sequencing problem. In this paper the goal of minimizing work overload is treated. This approach considers the existence of time windows in each work station. Different versions of a product are considered to be assembled in the line (e.g. car industry), which require different processing time according to the work required in each work station. Long sequences of rich-work products can lead to produce work overload when stations cannot fulfil all the assigned tasks. Since solve this problem optimally is difficult, we test local search and a hyper-heuristic procedure. A computational experiment is used to detect the performance of the proposed procedures.

... Bolat and Yano (1992a) develop scheduling algorithms that minimize utility work in 0(N) computation time for a single station on a paced assembly line. To ease computation, Bolat and Yano (1992b) also introduce a surrogate objective for utility work. Tsai (1995) investigates the problem of sequencing two types of products on an assembly line with two objectives: minimizing (1) the risk of conveyor stoppage and (2) the total utility work. ...

This paper presents a fast sequencing algorithm for a mixed model assembly line with multiple workstations which minimize the total utility work and idle time. We compare the proposed algorithms with another heuristic, the Tsai-based heuristic, for a sequencing problem that minimizes the total utility works. Numerical experiments are used to evaluate the performance and effectiveness of the proposed algorithm. The Tsai-based heuristic performs best in terms of utility work, but the fast sequencing algorithm performs well for both utility work and idle time. However, the computational complexity of the fast sequencing algorithm is O (KN) while the Tsai-based algorithm is O (KNlogN). Actual computational time of the fast sequencing heuristic is 2-6 times faster than that of the Tsai-based heuristic.

... Ceci pourrait constituer un frein à l'optimisation et à la mise en place industrielle si de telles données sont difficiles à collecter. (Bautista et Cano, 2008) x x (Bautista et Cano, 2011) x x x Interruption conditionnée des opérations suite à un retard (Bolat, 1997) x x Temps de retour à la limite sup du poste non négligeables Bolat et Yano (1992) x x x Un poste de travail et deux modèles (Bolat et Yano, 1992b) x x x (Bolat et al., 1994) x x x Minimise les coûts de préparation en plus des retards x (Sarker et Pan, 1998 x x x Postes de travail ouverts (Scholl, 1999) x x x (Scholl et al., 1998) x x (Sumichrast et al., 2000) x x (Tavakkoli-Moghaddam et Rahimi-Vahed, 2006) x x Multi-objectifs (temps de préparation, retards, lissage consommation des pièces) (Thomopoulos, 1970) x x x x Postes de travail ouverts (Tsai, 1995) x x x Un seul poste de travail (Wester et Kilbridge, 1964) x x x Un seul poste de travail (Xiaobo et Ohno, 1994) x x La ligne est stoppée dès qu'un retard apparaît. (Xiaobo et Ohno, 1997) x x x La ligne est stoppée dès qu'un retard apparaît. ...

In this thesis, the problem of sequencing mixed model assembly lines (MMAL) is considered. Our goal is to determine the sequence of products to minimize the work overload. This problem is known as the mixed model assembly line sequencing problem with work overload minimization (MMSP-W). This work is based on an industrial case study of a truck assembly line.Two approaches can be used to minimize the work overload: the use of task operation times or the respect of sequencing rules. Most of the earlier works applied in car industry use the latter approach. The originality of this work is to employ the task operation times for the generation of the product sequence in a MMAL.The literature review has highlighted two main gaps in previous works: most of the papers consider a single type of operators, and propose heuristics or metaheuristics to solve the problem. The originality of this work is to test exact methods for industrial case instances and to model three different types of operators.Two exact methods are developed: the mixed integer linear programming and dynamic programming. The models are tested on industrial case study instances. An experimental study is developed for both approaches in order to understand the complexity factors.Moreover, the problem is treated by two approximate methods: a heuristic based on dynamic programming and metaheuristics (genetic algorithm, simulated annealing and a hybrid method based on both genetic algorithm and simulated annealing). All approaches are tested on academic instances and on real data from the industrial case study.

... Dans ce travail, notre étude relève de la première approche et se concentre sur le problème du séquencement sur une ligne d'assemblage multi modèles avec minimisation de la surcharge de travail (MMSP-W). Cette approche a été peu développée ; on trouve néanmoins quelques travaux dans [6], [7], [8], [23], [18] et [2], entre autres. ...

... Considerando las trabajos anteriores como punto de partida, en el presente texto nos centraremos en las aportaciones de Yano y Rachamadugu [4], de Bolat y Yano [1,2] y Tsai [3], extendiéndonos sobre ellas. Nuestra propuesta incluye, para el caso de dos tipos de producto, dos familias de algoritmos para una sola estación y cuatro procedimientos para el caso de múltiples estaciones; y, para el caso de múltiples productos, se proponen extensiones de los algoritmos para dos tipos de producto. ...

... En Bolat y Yano (1992b) se propone una función objetivo distinta a la de los trabajos anteriores: minimizar el número total de unidades especiales que exceden a las k permitidas en cada esquema de tamaño l, con ello se reducen los cálculos. ...

RESUMEN Una variante del problema de secuenciación de productos mixtos en una línea de montaje es la propuesta por Yano y Rachamadugu. En ella se considera la existencia de ventanas temporales en las estaciones de trabajo y el concepto de trabajo perdido (suma de las diferencias entre los instantes reales de compleción de las unidades en las estaciones y sus fechas de finalización comprometidas dependientes del valor de la ventana temporal). En el presente trabajo se propone una serie de procedimientos para resolver el problema, y se comparan con los existentes en la literatura a través de una experiencia computacional.

... If work overload is compensated by additional workers, this amount of work is also called utility work. Papers which deal with these objectives are, for instance, Wester and Kilbridge (1964), Thomopoulos (1967), Macaskill (1973), Yano and Bolat (1989), Yano and Rachamadugu (1991), Bolat and Yano (1992b), Tsai (1995), Scholl et al. (1998), Sumichrast et al. (2000), Sarker and Pan (2001), Kim and Jeong (2007) and Bautista and Cano (2008). ...

Sequencing mixed-model assembly lines is a well researched topic in the literature. However, many methods that have been developed to solve this problem fail to cope with either the large size or the specific characteristics of real-life problems. In this paper, a heuristic is proposed that is derived from Vogel's approximation method for transportation planning. The heuristic is able to handle large and supposedly difficult problem instances. Sophisticated test scenarios considering real-life aspects were generated to evaluate the performance of the heuristic for realistic problem instances. It is shown that the proposed heuristic significantly outperforms priority rule-based methods and requires only reasonable computational effort.

... When we take into consideration not only a single workstation but all workstations, the problem becomes very complex. This goal has been discussed by, for example, Bard, et al. (1992), Bolat and Yano (1992), Dar-El and Cother (1975), Dar-El and Cucuy (1977), Goladschmidt, et al. (1997), Johnson (2002), Kim, et al. (1996, Macaskill (1973), Matanachai and Yano (2001), Merengo, et al. (1999), Mithsumori (1969 Kurashige, et al. (2002), Leu, et al. (1997, Lovgren and Racer (2000), McMullen and Frazier (2000), Merengo, et al. (1999), Miltenburg and Sinnamon (1989), Ponnambalama, et al. (2003, Steiner and Yeomans (1993), Sumichrast and Clayton (1996), Sumichrast, et al. (2000, Ventura and Radhakrishnan (2002), Zeramdini, et al. (2000), Zhang, et al. (2000, and Zhao and Zhou (1999). Several studies address a surrogated objective of keeping the constant feeding rate of every model fed into the assembly line to indirectly reach the goal of constant usage rate of every component family (see, for example, Ding and Cheng (1993), Drexl and Kimms (2001), Kubiak (1993), and Miltenburg (1989)). ...

A mixed model assembly line (MMAL) comprises a set of workstations in serial and a conveyor moving at a constant speed, which can assemble variety products in different models during a working shift or a working day. Initial-units that belong to different models are successively fed onto the conveyor at a given cycle time length to get into the assembling operations as semi-products. The conveyor moves semi-products to pass through the workstations to gradually complete the assembling operations for generating finished-products. A set of warehouses stores finished-products, and each model has a specified warehouse. Customers arrive at the warehouses to demand finished-products at stochastic demand forms. A daily scheduling task is the determination of the sequence that specifies the feeding order of the models, which must be set out at the beginning of each day. This paper deals with a new goal, " sequence-to-customer" , with stochastic customer demands. An optimization problem is formulated with the objective of minimizing the system cost that includes the holding cost for finished-products and the penalty cost for backordered customers during a decision horizon. A lower bound of the system cost is found, which is useful in verifying the optimality of any solution. A heuristic algorithm is proposed to solve the optimization problem, which can obtain optimal solutions or near-optimal solutions with almost ignorable relative errors to optimal solutions. By using the algorithm, the behavior of the system cost with respect to the variation in customer dema nds is also investigated to provide insights into management of an MMAL.

... Later on, the objective proposed in Bolat and Yano (1992b) is the minimization of the number of total special units exceeding the k permitted in sequential parts of size l. The authors develop a sequencing procedure, which provides optimal solutions under certain conditions. ...

A variant of the mixed-model sequencing problem on assembly lines is the one proposed by Yano and Rachamadugu in 1991. They consider time windows in workstations and the work overload concept-sum of differences between real completion time in the workstation and due dates, which depends on the time window value. This paper proposes some procedures for solving the problem, and compares them with others taken from literature using two computational experiments. (c) 2007 Elsevier B.V. All rights reserved.

... Bard et al. [6], Xiaobo and Ohno [7], and Tamura et al. [8] further extended this work by incorporating`realincorporating`real-worlda variants into this problem . Bolat and Yano [9,10] and Bolat [11] address sequencing problems where addressing setup and utility costs is a subject of concern. Ghosh and Gagnon [12] and Yano and Bolatt [13] provide extensive literature reviews of this relevant body of literature. ...

A technique is presented which addresses a JIT production-scheduling problem where two objectives are present – minimization of setups between differing products and optimization of schedule flexibility. These two objectives are inversely related to each other, and, as a result, simultaneously obtaining desirable results for both is problematic. An efficient frontier approach is employed to address this situation, where the most desirable sequences in terms of both objectives are found. Finding the efficient frontier requires addressing the combinatorial complexity of sequencing problems. The artificial neural network approach of a Kohonen self-organizing map (SOM) is used to find sequences which are desirable in terms of both the number of setups and flexibility. The Kohonen SOM was used to find sequences for several problems from the literature. Experimental results suggest that the SOM approach provides near-optimal solutions in terms of the two objectives, in addition to comparing formidably with other search heuristics. Results also show, however, that the SOM approach performs poorly with regard to CPU time.

... Nevertheless, due to the complexity of the problem, heuristic approaches are more common than exact methods to minimize work overload and other sequencing objectives. Some of these heuristics consider not only the minimization of work overload [37, 38, 8, 9, 4], but multiple objectives [39, 21, 15]. Also, meta-heuristics ([35] minimize work overload, or [30] minimize conveyor stoppage time), multi-objective meta-heuristics ([17] minimize utility work, keep a constant rate of part usage and minimizing setup cost with genetic algorithms; [19] keep a constant rate of part usage, smooth production load and minimize setup times with simulated annealing; [31] minimize utility work cost, product rate variation cost and setup cost with a memetic algorithm), hybrid multi objective heuristics ([25] minimize utility work, production rate variation and setup cost), and beam search ([16] part-usage variation and load leveling) have been developed. ...

We address a mixed-model assembly-line sequencing problem with¡ the goal of minimizing work overload. We consider time windows in work stations of the assembly line (closed stations) and different versions of a product to be assembled in the line (e.g., automotive industry), which require different processing time according to the work required in each work station. In a paced assembly line, products are feeded in the line at a predetermined constant rate (cycle time). Then, if many products with processing time greater than cycle time are feeded consecutively, work overload can be produced when the worker have insufficient time to finish his/her job. We propose a scatter search based hyper-heuristic for this NP-hard problem. In the low-level, the procedure implies the use of priority rules through a constructive procedure. We compare the hyper-heuristic with other classical heuristic approaches in order to know how competitive it can be. Computational results shows the efficiency of the hyper-heuristic and the relevance of some of the rules considered.

Industry trends such as product customization, radical innovation, and local production, accelerate the adoption of mixed‐model assembly lines that can cope with a widening gap between model processing times and true build to order capabilitiy. The existing high work content deviations on such assembly lines stress production planning, especially the assembly line sequencing. Most manufacturers set the launching rate for all assembly line products to a fixed launching rate resulting in rising utility work and idle time when system load increases. We present an “ideal” variable rate launching case resulting in minimal computation and achieving 100 percent productivity (full elimination of ilde time and utility work) for balanced assembly times and homogenous station lengths. Managers should foster the ideal circumstances where operators need not wait for a preceding task to be completed and product sequence restrictions are eliminated. Thus, enabling un‐matched production flexibility. Furthermore, we present a mixed‐integer model to analyze both closed and open workstations on a mixed‐model assembly line for fixed and variable rate launching. This model incorporates costs not only for labor inefficiencies but also for extending the line length. We present a heuristic solution method when process times and station lengths are heterogeneous and demonstrate that the variable takt dominates the fixed takt. In a numerical, industrial benchmark study, we illustrate, that a variable rate launching strategy with open stations has significantly lower labor costs as well as a substantially reduced total line length and thus lower throughput time. This article is protected by copyright. All rights reserved

Just-in-sequence material supply is the status quo in the automotive industry. In this process, the assembly sequence of vehicles is set several days prior to production, and communicated to the suppliers. The committed sequence is essential for efficient operations both at the original equipment manufacturer and its suppliers. In practice, however, sequence stability is insufficient. Short-term disruptions, such as quality problems and missing parts, put the sequence at risk. If a disruption occurs, the affected vehicle is removed from the sequence. The resulting gap is closed by bringing the succeeding vehicles forward. Such sequence alterations, however, cause workload changes and potentially work overloads at the assembly stations. As a remedial measure, additional sequence alterations are necessary, which further disturb material supply. Robustness against short-term sequence alterations is currently a key objective of automotive manufacturers.
In this paper, we propose a sequencing approach that includes the vehicles’ failure probabilities in order to generate robust sequences. Robust sequences are sequences that can be operated without modifications, even when vehicles fail. We develop a branch-and-bound algorithm that optimally solves small-sized instances. For large-sized instances, we design a sampling-based adaptive large neighborhood search heuristic. The superiority of our approach is validated in a simulation study using real-world data from a major European manufacturer. We find reductions in the expected work overloads of 72% and 80%, compared to the industry solution, and compared to an approach taken from literature which does not take failures into account.

This paper considers the problem of sequencing mixed-model assembly lines (MMALs). Our goal is to determine the sequence of products to minimise work overload. This problem is known as the MMAL sequencing problem with work overload minimisation: we explicitly use task operation times to find the product sequence. This paper is based on an industrial case study of a truck assembly line. In this industrial context, as a reaction to work overloads, operators at the workstations finish their tasks before the product reaches the next workstation, but at the expense of fatigue. Furthermore, there are different types of operators, each with different task responsibilities. The originality of this work is to model this new way of reacting against work overloads, to integrate three operator types in the sequencing model and to apply the developed methods in a real industrial context. To solve this problem, we propose three meta-heuristic procedures: genetic algorithm, simulated annealing and a combination of these two meta-heuristics. All the methods proposed are tested on industrial data and compared to the solutions obtained using a mixed-integer linear programme. The results show that the proposed methods considerably improve the results of the current procedure used in the case study.

La secuenciación de unidades en líneas de montaje de productos mixtos puede atender a diversos criterios; uno de ellos es el que consiste en minimizar la sobrecarga o trabajo perdido. En el presente trabajo proponemos heurísticas para el caso general con n variantes de un producto y m estaciones de trabajo y probamos la eficiencia de dichos procedimientos a través de una experiencia computacional.

Assembly lines are flow-oriented production systems, which gained an important practical role. One of the most important optimization problems for assembly line control is the sequencing problem, which usually aims to minimize work overload situations. The car sequencing problem minimizes work overload situations indirectly with sequencing rules. These rules restrict the maximum occurrence of options, which cause high processing times, in a subsequence of a certain length. Only few approaches exist on how to derive such sequencing rules. In this paper methods are presented which solve some problems of already presented rule generation approaches. One extension is the consideration of production rates for feasibility checks of generated sequencing rules and another extension is the selection of real options instead of virtual options. Furthermore, all presented strategies are applied on real world data.

Assembly lines are flow-oriented production systems, which gained an important practical role. One of the most important optimization problems for assembly line control is the sequencing problem, which usually aims to minimize work overload situations. The car sequencing problem minimizes work overload situations indirectly with sequencing rules. These rules restrict the maximum occurrence of options, which cause high processing times, in a subsequence of a certain length. Only few approaches exist on how to derive such sequencing rules. In this paper a novel multi-staged optimization approach is introduced for the selection of characteristic combination of options ('or' and 'and' links are used) for a specific subset of orders (for example all orders with a processing time higher than the cycle time). Three different (linked) MIP-models and various pre-processing strategies are presented. Furthermore, all presented strategies are applied on real world data with really good results in runtime and solution quality.

In this paper, the problem of sequencing mixed model assembly lines (MMAL) is considered. Usually MMAL consists of a number of workstations linked by a conveyor belt and each workstation has a work zone limited by upstream and downstream boundaries. We consider different models of products to be scheduled in the MMAL to meet the demand plan. In case of work overload, the operator has to rush or reinforcement workers assist him to finish the job on time. Our goal is to determine the sequence of products to minimize the work overload. This problem is known as the mixed model assembly line sequencing problem with work overload minimization (MMSP-W). This work is based on an industrial case study of a truck assembly line. We propose an exact method based on dynamic programming approach to solve the proposed problem. The limits of this optimal procedure are demonstrated with numerical tests. We then propose heuristics to solve the problem through extensions of the exact method. A comparison between the proposed heuristics and the exact method is studied. Numerical tests are carried out on academic instances from the literature and on industrial case study instances.

The paper deals with the two most important mathematical models for sequencing products on a mixed-model assembly line in order to minimize work overload the mixed-model sequencing (MMS) model and the car sequencing (CS) model. Although both models follow the same underlying objective, only MMS directly addresses the work overload in its objective function. CS instead applies a surrogate objective using so-called sequencing rules which restrict labor-intensive options accompanied with the products in the sequence. The CS model minimizes the number of violations of the respective sequencing rules, which is widely assumed to lead to minimum work overload. This paper experimentally compares CS with MMS in order to quantify the gap in the solution quality between both models. The paper studies several variants of CS with different sequencing rule generation approaches and different objective functions from the literature as well as a newly introduced weighting factor. The performance of the different models is evaluated on a variety of random test instances. Although the objectives of CS and MMS are positively linearly correlated, results show that a sequence found by CS leads to at least 15% more work overload than a solution found by MMS. For none of the considered test instances and for none of the three different objective functions, CS is able to produce competitive results in terms of solution quality (work overload) compared to MMS. The results suggest that decision makers using CS should investigate whether MMS would lead to better sequencing orders for their specific instances.

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.

Under a Just-In-Time (JIT) pull system the sequencing of products requires the satisfaction of two main goals: (1) keeping a constant rate of usage of parts, and (2) smoothing the workload at work stations to avoid line stoppages. By using a practical observation related to JIT delivery systems we propose a two-step approach, where in the first step we consider only goal (1) by applying a benchmark heuristic. In the second step we focus on goal (2), by investigating the effectiveness of a spacing-constraint based approach, commonly used in the automotive industry, in comparison with a more general time-based one. We designed and conducted a simulation experiment based on the practical situation of final assembly lines and we found that the benchmark heuristic represents an appropriate choice for step one (based on a new performance measure that represents a lower bound on variation in parts utilization). For the second step, related to workload smoothing, the spacing-constraint based method presents better achievement than the time-based one.

Just-in-time (JIT) is a pull concept applied mainly in repetitive manufacturing systems, and it is characterized by a scenario where only the required units are produced in the required quantities at the required times. It particularly aims at eliminating wastes associated with inventories in the system. A level schedule is desirable for a JIT assembly system, as it serves as an approximation for all forms of smoothing. The min-sum formulation of the assembly line level schedule problem is one of those that has been mainly used in the literature. Using this formulation as a base, we develop some useful structural properties for the problem. Among other things, it is shown that a level schedule would tend to be more difficult to achieve for products (models) with comparatively fewer units in the products composition structure.

In this manuscript, we present a formulation for the MMSP-W (Mixed model sequencing problem with workload minimisation) for production lines with serial workstations. We demonstrate the validity of the basic models in the presence of a control system on the production line that allows the stopping of operations with no restrictions. We propose an extension of the basic models that allows conditioned interruption of operations to facilitate line management. We then propose a procedure to solve the proposed problem through BDP (Bounded Dynamic Programming), and demonstrate its validity through a computational experiment with reference instances and a case study linked to the Nissan powertrain plant in Barcelona.

In this paper, the problem of sequencing mixed-model assembly lines in case of fixed rate launching and closed stations is considered. The problem consists of finding an intermixed sequence of different models of a basic product, which are jointly produced on an assembly line, such that customer demands are fulfilled and total work overload is minimized. For solving this problem an informed tabu search procedure with a pattern based vocabulary building strategy is developed. Computational tests demonstrate that considerable improvements are obtained by comparison to methods which do not incorporate such an approach.

Manufacturers in a wide range of industries nowadays face the challenge of providing a rich product variety at a very low cost. This typically requires the implementation of cost efficient, flexible production systems. Often, so called mixed-model assembly lines are employed, where setup operations are reduced to such an extent that various models of a common base product can be manufactured in intermixed sequences. However, the observed diversity of mixed-model lines makes a thorough sequence planning essential for exploiting the benefits of assembly line production. This paper reviews and discusses the three major planning approaches presented in the literature, mixed-model sequencing, car sequencing and level scheduling, and provides a hierarchical classification scheme to systematically record the academic efforts in each field and to deduce future research issues.

The mixed-model sequencing problem is to sequence different product models launched down an assembly line, so that work overload at the stations induced by direct succession of multiple labor-intensive models is avoided. As a concept of clearing overload situations, especially applied by Western automobile producers, a team of cross-trained utility workers stands by to support regular workforce. Existing research assumes that regular and utility worker assemble side-by-side in an overload situation, so that processing speed is doubled and the workpiece can be finished inside a station's boundaries. However, in many real-world assembly lines the application of utility workers is organized completely different. Whenever it is foreseeable that a work overload will occur in a production cycle, a utility worker takes over to exclusively execute work whereas the regular worker omits the respective cycle and starts processing at the successive workpiece as soon as possible. The paper investigates this more realistic sequencing problem and presents a binary linear program along with a complexity proof. Then, different exact and heuristic solution procedures are introduced and tested. Additional experiments show that the new model is preferable from an economic point of view whenever utility work causes considerable setup activities, e.g., walking to the respective station.

Mixed-model assembly lines are of great practical relevance and are widely used in a range of industries, such as the final assembly of the automotive and electronics industries. Prior research mainly selected and discussed isolated problems rather than considering the whole planning process. In this article mixed-model production planning is decomposed into five steps: initial configuration of the line, master scheduling, reconfiguration planning, sequencing and resequencing. The paper reviews and discusses all relevant planning steps and proposes general planning instruments as well as formalized decision models for those steps, which have not been thoroughly investigated in the literature thus far.

In this article we address the problem of sequencing jobs for one station on a paced assembly line with no buffers, at which two types of operations can be performed. We develop optimal solution procedures for three of four mutually exclusive and collectively exhaustive problem subclasses, with the goal of minimizing total utility work. For the fourth subclass, we evaluate heuristics that are structurally similar to the optimal procedures for the other subclasses. We provide worst-case error bounds for one of these procedures. Computational results indicate that very good, and often optimal, results can be obtained with a combination of these procedures.

We address the problem of sequencing jobs, each of which is characterized by one of a large number of possible combinations of customer-specified options, on a paced assembly line. These problems arise frequently in the automotive industry. One job must be launched into the system at equal time intervals, where the time interval (or cycle time) is prespecified. The problem is to sequence the jobs to maximize the total amount of work completed, or equivalently, to minimize the total amount of incomplete work (or work overload).
Since there is a large number of option combinations, each job is almost unique. This fact precludes the use of existing mixed model assembly line sequencing techniques. We first consider the sequencing problem for a single station which can perform two different sets of operations. We characterize the optimal solution for this problem and use the results as the basis for a heuristic procedure for multiple stations. Computational results with data from a major automobile company are reported.