A goal programming approach to mixed model assembly line balancing problem

Cataloged from PDF version of article.In this paper, a binary goal programming model for the mixed-model assembly line balancing (ALB) problem is developed. The model is based on the concepts developed by Patterson and Albracht [l] and the model of Deckro and Rangachari [2] developed for the single-model ALB problem. The proposed model provides a considerable amount of flexibility to the decision maker since several conflicting goals can be simultaneously considered

Balancing Lexicographic Multi-Objective Assembly Lines with Multi-Manned Stations

In a multi-manned assembly line, tasks of the same workpiece can be executed simultaneously by different workers working in the same station. This line has significant advantages over a simple assembly line such as shorter line length, less work-in-process, smaller installation space, and less product flow time. In many realistic line balancing situations, there are usually more than one objective conflicting with each other. This paper presents a preemptive goal programming model and some heuristic methods based on variable neighborhood search approach for multi-objective assembly line balancing problems with multi-manned stations. Three different objectives are considered, minimizing the total number of multi-manned stations as the primary objective, minimizing the total number of workers as the secondary objective, and smoothing the number of workers at stations as the tertiary objective. A set of test instances taken from the literature is solved to compare the performance of all methods, and results are presented

Optimization of A Real Time Multi Mixed Make-To-Order Assembly Line to Reduce Positive Drift

ThesisAssembly lines are critical for the realization of product manufacture. In recent times, there has been a shift from the make-to-stock (mass production) approach to a make-to-order (mass customization) approach and this has brought on a strong emphasis on product variety. Although variety can be included to a product at various phases of production, literature shows that by providing each functional module of the product with several variants, assembly lines provide the most cost-effective approach to achieve high product variety. However, there are certain challenges associated with using assembly lines to achieve product variety. One of these challenges is assembly line balancing. Assembly line balancing is the search for an optimum assignment of tasks, such that given precedence constraints according to pre-defined single or multi objective goal are met. These objectives include reducing the number of stations for a given cycle time or minimizing the cycle time for a given number of stations. Cycle time refers to the amount of time allotted to accomplish a certain process in an assembly process. This deviation from the optimal cycle time is technically referred to as drift. Drift can be negative or positive. Negative drift represents the time span during which an assembly line is idle, due to work being finished ahead of prescribed cycle time. Positive drift, meanwhile, represents time span in which an assembly line exceeds the prescribed cycle time. The problems caused by drift, especially positive drift, is so vast that there is a research niche are dedicated to this study called Assembly Line Balancing Problems. Various authors have proposed numerous solutions for solving assembly line balancing problems created by positive drift. However, there is very little information on optimizing multi model make-to order systems with real time inputs so as to reduce the effects of positive drift. This study looks at how such a system can be optimized by using the case study of a water bottling plant. This is done by initially looking at the literature in the field of assembly line balancing to isolate the research gap this study aims to fill. Secondly, the water bottling plant, described as the case study, is modelled using MATLAB/Simulink. Thirdly, the different optimization methodologies are discussed and applied to the created model. Finally, the optimized model is tested and the results are analysed. The results of this study show that positive drift, which can be a major challenge in a real time multi mixed assembly line, can be reduced by the optimization of assembly lines. The results of this study can also be seen as an addition to the knowledge base of the broader research on mixed model assembly line balancing

A Network Model for Parallel Line Balancing Problem

Gökçen et al. (2006) have proposed several procedures and a mathematical model on single-model (product) assembly line balancing (ALB) problem with parallel lines. In parallel ALB problem, the goal is to balance more than one assembly line together. In this paper, a network model for parallel ALB problem has been proposed and illustrated on a numerical example. This model is a new approach for parallel ALB and it provides a different point of view for interested researchers

Analysing and levelling manufacturing complexity in mixed-model assembly lines

In recent years, the automotive industry has witnessed a rapid increase in model variety and customization. New models, which are mainly being introduced in response to consumers demand, feature long lists of choices in terms of variants (engine model, comfort level, colour palette, etc.) and options (entertainment system, start/stop functionality, etc.). This high variability increases the complexity of factory processes and workstations and thus impacts directly upon the complexity of the manufacturing system as a whole. The shift from mass production to mass customized production is a trend that looks likely to continue in the foreseeable future, driven by automotive manufacturers' struggle to maintain market share in their traditional markets and seize market share in new, fast-growing markets. To cope with this intensified customization, automotive assembly platforms are designed to be capable of assembling a large range of relatively different models. That is they become mixed-model assembly lines. This implies that a high variety of tasks are to be performed at each workstation. As a consequence, the manufacturing complexity at these workstations increases. Mixed-model assembly lines are flow-line production systems that typically encounter the assembly line balancing problem (ALBP), a combinatorial optimization problem involving the optimal partitioning of assembly work among the workstations with a particular objective in mind. Subsequently, solving mixed-model assembly line balancing problems (MMALBPs) is much more complex than single-model cases, as workload must be smoothed for all workstations and all models in order to avoid overload or idle time. Despite the recent focus on manufacturing complexity and the extensive study of the ALBP, little research has explored how complexity can be applied to optimize line efficiency. Manufacturing complexity has been a key concern of many researchers and manufacturers in recent years, however, practical procedures to level complexity have not yet been considered and investigated when balancing the assembly lines. Analysing, measuring and monitoring complexity while creating line balancing solutions is a new and unexplored topic, especially when using real industry scenarios. In this dissertation, we propose an approach that can be used to monitor manufacturing complexity at each workstation while balancing the mixed-model assembly lines. The research carried out relies on an investigation of real MMAL's aiming to develop a deep analysis of complexity. The goal is to understand what and how complexity is generated, in order to cope and reduce the high complexity and its impacts in the line. During several visits and workshops carried out in collaboration with manufactures, we could observe that work load distribution is directly related with models variety, as tasks' time might differ from model to model. We first explored the existing scientific literature on the mixed-model assembly line balancing problem and manufacturing complexity in Chapter 2. Then, manufacturing complexity is investigated using two approaches: (1) an empirical analysis approach based on data collected in the Field and (2) a quantitative analysis approach measuring the level of uncertainty by means of entropy

Iterative Beam Search for Simple Assembly Line Balancing with a Fixed Number of Work Stations

The simple assembly line balancing problem (SALBP) concerns the assignment of tasks with pre-defined processing times to work stations that are arranged in a line. Hereby, precedence constraints between the tasks must be respected. The optimization goal of the SALBP-2 version of the problem concerns the minimization of the so-called cycle time, that is, the time in which the tasks of each work station must be completed. In this work we propose to tackle this problem with an iterative search method based on beam search. The proposed algorithm is able to obtain optimal, respectively best-known, solutions in 283 out of 302 test cases. Moreover, for 9 further test cases the algorithm is able to produce new best-known solutions. These numbers indicate that the proposed iterative beam search algorithm is currently a state-of-the-art method for the SALBP-2

Simple heuristics for the assembly line worker assignment and balancing problem

We propose simple heuristics for the assembly line worker assignment and balancing problem. This problem typically occurs in assembly lines in sheltered work centers for the disabled. Different from the classical simple assembly line balancing problem, the task execution times vary according to the assigned worker. We develop a constructive heuristic framework based on task and worker priority rules defining the order in which the tasks and workers should be assigned to the workstations. We present a number of such rules and compare their performance across three possible uses: as a stand-alone method, as an initial solution generator for meta-heuristics, and as a decoder for a hybrid genetic algorithm. Our results show that the heuristics are fast, they obtain good results as a stand-alone method and are efficient when used as a initial solution generator or as a solution decoder within more elaborate approaches.Comment: 18 pages, 1 figur