Optimum assembly line balancing: A stochastic programming approach

Assembly line balancing problem is an approach of assigning a set of tasks to an ordered sequence of workstations. This assignment needs to be made in such a way that the underlying precedence constraints are not violated and efficiency measures are optimized subject to the restriction of the cycle time constraint. Research works, reported so far, mainly deal with the minimization of balancing loss, subject to precedence constraints. Lack of uniqueness in those optimum solutions and pressing demand to include system loss in the objective function have led to the present work of minimization of both balancing and system loss. As there is no standard measure for system loss, the current work proposes a measure for system loss and offers solution to this bi-objective problem

A Survey on Cost and Profit Oriented Assembly Line Balancing

http://www.nt.ntnu.no/users/skoge/prost/proceedings/ifac2014/media/files/0866.pdfInternational audienceProblems, approaches and analytical models on assembly line balancing that deal explicitly with cost and profit oriented objectives are analysed. This survey paper serves to identify and work on open problems that have wide practical applications. The conclusions derived might give insights in developing decision support systems (DSS) in planning profitable or cost efficient assembly lines

Balancing and Sequencing of Mixed Model Assembly Lines

Assembly lines are cost efficient production systems that mass produce identical products. Due to customer demand, manufacturers use mixed model assembly lines to produce customized products that are not identical. To stay efficient, management decisions for the line such as number of workers and assembly task assignment to stations need to be optimized to increase throughput and decrease cost. In each station, the work to be done depends on the exact product configuration, and is not consistent across all products. In this dissertation, a mixed model line balancing integer program (IP) that considers parallel workers, zoning, task assignment, and ergonomic constraints with the objective of minimizing the number of workers is proposed. Upon observing the limitation of the IP, a Constraint Programming (CP) model that is based on CPLEX CP Optimizer is developed to solve larger assembly line balancing problems. Data from an automotive OEM are used to assess the performance of both the MIP and CP models. Using the OEM data, we show that the CP model outperforms the IP model for bigger problems. A sensitivity analysis is done to assess the cost of enforcing some of the constraint on the computation complexity and the amount of violations to these constraints once they are disabled. Results show that some of the constraints are helpful in reducing the computation time. Specifically, the assignment constraints in which decision variables are fixed or bounded result in a smaller search space. Finally, since the line balance for mixed model is based on task duration averages, we propose a mixed model sequencing model that minimize the number of overload situation that might occur due to variability in tasks times by providing an optimal production sequence. We consider the skip-policy to manage overload situations and allow interactions between stations via workers swimming. An IP model formulation is proposed and a GRASP solution heuristic is developed to solve the problem. Data from the literature are used to assess the performance of the developed heuristic and to show the benefit of swimming in reducing work overload situations

Best matching processes in distributed systems

The growing complexity and dynamic behavior of modern manufacturing and service industries along with competitive and globalized markets have gradually transformed traditional centralized systems into distributed networks of e- (electronic) Systems. Emerging examples include e-Factories, virtual enterprises, smart farms, automated warehouses, and intelligent transportation systems. These (and similar) distributed systems, regardless of context and application, have a property in common: They all involve certain types of interactions (collaborative, competitive, or both) among their distributed individuals—from clusters of passive sensors and machines to complex networks of computers, intelligent robots, humans, and enterprises. Having this common property, such systems may encounter common challenges in terms of suboptimal interactions and thus poor performance, caused by potential mismatch between individuals. For example, mismatched subassembly parts, vehicles—routes, suppliers—retailers, employees—departments, and products—automated guided vehicles—storage locations may lead to low-quality products, congested roads, unstable supply networks, conflicts, and low service level, respectively. This research refers to this problem as best matching, and investigates it as a major design principle of CCT, the Collaborative Control Theory. The original contribution of this research is to elaborate on the fundamentals of best matching in distributed and collaborative systems, by providing general frameworks for (1) Systematic analysis, inclusive taxonomy, analogical and structural comparison between different matching processes; (2) Specification and formulation of problems, and development of algorithms and protocols for best matching; (3) Validation of the models, algorithms, and protocols through extensive numerical experiments and case studies. The first goal is addressed by investigating matching problems in distributed production, manufacturing, supply, and service systems based on a recently developed reference model, the PRISM Taxonomy of Best Matching. Following the second goal, the identified problems are then formulated as mixed-integer programs. Due to the computational complexity of matching problems, various optimization algorithms are developed for solving different problem instances, including modified genetic algorithms, tabu search, and neighbourhood search heuristics. The dynamic and collaborative/competitive behaviors of matching processes in distributed settings are also formulated and examined through various collaboration, best matching, and task administration protocols. In line with the third goal, four case studies are conducted on various manufacturing, supply, and service systems to highlight the impact of best matching on their operational performance, including service level, utilization, stability, and cost-effectiveness, and validate the computational merits of the developed solution methodologies

Balancing parallel assembly lines with disabled workers

[EN] In this paper, we study an assembly line balancing problem that occurs in sheltered worker centres for the disabled, where workers with very different characteristics are present. We are interested in the situation in which complete parallel assembly lines are allowed and name the resulting problem as parallel assembly line worker assignment and balancing problem (PALWABP). This approach enables many new possible worker-tasks assignments, what is beneficial in terms of both labour integration and productivity. We present a linear mixed-integer formulation and two heuristic solution methods: one is based on tabu search and the other is a biased random-key genetic algorithm (BRKGA). Computational results with a large set of instances recently proposed in the literature show the advantages of allowing such alternative line layouts.This research was supported by CAPES-Brazil and MEC-Spain (coordinated project CAPES DGU 258-12/PHB2011-0012-PC) and by FAPESP-Brazil. The authors thank Dr. Marcus Ritt, from Universidade Federal do Rio Grande do Sul (UFRGS - Brazil), for providing the optimal solutions for the serial ALWABP. The authors also thank three anonymous reviewers for their comments which have helped improve this paper.Araujo, FFB.; Costa, AM.; Miralles Insa, CJ. (2015). Balancing parallel assembly lines with disabled workers. European J of Industrial Engineering. 9(3):344-365. https://doi.org/10.1504/EJIE.2015.069343S3443659

Two extensions for the ALWABP: Parallel stations and collaborative approach

[EN] In this article, we introduce two new variants of the ALWABP that allow parallelization of and collaboration between heterogeneous workers. These new approaches suppose an additional level of complexity in the Line Design and Assignment process, but also higher flexibility; which may be particularly useful in practical situations where the aim is to progressively integrate slow or limited workers in conventional assembly lines. We present linear models and heuristic procedures for these two new problems. Computational results show the efficiency of the proposed approaches and the efficacy of the studied layouts in different situations.This research was supported by CAPES-Brazil and MEC-Spain (coordinated project CAPES-DGU 258-12/PHB-0012-PC) and by FAPESP-Brazil. We also thank the project ‘‘CORSARI MAGIC DPI2010-18243’’ of the Ministerio de Ciencia e Innovación del Gobierno de España within the Program ‘‘Proyectos de Investigación Fundamental No Orientada’’.Araujo, FF.; Costa, AM.; Miralles Insa, CJ. (2012). Two extensions for the ALWABP: Parallel stations and collaborative approach. International Journal of Production Economics. 140(1):483-495. https://doi.org/10.1016/j.ijpe.2012.06.032S483495140

A Multi-Objective Particle Swarm Optimization for Mixed-Model Assembly Line Balancing with Different Skilled Workers

This paper presents a multi-objective Particle Swarm Optimization (PSO) algorithm for worker assignment and mixed-model assembly line balancing problem when task times depend on the worker’s skill level. The objectives of this model are minimization of the number of stations (equivalent to the maximization of the weighted line efficiency), minimization of the weighted smoothness index and minimization of the total human cost for a given cycle time. In addition, the performance of proposed algorithm is evaluated against a set of test problems with different sizes. Also, its efficiency is compared with a Simulated Annealing algorithm (SA) in terms of the quality of objective functions. Results show the proposed algorithm performs well, and it can be used as an efficient algorithm. This paper presents a multi-objective Particle Swarm Optimization (PSO) algorithm for worker assignment and mixed-model assembly line balancing problem when task times depend on the worker’s skill level. The objectives of this model are minimization of the number of stations (equivalent to the maximization of the weighted line efficiency), minimization of the weighted smoothness index and minimization of the total human cost for a given cycle time. In addition, the performance of proposed algorithm is evaluated against a set of test problems with different sizes. Also, its efficiency is compared with a Simulated Annealing algorithm (SA) in terms of the quality of objective functions. Results show the proposed algorithm performs well, and it can be used as an efficient algorith

A STUDY ON GENERAL ASSEMBLY LINE BALANCING MODELING METHODS AND TECHNIQUES

The borders of the assembly line balancing problem, as classically drawn, are as clear as any other operations research topic in production planning, with well-defined sets of assumptions, parameters, and objective functions. In application, however, these borders are frequently transgressed. Many of these deviations are internal to the assembly line balancing problem itself, arising from any of a wide array of physical or technological features in modern assembly lines. Other issues are founded in the tight coupling of assembly line balancing with external production planning and management problems, as assembly lines are at the intersection of multiple related problems in job sequencing, part flow logistics, worker safety, and quality. The field of General Assembly Line Balancing is devoted to studying the class of adapted and extended solution techniques necessary in order to model these applied line balancing problems. In this dissertation a complex line balancing problem is presented based on the real production environment of our industrial partner, featuring several extensions for task-to-task relationships, station characteristics limiting assignment, and parallel worker zoning interactions. A constructive heuristic is developed along with two improvement heuristics, as well as an integer programming model for the same problem. An experiment is conducted testing each of these new solution methods upon a battery of testbed problems, measuring solution quality, runtime, and achievement of feasibility. Additionally, a new method for measuring a secondary horizontal line balancing objective is established, based on the options-mix paradigm rather than the customary model-mix paradigm

Equilibrado de líneas de montaje de productos voluminosos

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