Design and balancing of assembly lines that minimize ergonomic risk

Minimización del Riesgo ergonómico de la línea de motores de Nissan-BCN en función del número de estaciones de trabajo.In this paper, an assessment system of the ergonomic hazards existing in the workstations of an assembly line is provided. A mathematic model to solve the assembly line balancing problem is developed with the aim of minimizing the ergonomic risk that exists in an assembly line by taking into account the number of workstations and a set of temporal and spatial restrictions. This model has been applied, by means of a computational experiment, in a problem taken from a case study of Nissan’s engine plant in Barcelona. The experiment measures the impact that the increase in the number of workstations causes on the improvement of the ergonomic quality of such workplaces and on the reduction of the ergonomic risk.Preprin

Delimiting the linear area on the problems of assembly line balancing with minimal ergonomic risk

In this paper we propose to incorporate some working conditions to the assembly lines. For this, used a mathematical model to solve the assembly line balancing problem whose objective is minimizing the ergonomic risk, imposing the limitation of the cycle time, number of workstations and the maximum linear area for each station. A study is presented through a case study that corresponds to an assembly line from Nissan’s plant in Barcelona.Postprint (published version

Reducing physical ergonomic risks at assembly lines by line balancing and job rotation: A survey

Factors such as repetitiveness of work, required application of forces, handling of heavy loads, and awkward, static postures expose assembly line workers to risks of musculoskeletal disorders. As a rule, companies perform a post hoc analysis of ergonomic risks and examine ways to modify workplaces with high ergonomic risks. However, it is possible to lower ergonomic risks by taking ergonomics aspects into account right from the planning stage. In this survey, we provide an overview of the existing optimization approaches to assembly line balancing and job rotation scheduling that consider physical ergonomic risks. We summarize major findings to provide helpful insights for practitioners and identify research directions

Maximizing comfort in Assembly Lines with temporal, spatial and ergonomic attributes

We aim at maximizing the comfort of operators in mixed-model assembly lines. To achieve this goal, we evaluate two assembly line balancing models: the first that minimizes the maximum ergonomic risk and the second one that minimizes the average absolute deviations of ergonomic risk. Through a case study we compare the results of the two models by two different resolution procedures: the Mixed Integer Linear Programming (MILP) and Greedy Randomized Adaptive Search Procedures (GRASP). Although linear programming offers best solution, the results given by GRASPs are competitive.Peer ReviewedPostprint (author's final draft

Comparative models for minimizing ergonomic risk in assembly lines

We present a new mathematical model for the assembly line balancing problem with the objective of maximizing the line comfort to operators. Besides minimizing discrepancies between the ergonomic risks of workstations, balancing is subject to temporal and spatial conditions for the workstations. To evaluate the performance of the proposed model, we compare it with other mathematical model whose objective is minimizing the maximum ergonomic risk of a mixed-model assembly line. To compare the models, a case study linked to Nissan’s engine plant in Barcelona (NMISA, Nissan Motor Ibérica – BCN).Postprint (published version

A case study at the Nissan Barcelona factory to minimize the ergonomic risk and its standard deviation in a mixed-model assembly line

This work examines a balancing problem wherein the objective is to minimize both the ergonomic risk dispersion between the set of workstations of a mixed-model assembly line and the risk level of the workstation with the greatest ergonomic factor. A greedy randomized adaptive search procedure (GRASP) procedure is proposed to achieve these two objectives simultaneously. This new procedure is compared against two mixed integer linear programs: the MILP-1 model that minimizes the maximum ergonomic risk of the assembly line and the MILP-2 model that minimizes the average deviation from ergonomic risks of the set of workstations on the line. The results from the case study based on the automotive sector indicate that the proposed GRASP procedure is a very competitive and promising tool for further research.Peer ReviewedPostprint (published version

Minimizing the ergonomic risk and its dispersion in a mixed model assembly line using GRASP

Postprint (author's final draft

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