Assembly lines with mixed products present ergonomic risks that can affect productivity of workers and lines. Because of that, the line balancing must consider the risk of injury in regard with the set of tasks necessary to process a product unit, in addition to other managerial and technological attributes such as the workload or the space. Therefore, in this paper we propose a new approach to solve the assembly line balancing problem considering temporal, spatial and ergonomic attributes at once. We formulate several mathematical models and we analyze the behavior of one of these models through case study linked to Nissan. Furthermore, we study the effect of the demand plan variations and ergonomic risk on the line balancing resultPeer ReviewedPostprint (author's final draft

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.

One of the major issues in industrial environments is currently maximizing productivity while reducing manufacturing cost. This can be seen clearly reflected in mixed-model assembly lines based systems, where obtaining efficient manufacturing sequences is a key to be competitive in a dynamic and globalized market. However, this continuous cost reduction and productivity growth should not penalize the welfare of employees. This work is intended to address this lack of compatibility between the economic and social objectives through the study of the mixed-model sequencing problem from both the business and labor perspective. This is done by considering the possibility of reducing or increasing processing times of operations by varying the work pace of line's operators within the permissible legal boundaries. Thus, depending on this flexible activation time of operators, the amount of completed work and idle time will be one or the other and, consequently, the productivity of the line will also improve or get worse. In this regard, we propose new approach to the sequencing problem without incurring cost increases and providing a safe working environment, in accordance with applicable law. This new approach leads to obtain efficient manufacturing sequences, in terms of both productivity and labor conditions. Specifically, the objective of the new problem is minimizing the unproductive costs of the line by incorporating the possibility of increasing production through the variation of the work pace of line's operators. Increasing the work pace of operators, the amount of non-completed work or the preventable idle time can be reduced and therefore, their associated costs too. In addition, and without losing sight of the effort involved in working with a work pace above the normal, we propose several economic criteria to compensate the activation of workers where necessary.

No abstract

Abstract.A linear program-assisted hybrid algorithm (GRASP-LP) is presented to solve a mixed-model sequencing problem in an assembly line. The issue of the problem is to obtain manufacturing sequences of product models with the minimum work overload, allowing the free interruption of operations at workstations and preserving the production mix. The implemented GRASP-LP is compared with other procedures through a case study linked with the Nissan' Engine Plant from Barcelona.Keywords: GRASP; Linear programming; Sequencing; Mixed-model assembly lines: Production mix preservation PreliminariesFlexibility is the paradigm of the vast majority of the current production systems. Today production systems must be able to manufacture different versions of a product without physical changes at modules or workstations and with negligible setup times between different-type consecutive units; furthermore, they must respond quickly to any variation in the production plan. For this reason flexibility is what makes it important the sequencing problem.This flexibility is crucial at many manufacturing sectors, such as the Automotive, where production is carried on mixed-model assembly lines and the product mix changes frequently. This leads to the two main problems of this type of assembly lines: the balancing problem and the sequencing problem.Balancing problem appears in first place and it consists of assigning efficiently the set of assembly tasks for a product into the set of workstations arranged in series. The resulting line's configuration must meet the coherent order of tasks, and the set of restrictions linked with the task-attributes, such as the processing time, the required space and the involved risk [1].Once the line is configured and the demand plan is defined, the sequencing problem appears. This problem focuses on determining the manufacturing order of prod-