Models for assembly line balancing by temporal, spatial and ergonomic risk attributes

Bautista, Joaquı́n; Batalla-García, Cristina; Alfaro-Pozo, Rocío

doi:10.1016/j.ejor.2015.12.042

Cited by 64 publications

(20 citation statements)

References 18 publications

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“…Indeed, we use a unified risk level classification proposed by Ref. 10 handling. Some tasks performed by workers involve the object lifting, movement, push, grip and transport, and therefore they may be physically harmful 14 .…”

Section: Incorporating Ergonomics Into the Tsalbpmentioning

confidence: 99%

“…However, in a latter paper, Ref. In line with the previous works 7,8,9,10,11 , this research seeks to maximize the comfort of an assembly line, considering the area and the time limitations. This assembly line comfort supposes: (1) minimizing, as far as possible, the maximum ergonomic risk of the line; and (2) 12 ), with those obtained by the MILP and the GRASP proposed in this paper to solve the model whose objective is minimize the ergonomic risk range of the line.…”

Section: Introductionmentioning

confidence: 99%

“…The second model is a specific case from the model 10 . Now, the model has a monoobjective function that aims at minimizing the discrepancy between real and ideal values for the ergonomic risk of the line, considering the temporal, spatial and ergonomic attributes.…”

Section: Minimization Of Average Absolute Deviations Of Ergonomic Riskmentioning

confidence: 99%

“…Section 3 reminds the mathematical model that minimizes the maximum ergonomic risk of the line 12 and presents a specific variant, of the optimization model proposed in Ref. 10, whose objective is to minimize the discrepancy between real and ideal values for the ergonomic risk. Section 4 contains the GRASPs used for the problem.…”

Section: Introductionmentioning

confidence: 99%

See 3 more Smart Citations

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

Bautista¹,

Alfaro-Pozo²,

Batalla-García³

2016

IJCIS

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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.

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Section: Incorporating Ergonomics Into the Tsalbpmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

Section: Minimization Of Average Absolute Deviations Of Ergonomic Riskmentioning

confidence: 99%

Section: Introductionmentioning

confidence: 99%

See 2 more Smart Citations

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

Bautista¹,

Alfaro-Pozo²,

Batalla-García³

2016

IJCIS

Self Cite

View full text Add to dashboard Cite

show abstract

“…On the basis of compatibility and adjustment functions defined by Bautista et al, (2016) and Batalla (2015), a new optimization model is proposed. The model considers the temporal, spatial and ergonomic attributes and its objective is to minimize the discrepancy between real and ideal values for the ergonomic risk of the line.…”

Section: Mathematical Modelmentioning

confidence: 99%

Comparative Models for Minimizing Ergonomic Risk in Assembly Lines

Valhondo

Batalla-García

Alfaro-Pozo

2017

Lecture Notes in Management and Industrial Engineering

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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).

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A bi‐objective ergonomic assembly line balancing model with conic scalarization method

Yetkin

Kahya

2022

Hum Ftrs & Erg Mfg Svc

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The most important factor affecting efficiency and ergonomic risk levels in an assembly line design is the problem of assigning certain tasks to certain stations, namely the assembly line balancing problem. In the literature, assembly line balancing problem has often been studied, but studies that consider ergonomic risks are deficient. Recently, it has been one of the issues that have started to attract great attention with the realization of health problems caused by assembly lines. To this end, in this study, a bi‐objective mathematical model is developed that considers balancing assembly line station time and ergonomic risk levels, simultaneously. It is aimed to minimize both station time and the total deviations of ergonomic risk scores for the stations. Weighted sum and conic scalarization methods are applied to solve the bi‐objective model. To analyze the outcomes of the developed model, an application is proposed and tested on a real industrial case, at a home appliance assembly line. The deployment of the OMAX method is a contribution to the literature since it shows an analysis tool which evaluates the results of assembly line balancing. This method evaluates the performance of the stations based on different criteria such as station time and ergonomic risk. The number of high‐risk stations is obtained as 13 in the single‐objective model aiming to minimize the station time, while it is found to be nine in the bi‐objective model solved with CSM, without an increase in the total number of stations.

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Models for assembly line balancing by temporal, spatial and ergonomic risk attributes

Cited by 64 publications

References 18 publications

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

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

Comparative Models for Minimizing Ergonomic Risk in Assembly Lines

A bi‐objective ergonomic assembly line balancing model with conic scalarization method

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