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Process sequencing for a pick-and-place robot in a real-life flexible robotic cell

Abstract

Robots are used in manufacturing cells for wide purposes including pick and place of the items from a location to a destination. As far as the authors’ knowledge in this context, the scheduling problem of a real-life flexible robotic cell (FRC) with intermediate buffers is missing in the literature. Therefore, in this study, the process-sequencing problem of a real-life FRC is considered, aiming to minimize the cyclic operation time of the cell. The problem is mathematically modeled and solved for a real case. Since computation times for solving the problems rise exponentially with increasing the number of machines in the FRC, a genetic, a simulated annealing, and a hybrid genetic algorithms are proposed to solve the large-sized problems. The objective function value of a given solution in metaheuristic algorithms is computed by solving a linear programming model. After tuning the parameters of the proposed algorithms, several numerical instances are solved, and the performance of these algorithms are evaluated and compared. The results show that the performance of the hybrid genetic algorithm was significantly better than both genetic and simulated annealing algorithms.

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Abbreviations

CNC:

Computer numerical control

FRC:

Flexible robotic cell

GA:

Genetic algorithm

HGA:

Hybrid genetic algorithm

MIP:

Mixed integer programming

RC:

Robotic cell

SA:

Simulated annealing

α :

The coefficient for temperature modifications

t a :

The completion time of activity a

C :

The cycle time

T f :

The final temperature

T 0 :

The initial temperature

M i :

The ith machine in the FRC

L ik :

The loading of the kth item on machine i in each cycle

T i ab :

The lower bound of dab for machine i

Iter max :

The maximum number of iterations in GA

N :

The number of iterations in SA

m :

The number of machines in the FRC

Pop :

The number of population

P c :

The probability of crossover

P m :

The probability of mutation

p :

The processing time for an item on any machine

w ab :

The robot waiting time between ta and tb

L i :

The set of loading activities of machine i in each cycle

U i :

The set of unloading activities of machine i in each cycle

ε :

The time for just picking/placing an item from/to the input/output buffer, or any machine

d ab :

The time of performing activity b after finishing activity a, by the robot

δ :

The travel time of the robot between two consecutive station

U ik :

The unloading of the kth item from machine i in each cycle

x ab :

1, if the robot performs activity b immediately after activity a; 0, otherwise

z ik :

1, if the kth order is applied for the activities of machine i; 0, otherwise

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Correspondence to Reza Vatankhah Barenji.

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Ghadiri Nejad, M., Shavarani, S.M., Güden, H. et al. Process sequencing for a pick-and-place robot in a real-life flexible robotic cell. Int J Adv Manuf Technol 103, 3613–3627 (2019). https://doi.org/10.1007/s00170-019-03739-6

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Keywords

  • Flexible robotic cell
  • Cyclic scheduling
  • Manufacturing cell
  • Metaheuristic