PROCESS SEQUENCING FOR A PICK-AND-PLACE ROBOT IN A REAL-LIFE FLEXIBLE ROBOTIC CELL

Mazyar Ghadiri Nejad, Seyed Mahdi Shavarani, Hüseyin Güden, Reza Vatankhah Barenji

Research output: Contribution to journalArticlepeer-review

Abstract

Robots are used in manufacturing cells for wide purposes including pick and place of the items from a location to a destination. In this study, the process-sequencing problem of a real-life flexible robotic cell 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 algorithm 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 showed that the performance of the hybrid genetic algorithm was significantly better than both genetic and simulated annealing algorithm.
Original languageEnglish
JournalInternational Journal of Advanced Manufacturing Technology
Early online date7 May 2019
DOIs
Publication statusE-pub ahead of print - 7 May 2019

Keywords

  • Flexible robotic cell
  • Robotic cell
  • Cyclic Scheduling
  • Metaheuristic

Fingerprint

Dive into the research topics of 'PROCESS SEQUENCING FOR A PICK-AND-PLACE ROBOT IN A REAL-LIFE FLEXIBLE ROBOTIC CELL'. Together they form a unique fingerprint.

Cite this