Effective Scheduling of Multi-Load Automated Guided Vehicle in Spinning Mill: A Case Study

Parkavi Krishnamoorthy, N. Satheesh, D. Sudha, Sudhakar Sengan, Meshal Alharbi, Denis A. Pustokhin, Irina V. Pustokhina, Roy Setiawan

Research output: Contribution to journalArticlepeer-review

1 Citation (Scopus)


In the Flexible Manufacturing System (FMS), where material processing is carried out in the form of tasks from one department to another, the use of Automated Guided Vehicles (AGVs) is significant. The application of multiple-load AGVs can be understood to boost FMS throughput by multiple orders of magnitude. For the transportation of materials and items inside a warehouse or manufacturing plant, an AGV, a mobile robot, offers extraordinary industrial capabilities. The technique of allocating AGVs to tasks while taking into account the cost and time of operations is known as AGV scheduling. Most research has exclusively addressed single-objective optimization, whereas multi-objective scheduling of AGVs is a complex combinatorial process without a single solution, in contrast to single-objective scheduling. This paper presents the integrated Local Search Probability-based Memetic Water Cycle (LSPM-WC) algorithm using a spinning mill as a case study. The scheduling model's goal is to maximize machine efficiency. The scheduling of the statistical tests demonstrated the applicability of the proposed model in lowering the makespan and fitness values. The mean AGV operating efficiency was higher than the other estimated models, and the LSPM-WC surpassed the different algorithms to produce the best result.

Original languageEnglish
Pages (from-to)9389-9402
Number of pages14
JournalIEEE Access
Publication statusPublished - 2023
Externally publishedYes


  • Manufacturing system
  • automated guided vehicles
  • computer integrated manufacturing
  • makespan
  • spinning mill
  • water cycle algorithm


Dive into the research topics of 'Effective Scheduling of Multi-Load Automated Guided Vehicle in Spinning Mill: A Case Study'. Together they form a unique fingerprint.

Cite this