Optimization of job scheduling for flexible manufacturing systems using ANOVA technique and artificial neural networks
摘要
FMS systems have evolved as an integral part of modern manufacturing, offering flexibility and adaptability in production. Job scheduling rules such as Critical Ratio and Slack/Remaining Operations have been employed to prioritize jobs. Optimization techniques, including Taguchi methods and ANOVA, help identify influential parameters. Automation, tool management, and layout design also contribute significantly to system efficiency. Overall, this review provides a foundation for the subsequent study’s exploration of optimization strategies in FMS.