Over the past years, we have been steadily expanding our knowledge in production planning and scheduling for highly automated manufacturing environments. Building on earlier work and in collaboration with Eindhoven University of Technology (TU/e), we focused on one of the key challenges of autonomous production: efficiently scheduling parallel machines that can operate without direct supervision, while accounting for tool changes and fixture constraints. The result is the publication of a new paper: “A genetic algorithm for scheduling an automated machine cell with tool and pallet-fixture setups”. Read more [Picture source: KMWE on linkedin.com]
