Most fixed automations in traditional manufacturing systems are not equipped to manage product variations efficiently. This paper presents a design and configuration for a machine-vision-equipped robotic packing cell that is capable of managing a wide range of product sizes. Product size information is gathered at an earlier stage in the manufacturing process and then transferred electronically to the robot cell. Different controllers are needed to manage robot cell functions related to incoming product, machine vision, robot control, robot manipulator, and multiple layers of safety control information. Each controller, due to the nature of its function, has different advantages in processing different data types. In order to achieve the highest possible robot manipulator utilization rate, the assignment of information processing among controllers needs to be thoughtfully planned, especially for the critical mathematical routines. Coordination and calibration between charged-coupled device (CCD) cameras and robots in existing manufacturing facilities are configured with considerations for building vibrations, lighting conditions, and signal processing assignments among the available devices. System efficiency is improved when the vision signal, robot logical signal, and robot manipulator signal processing units are running cohesively in parallel. The capability of the machine-vision-assisted robot end effector automatic path adjustment, to pick up and pack different sizes of products dynamically, allows a higher level of flexibility and efficiency. This paper describes a feasible design and configuration for an integrated machine vision robotic cell in a manufacturing system.
Colored timed Petri net based statistical process control and fault diagnosis to flexible manufacturing systems
