This study investigates the feasibility of remote quality control using a host of advanced automation equipment with Internet accessibility. Recent emphasis on product quality and reduction of waste stems from the dynamic, globalized and customer-driven market, which brings opportunities and threats to companies, depending on the response speed and production strategies. The current trends in industry also include a wide spread of distributed manufacturing systems, where design, production, and management facilities are geographically dispersed. This situation mandates not only the accessibility to remotely located production equipment for monitoring and control, but efficient means of responding to changing environment to counter process variations and diverse customer demands. To compete under such an environment, companies are striving to achieve 100%, sensor-based, automated inspection for zero-defect manufacturing. In this study, the Internet-based quality control scheme is referred to as "E-Quality for Manufacturing" or "EQM" for short. By its definition, EQM refers to a holistic approach to design and to embed efficient quality control functions in the context of network integrated manufacturing systems. Such system let designers located far away from the production facility to monitor, control and adjust the quality inspection processes as production design evolves.
The current trends in industry include integration of an information and knowledge base network with a manufacturing system, which coined a new term, E-Manufacturing. From the perspective of E-Manufacturing, any production equipment and its control functions do not exist alone, but become a part of the holistic operation system with distant monitoring and fault diagnostic capabilities. The key to this new paradigm is the accessibility to a remotely located system and having the means of responding to a changing environment. In this study, a new methodology in predicting a system output has been investigated by applying a data mining technique and a hybrid type II fuzzy system in CNC turning operations. The purpose was to generate a supplemental control function under the dynamic machining environment, where unforeseeable changes may occur frequently. Two different types of membership functions were developed for the fuzzy logic systems and also by combining the two types, a hybrid system was generated. Genetic algorithm was used for fuzzy adaptation in the control system. Fuzzy rules are automatically modified in the process of genetic algorithm training. The computational results showed that the hybrid system with a genetic adaptation generated a far better accuracy. The hybrid fuzzy system with genetic algorithm training demonstrated more effective prediction capability and a strong potential for the implementation into existing control functions.
There is a missing link between a virtual development environment (e.g., a CAD/CAM driven offline robotic programming) and production requirements of the actual robotic workcell. Simulated robot path planning and generation of pick-and-place coordinate points will not exactly coincide with the robot performance due to lack of consideration in variations in individual robot repeatability and thermal expansion of robot linkages. This is especially important when robots are controlled and programmed remotely (e.g., through Internet or Ethernet) since remote users have no physical contact with robotic systems. Using the current technology in Internet-based manufacturing that is limited to a web camera for live image transfer has been a significant challenge for the robot task performance. Consequently, the calibration and accuracy quantification of robot critical to precision assembly have to be performed on-site and the verification of robot positioning accuracy cannot be ascertained remotely. In worst case, the remote users have to assume the robot performance envelope provided by the manufacturers, which may causes a potentially serious hazard for system crash and damage to the parts and robot arms. Currently, there is no reliable methodology for remotely calibrating the robot performance. The objective of this research is, therefore, to advance the current state-of-the-art in Internet-based control and monitoring technology, with a specific aim in the accuracy calibration of micro precision robotic system for the development of a novel methodology utilizing Ethernet-based smart image sensors and other advanced precision sensory control network.
In today's global world, manufacturers are facing many challenges such as product design with distributed and collaborative workflows. Complexity in collaborative product design arises from the need to synthesize different perspectives of a problem. Specifically, dependency identification of the product design process, as well as integration and sharing of computing application among the design teams that are critical for efficiency of manufacturability. Web services are considered to be the key to collaborative product design through the Internet. Web services alone are passive whereas agents can provide alerts and updates when new information becomes available. In this paper, an agent-based Web services architecture is proposed and applied to augment manufacturability. Not only the agent-based Web services architecture makes system interoperation feasible, but also increases the efficiency of the distributed collaboration.
Conference Committee Involvement (1)
Intelligent Systems in Design and Manufacturing VI
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