Catálogo de publicaciones - libros

In manufacturing, information acquired through integrated sensors can be used to increase flexibility, reliability, and accuracy of autonomous robotic systems. Furthermore, use of such sensors, as a means by which to implement flexible automation, can potentially diminish costs by reducing the need for customized and complex tooling often needed in non-programmable automation.

Robotic sensors can be categorized into three groups: medium-range and short-range proximity sensors (typically, for object recognition and/or position/orientation estimation) and contact sensors (typically, for force/torque measurements). This chapter focuses on the use of medium-range sensors; more specifically, the objective is the review of the state-of-the-art in autonomous active sensor networks.

Remote monitoring and control are crucial in decentralized manufacturing environments. This is evidenced by today’s distributed shop floors where agility and responsiveness are required to maintain high productivity and flexibility. However, there exists a lack of an effective system architecture that integrates remote condition monitoring and control of automated equipment. Addressing this problem, this chapter introduces a web-based and sensor-driven technique that bridges this missing link. A framework of (eb-based ntegrated ensor-driven ) was designed to realize such a concept. The conceptulization, architectural design, and system implementation are discussed in detail and two case studies on robot control and remote machining are presented. Enabled by Java and web technologies, demonstrates significant promise of intelligent distributed manufacturing.

This chapter describes a nanofabrication probe for surface displacement measurement and/or surface profile measurement. The probe is the combination of a fast-tool-control (FTC) cutting unit and a force sensor. The FTC cutting unit, which consists of a ring-type PZT actuator and a nanometer capacitance-type displacement sensor, is used for diamond turning of complex surface profiles. The force at the interface between the tip of the cutting tool and the surface can be detected by the force sensor with a sensitivity of 0.01 mN through employing an AC modulation technique. In the displacement/surface profile measurement mode, the surface is tracked by the tool through servo-control of the contact force by the FTCunit, in which the displacement/surface profile can be obtained from the capacitance-type displacement sensor. Probe design and evaluation are presented.

This chapter presents a summary of the distributed architecture-based IEEE 1451 suite of smart transducer interface standards for sensors and actuators. These standards specify communication protocols and transducer electronic data sheets (TEDS) for networked digital smart sensors and actuators, high-speed synchronized distributed multi-drop sensor systems, and wireless sensor interfaces. The concept of IEEE 1451 is based on a distributed architecture, which means intelligence is decentralized and is pushed down to the sensor module level. This arrangement is well suited for remote monitoring and control applications, such as condition-based maintenance (CBM). Machinery condition and health could affect machine performance, part quality, and productivity. Machinery Information Management Open Systems Alliance (MIMOSA) was organized to establish an open architecture and a set of protocols for exchanging complex sensor information between condition-based maintenance (CBM) systems. With the capability and wide availability of the Web, any sensor connected to a wired or wireless network can be accessed anywhere via the network or Internet. This will greatly enhance the effectiveness and application of machinery health monitoring and control in the manufacturing and production environments.

Integrated System Health Management (ISHM) describes a set of system capabilities that in aggregate perform: determination of condition for each system element, detection of anomalies, diagnosis of causes for anomalies, and prognostics for future anomalies and system behavior. The ISHM should also provide operators with situational awareness of the system by integrating contextual and timely data, information, and knowledge (DIaK) as needed. ISHM capabilities can be implemented using a variety of technologies and tools. This chapter provides an overview of ISHM contributing technologies and describes in further detail a novel implementation architecture along with associated taxonomy, ontology, and standards. The operational ISHM testbed is based on a subsystem of a rocket engine test stand. Such test stands contain many elements that are common to manufacturing systems, and thereby serve to illustrate the potential benefits and methodologies of the ISHM approach for intelligent manufacturing.