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1.16.1 Spectralon Material Light Reflectance Calibration
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Spectralon reflectance standards (Fig. 1.24) are available individually and in sets consisting of a diffuse white standard and a selection of diffuse gray standards. Each is supplied with reflectance data from 250 nm to 2500 nm, in 50-nm increments. These durable, chemically
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FIGURE 1.24 Spectralon diffuse white standards provide the highest diffuse re ectance values of any known substance.
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FIGURE 1.25 Spectralon calibration material.
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inert, and washable standards have typical reflectance values of 95 to 99 percent and are spectrally flat over the UV-VIS-NIR spectrum. Spectralon SRM-99 reflectance material is the most Lambertian reflector available for use over the wavelength range from 250 2500 nm. All reflectance calibration tests are directly traceable to NIST (Fig. 1.25). It is used for calibrating: Densitometers Integrating sphere systems Optical equipment Photographic equipment Reflectometers Remote sensing Spectroscopy instruments
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Highest diffuse reflectance values of any known substance Durable, chemically inert, and washable standards Reflectance values of 95 99 percent Spectrally flat over the UV-VIS-NIR spectrum Data from 250 2500 nm, in 50-nm increments NIST traceable calibration
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Chappel, A. (ed.), Optoelectronics: Theory and Practice, McGraw-Hill, New York, 1978. Doebelin, E. O., Measurement Systems: Application and Design, 4th ed., McGraw-Hill, New York, 1990.
The Role of Sensors in the 21st Century
Holliday, D., and R. Resnick, Physics, Wiley, New York, 1975. International Organization for Standardization, Statistical Interpretation of Data: Comparison of Two Means in the Case of Paird Observations, ISO 3301 1975. Lion, K. L., Elements of Electrical and Electronic Instrumentation, McGraw-Hill, New York, 1975. Neubert, H.K.P., Instrument Transducers, 2d ed., Clarendon Press, Oxford, 1975. Ogata, K., Modern Control Engineering, 2d ed., Prentice-Hall, Englewood Cliffs, N.J, 1990. Rock, I., Lightness Constancy, Perception, W. H. Freeman, New York, 1984. Seippel, R. G., Optoelectronics, Reston Publishing Co., Reston, Va., 1981. Shortley, G., and D. Williams, Quantum Property of Radiation, Prentice-Hall, Englewood Cliffs, N.J., 1971. Todd, C. D. (Bourns Inc.), The Potentiometer Handbook, McGraw-Hill, New York, 1975. White, R. M., A Sensor Classification Scheme, IEEE Trans. Ultrasonics, Ferroelectrics, and Frequency Control, March, 1987.
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Classification and Types of Sensors
2.0 Introduction
Workstations, work cells, and work centers represent a coordinated cluster of a production system. A production machine with several processes is considered a workstation. A machine tool is also considered a workstation. Integrated workstations form a work cell. Several complementary workstations may be grouped together to construct a work cell. Similarly, integrated work cells may form a work center. This structure is the basic concept in modeling a flexible manufacturing system. The flexible manufacturing system is also the cornerstone of the computer-integrated manufacturing strategy (Fig. 2.1). The goal is to provide the management and project development team with an overview of major tasks to be solved during the planning, design, implementation, and operation phases of computerintegrated machining, inspection, and assembly systems. Financial and technical disasters can be avoided if a clear understanding of the role of sensors and control systems in the computer-integrated manufacturing strategy is asserted. Sensors are largely applied within the workstations and are the only practical means of operating a manufacturing system and tracking its performance continuously. Sensors and control systems in manufacturing provide the means of integrating different, properly defined processes as input to create the expected output. Input may be raw material and/or data that have to be processed by various auxiliary components such as tools, fixtures, and clamping devices. Sensors provide the feedback data to describe the status of each process. The output may also be data and/ or materials that can be processed by further cells of the manufacturing system. A flexible manufacturing system, which contains workstations, work cells, and work centers and is equipped with appropriate sensors and control systems, is a distributed management
FIGURE 2.1 Workstation, work cell, and work center.
information system, linking together subsystems of machining, packaging, welding, painting, flame cutting, sheet-metal manufacturing, inspection, and assembling with material-handling and storage processes. In designing various workstations, work cells, and work centers in a flexible manufacturing system within the computer-integrated manufacturing strategy, the basic task is to create a variety of sensors interconnecting different material-handling systems, such as robots, automated guided-vehicle systems, conveyers, and pallet loading and unloading carts, to allow them to communicate with data processing networks for successful integration with the system. Figure 2.2 illustrates a cell consisting of several workstations with its input and output, and indicates its basic functions in performing the conversion process, storing workpieces, linking material-handling systems to other cells, and providing data communication to the control system. The data processing links enable communication with the databases containing part programs, inspection programs, robot programs, packaging programs, machining data, and real-time control data through suitable sensors. The data processing links also enable communication of the feedback data to the upper level of the control hierarchy. Accordingly, the entire work-cell facility is equipped with current data for real-time analysis and fault recovery. A cluster of manufacturing cells grouped together for particular production operations is called a work center. Various work centers
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