Intelligent instruments

ICP-OES is one of the most successful multielement analysis techniques for materials characterization. While precision and interference effects are generally best when solutions are analyzed, a number of techniques allow the direct analysis of solids. The strengths of ICP-OES include speed, relatively small interference effects, low detection limits, and applicability to a wide variety of materials. Improvements are expected in sample-introduction techniques, spectrometers that detect simultaneously the entire ultraviolet—visible spectrum with high resolution, and in the development of intelligent instruments to further improve analysis reliability. ICPMS vigorously competes with ICP-OES, particularly when low detection limits are required. 

It should be capable of monitoring and controlling as wide a range of process devices as possible, including intelligent instruments and sensors, and should be able to log and retrieve large amounts of process data. 

Additionally, use of a commercial AI shell for expert system development has been demonstrated without the need to learn computer programming languages (C, Pascal, LISP or any of its variations), nor to have an intermediary knowledge engineer. Although this development effort of 4-5 man months was on a minicomputer, adaptation of EXMAT to the microcomputer version of TIMM is anticipated. The completed implementation of EXMAT will support the belief that AI combined with intelligent instrumentation can have a major impact on future analytical problem-solving. 

In general, it appears that expert systems which combine symbolic/numeric processing capabilities are necessary to effectively automate decision-making in applications involving analytical and process instrumentation/sensors. Furthermore, these integrated decision structures will likely be embedded (67-69) within the analytical or process units to provide fully automated pattern recognition/correlation systems for future intelligent instrumentation. 

The cost of an intelligent instrument can be twice that of the equivalent device without the smart facility (the latter is termed a dumb instrument)(99). However, the use of a smart transmitter does generally improve the inherent accuracy of the sensor itself. 

Barney, G. C. Intelligent Instrumentation, 2nd edn (Prentice-Hall, Englewood Cliffs, New Jersey, 1988). 

The young scientific discipline Chemometrics has rapidly developed in the past two decades. This enormous increase was initiated by advances in intelligent instruments and laboratory automation as well as by the possibility of using powerful computers and user-friendly software. So, chemometrics became a tool in all parts of quantitative chemistry, but particularly in the field of analytical chemistry. Nowadays, the analyst is increasingly faced with the need to use mathematical and statistical methods in his daily work. 

A trend to more complex problems and the availability of automated instruments are novel aspects of modern scientific research. When complex problems are investigated it is usually necessary to characterize an object (e.g. a sample, a reaction, a fact) not only by one parameter (measurement, feature) but by several parameters. The aim of the investigation is often to obtain a better insight into the treated problem, rather in a qualitative than in a quantitative manner. In chemistry such demands for an exploratory data analysis frequently arise in connection with analytical work on complex samples, e.g. environmental samples and also in the field of structure-property-relationships. With modern, sometimes called intelligent, instruments a great amount of data can easily be obtained from samples. The bottle-neck in this work is the data interpretation. 

Data can be entered manually or acquired automatically from spectrum generating and spot reading instruments such as chromatographs, spectrophotometers, balances, pH meters and a wide variety of intelligent instrumentation. 

In other circumstances IPCs can be used to control intelligent instrumentation, analysis equipment, or small-scale prodnction units. The technology can be found as a ruggedized PC, a Windows terminal, panel-monnted, rack-mounted, or hand-held portable device, or as a portable terminal with radio freqnency communications. The term IPC here is treated as covering all these types of equipment. 

Hence, computers allow the ready automation of laboratory processes such as data acquisition and treatment, result delivery and process control. This great potential is further Increased by the possibility of linking computers to one another (intelligent instruments) and by the use of workstations, expert systems and data banks, ail of which are commented on In some detail below. 

Multifunctional, Adaptive materials Release from implanted drug depots as required Intelligent instruments... 

Biosensor advancement in the commercial world could also be accelerated by the use of intelligent instrumentation, electronics, and multivariate signal processing methods. Increasing attention must be paid to the engineering of both the basic components and the device as a whole. 

Intelligent instrumentation Barcode printers/readers Labeling systems Recipe Management Systems... 

Depending on the particular product, process and plant, the OCS will need to communicate to an extremely wide variety of devices. Experience in the 1990s suggests that these will include traditional PLC systems, intelligent instrumentation and other control systems (e.g., barcode readers, barcode printers, weigh and dispense systems, etc.). 

Much has been written about the use of Fieldbus in process industries over the years, and it is true to say that the use of so-called intelligent instrumentation and digital communications has provided some benefit to users. 

The major benefit to be realized from Fieldbus and intelligent instruments is primarily due to the ability to obtain on-line diagnostic information. This provides information on the performance of a control valve, for instance, or on the expected lifetime of a seal material based on the number of hours installed and the duty. These features lead to better planned maintenance (rather than preventative or run-to-breakdown maintenance), which in turn leads to lower overall maintenance costs and fewer unplanned losses of production. Validation of the on-line diagnostics will assist in the ongoing review of the validation status of the OCS. 

Many control systems fail to integrate Fieldbus instruments properly and cannot support the required data structures at all levels in the system. The modern OCS must be able to communicate with the intelligent instruments using whatever physical medium and protocol that the standard dictates, and the structure of the OCS must be able to pass the secondary attributes of the instrument to wherever the relevant software resides. This must be achieved without disrupting the real-time communications of the system and without corrupting the data structure which both the instrument and the associated software understands. 

An interface to the Fieldbus instruments, providing the OCS with the necessary data to perform supervisory control. Note that some control is performed at the level of the intelligent instruments themselves, and the control system downloads set points, monitors the control and records the various parameters. 

In the Fieldbus example, the Asset Management System converts the standard Fieldbus descriptor (in device descriptor language [DLL]) to a D-COM object. This is then passed to OCS where it is converted from D-COM into the OCS s own object model. This is so that the relevant parts of the Fieldbus device descriptor can be distributed to the various OCS nodes for display, trending, alarm purposes and so on. The OCS then uses its OMM to transfer the data to the OCS controller, where it is again converted to DLL format prior to sending across the Fieldbus link to the intelligent instrument. 

Voet. M. R. H, Vertongen, M. C. M., Boschmans. L. M. H.. and Mertens. M. M. J. (199.3), Overview of new damage techniques in composite materials for aeronautics using fibre optic sensors. Proc. Inter. Symp. on Intelligent Instrumentation for Remote and On-site Mcasurement.s. 6th TC-4 Symp.. pp. 127 132. 

Fig.l. Schematic layout of an intelligent instrument. 1. Sensors, 2. Actuators, 3. Input/output interface, 4. Microprocessor, 5. Memory, 6. Expert system shell, 7. Knowledge base, 8. External expert, 9. Periferals (VDU, printer, mouse etc.), 10. Microcomputer. 

Signals emanating from damage or faulty sensors will obviously cause enormous problems for intelligent instruments, so a facility for automatic sensor malfunction will be necessary in critical applications. Methods of doing this include ... 

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