COMPUTER AIDED QUALITY

Guided by the quality plan, the computer-aided quality inspection and quality data collection receive quality data during different phases. The phases include purchased-mateiial and part-quality inspection, part-production-quality data collection, and final-assembly quality inspection. The methods and techniques used in quality inspection and data collection are discussed in special books on quality control (Taguchi et al. 1990). 

Integrated quality system, see Computer-aided quality-management system Integrated simulation, 320 Integrated solutions business model, 603 Integrated system, creation of, 1009-1010 Integration ... 

Because traditional testing, such as melt flow index, ash content and tensile testing, may not provide enough information to avoid processing defects, the more complete analysis is desirable. Here, the data is entered into a computer aided quality (CAQ) system for analysis and comparison with specifications. The decision tree utilized is typical of what might be used for this class of materials. This same approach can be used for failure analysis of these materials in the product. 

Figure 2. Flow diagram for control of incoming materials at a supplier to the automotive industry [9]. (CAQ = computer-aided quality) (With permission from Kunststoffe.)...

CAQ = computer aided quality assurance EDP = electronic data processing GLP = good laboratory practice LIMS = laboratory information management system QM = quality management. 

As there were no commercial LIMSs, they had to be developed. The first LIMSs mainly supported sample management, entry of results, and printing of reports. As they were able to manage quality assurance in laboratories and for production, sometimes such systems were called computer aided quality assurance (CAQ). The development of LIMSs is outlined in Table 1. 

Implementation of a Computer Aided Quality System (CAQ) in CIM Environment Advantages and Disadvantages... 

It takes time to train a film interpreter. In addition, human interpretation of weld quality based on film radiography is very subjective, inconsistent, labour intensive, and sometimes biased. It is thus desirable to develop some forms of computer-aided systems. 

This paper describes the development of a novel system for improving the quality of information provided by manual ultrasonic examination of welds, while retaining the flexibility of the human operator to apply the techniques to components of a wide range of geometries and dimensions. The system, known as CamuS (Computer Aided Manual UltraSonics) provides assistance to the manual operator in two separate areas ... 

The correct interpretation of measured process data is essential for the satisfactory execution of many computer-aided, intelligent decision support systems that modern processing plants require. In supervisory control, detection and diagnosis of faults, adaptive control, product quality control, and recovery from large operational deviations, determining the mapping from process trends to operational conditions is the pivotal task. Plant operators skilled in the extraction of real-time patterns of process data and the identification of distinguishing features in process trends, can form a mental model on the operational status and its anticipated evolution in time. 

The excellent, high-resolution y- and X-ray spectra which can be obtained from semiconductor detectors make the detectors very important in modern instruments. A typical spectrum is shown in Figure 10.11(b) which may be compared with the much broader peaks from a scintillation detector (Figure 10.11(a)). The spectra are not immune from the problem of Compton scattering (p. 461) but a good quality modem detector will have a photopeak to Compton peak ratio of 50 1 or better. Computer-aided spectrum analysis also serves to reduce the interference from the Compton effect. 

With the advent of computer-aided-drug modeling (CADM) the critical, scientific and faster approach to newer drug entities based on the biologically active prototypes, combinatorial chemistry, chiral chemistry and biotechnology has paved the way towards more specific, potent and above all less toxic drugs to improve the ultimate quality of life in humans. 

Despite these problems EST databases are a valuable source of large-scale analysis of human variation. They will become even more valuable as the data continue to grow at the present rate. An algorithm for computer-aided SNP mining should contain filters to eliminate the potential sequence errors. Such filters can be based on the probabilistic analysis of sequence features. It can also take into account that multiple occurrences of a variant are more trustworthy, and it may furthermore focus on improving the quality of base-calling if the fluorescent traces are available for closer srcutiny. 

Bayesian regression to improve the quality of the model. J. Comput.-Aided Mol. Des. 1998, 12, 503-519. 

Computer-aided trend identification offers potential benefits, but is dependent on the quality of the input information. Expert systems and artificial intelligence are tools being tested. When successful, they may give improved insight into identifying common causes and trend analyses. 

Wang, M.H.S. Wang, L.K. Simmons, T. Bergenthal, J. Computer-aided air quality management. J. Environ. Mgnt. 1979, 9, 61-87. 

The grade determines whether the mica can be used in high technology elecironic instruments, e.g.. computer-aided tomography (CATl scan, or in low technology devices, e.g.. a toaster. Many types of insulators, as well as the base for electronic circuits, are formed from the high quality sheets of mica by a punch pressing operation. 

In this work, we have demonstrated that modern QSPR modeling methods are becoming an important tool for computer-aided designs of new metal binders. Further developments depend not only on new data-mining techniques and descriptors applied, but also on the quality of the experimental data used for the training and validation of the models. Thus, both theoretical and experimental chemists should make an effort to build a basis for predictive structure-property modeling that will accelerate the development of target molecules and materials. 

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