By Richard Mahaffey
Computing and knowledge administration applied sciences contact our lives within the environments the place we are living, play and, paintings. excessive tech is turning into the traditional. these of use who paintings in a laboratory setting are confronted with an seen problem. How will we top observe those technol ogies to earn cash for our businesses? the 1st point of deliverable advantages is completed via job automation. the second one point is ob tained through integrating the person islands of automation. The 3rd, or most sensible point, of advantages is expounded to using intelligence to computing purposes. using computing know-how, at point one, to automate lab professional cedures, tools, and tools has been ecocnomic for a few years. we will be able to simply locate every year returns within the variety of 10-50% for investments at this point. For point , the combination of a few functions has developed and has resulted in facts administration platforms and native quarter web operating within the lab surroundings. funding paybacks at point are considerably greater, within the diversity of 200-400%. Examples of functions on the best point, that of clever structures and functions, are few and much among. And what in regards to the payback for investments at this point? With such restricted adventure at point 3, we will in basic terms estimate the advantages. yet back, they seem like a lot larger, within the diversity of 2000- 4000%.
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Even for those systems analysts using commercial database products, system integration was difficult. Database tools of the early- and mid1980s did not provide an easy way to integrate applications. When a new program needed to interface to an existing database, if the database didn't contain all the required new data fields (which was usually the case), a new database would have to be created containing the new fields and then all the data were copied from the old database. Because of the difficulty and complexity of integrating computer systems and then maintaining them, large support groups evolved throughout the 1970s and 1980s.
Mechanization has existed in the laboratory for a long time. With the advent of Large-Scale Integration (LSI) technology, we now have CPU s in many of lab instruments, allowing us to classify them as automated. The drive behind laboratory automation is always, without exception, enhanced productivity. Laboratory automation systems have increased productivity by providing benefits such as the following: (1) calculation and transcription errors associated with copying data values from one piece of paper to another are significantly reduced, (2) records of who did what, how and when it was done, and any subsequent modifications are maintained automatically, [and] (3) "the working day can be extended from 8 to 18 hours without mUltiple shifts or additional staff" (36).
New generations of laboratory instruments and new computer methods to automate old instruments are allowing us to process more samples with fewer personnel. Laboratory robots work three shifts a day turning out data and more data. In order to prevent a productivity bottleneck, we must computerize and automate data management and associated information management processes. The integration of collecting, processing, and communicating all laboratory information is the essence of the new technology.