Data acquisition and management

Data management typically means normalization. Normalization software is available from several sources to help interpret RO operating data (see Chapters 11.3 and 12 for more detail about normalized data). Membrane manufacturers have normalization software that requires manual input of operating data, but that run the calculations. Some chemical and equipment vendors have software/ hardware packages that collect data and perform all the normalization calculations automatically. In general, RO control packages and PLCs do not come with normalization software. 

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In the data acquisition and management process, the user community and the user specifications need to be kept at the forefront. This is a crucial motivational factor, and the lack of it can often fatally damage monitoring programs. The cost of monitoring is so great, that continuing cost-user benefit tradeoffs for accuracy, precision by parameter days, and timeliness should be considered. 

Data acquisition and management RO skid frame Auxiliary equipment... 

A laboratory information management system (LIMS) is a computer or computer network used to automate the acquisition and management of raw analytical data. In its simplest form, it tracks samples and test results through analytical laboratories and provides summaries of the status of these samples and tests. In its most advanced form, the system is interfaced to the laboratory s instmmentation and communication network to allow automation of data gathering, compilation, and reporting. 

Historical data management—This includes the data acquisition and storage capabilities. Present-day prices of storage mediums have been dropping rapidly, and systems with 80 gigabyte hard disks are available. These disks could store a minimum of five years of one-minute data for most plants. One-minute data is adequate for most steady state operation, while start-ups and shutdowns or other non steady state operation should be monitored and stored at an interval of one second. To achieve these time rates, data for steady state operation can be obtained from most plant-wide D-CS systems, and for unsteady state conditions, data can be obtained from control systems. 

The laboratory should verify and document the proper functioning of the software immediately after any new data acquisition or management systems have been installed. The baseline verification consists of manual calculations to confirm the correctness of all computer calculations. Ongoing verification takes place during laboratory data review process whenever a reviewer replicates one of the results generated by the computer or a manual calculation from a bench sheet. All information used in the calculations (raw data, calibration data, laboratory QC checks, and blank results) is kept on file for the reconstruction of the final result at a later date, should it become necessary. Bench sheets that document sample preparation are also kept on file for the same purpose. 

It is noted several times in this book that the goal of experimental methodology is to provide optimum quality data for subsequent statistical analysis. This is true, but there is also a very important intermediary between data acquisition and data analysis this is the field of clinical data management. In many cases, Data Management and Statistics fall under the same division within a company, and in some cases these tasks are handled by different divisions. Whichever is the case, it is vital to have statisticians involved in all discussions regarding database development and use. 

The clear and practical approach adopted by the authors makes the book applicable to a wide audience. It will appeal particularly to those with a practical need (scientists, engineers, managers, research workers) who have completed their formal education but who still need to know efficient ways of carrying out experiments. It is also an ideal text for advanced undergraduate and graduate students following courses In chemometrics, data acquisition and treatment, and design of experiments. 

Regardless of the organization of the Data Acquisition and Archiving Subsystems, part of the information will come from automatic measurements of air and water pollution concentrations at a number of measurement stations, and from automatic water level gauges in individual river segments, which are of use for flood management. Because of considerable distances between measurement stations and data acquisition centers in this distributed system, the best solution for communication is a nationwide 2G cellular phone network, covering over 96% of the country s area. 

In this text the reader can find material related to computer-instrument-process communication, data acquisition and control, reliability of process control computer systems, management aspects of in-plant computer installations, and a large number of case studies. Additional general references on digital computers and their application in the real-time environment are the following ... 

Laboratory systems such as Laboratory Information Management Systems (LIMS) have also come under increased regulatory scrutiny as the complexity of the software they deploy has become more advanced. Currently, there are often two LIMS tiers of control, data acquisition and data processing, often implemented by two coupled LIMS applications. The data acquisition LIMS is likely, however, to disappear in the longer term as analytical... 

Computers (not built-in) are part of modern MIR spectrometer. The supplied software manages data acquisition and analysis. Additional software for chemometric evaluation is available. 

Most of the information management examples presented in this chapter are part of an application suite called PIVIT . PIVIT is an acronym for Performance Indicator Virtual Instrument Toolkit and is an easy-to-use data acquisition and analysis product. PIVIT was developed specifically in response to the wide array of information and analysis needs throughout the healthcare setting. 

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