Big Chemical Encyclopedia

Chemical substances, components, reactions, process design ...

Articles Figures Tables About

Process data

Feed/Products Feed Naphtha Light Cyde Oil Bottoms [Pg.198]


The model is meant to be relatively open to the evolution of NDT techniques. Thus, a normal evolution of the standard is to include, in future revisions, as "standard devices" some devices which have proved to be of current use. Two other axes of evolution are the handling of processed data and of simulated data. [Pg.927]

Core GIF Used for archiving and exchanging raw and processed data and derived... [Pg.121]

It is necessary to pre-process data by mean-centering, scaling or autoscaling... [Pg.224]

This chapter briefly discusses the advantages to be gained from the use of transputers in acquiring and processing data from an instrument like a mass spectrometer, which routinely deals with large-scale input and output at high speed. [Pg.311]

Obtain real-time process data confirm process models... [Pg.129]

In the past the successful operation of batch processes depended mainly on the skill and accumulated experience of the operator. This operating experience was difficult to codify in a form that enabled full use to be made of it in developing new designs. The gradual evolution of better instmmentation, followed by the installation of sequence control systems, has enabled much more process data to be recorded, permitting maintenance of process variations within the minimum possible limits. [Pg.299]

In object-oriented systems, the notion of inheritance is important. Inheritance means that a property of a class is automatically acquired by subclasses and objects of that class. Eor instance, having defined all the classes and objects Hsted above, if the property TIMESTAMP has to be added to all process data objects, one simply has to add it to the class PROCESS DATA. This modification would be automatically reflected in all subclasses and objects. [Pg.535]

Transfer function models are linear in nature, but chemical processes are known to exhibit nonhnear behavior. One could use the same type of optimization objective as given in Eq. (8-26) to determine parameters in nonlinear first-principle models, such as Eq. (8-3) presented earlier. Also, nonhnear empirical models, such as neural network models, have recently been proposed for process applications. The key to the use of these nonlinear empirical models is naving high-quality process data, which allows the important nonhnearities to be identified. [Pg.725]

The cost of capital may also be considered as the interest rate at which money can be invested instead of putting it at risk in a manufacturing process. Let us consider the process data listed in Table 9-4 and plotted in Fig. 9-10. If the cost oi capital is 10 percent, then the appropriate discounted-cash-flow curve in Fig. 9-10 is abcdef. Up to point e, or 8.49 years, the capital is at risk. Point e is the discounted breakeven point (DEEP). At this point, the manufacturing process... [Pg.812]

Process data Sp. gr. of feed liquid = 1.0 TDS (total dissolved solids) in feed liquid = 4.0 wt % fresh water used for washing vacuum level = 18 in Hg final cake liquid content = 25 wt %. [Pg.1704]

Magnitudes of /cg, /cp, /c, and indicate the importance of direct reactions with coal, where and are for hydrocracking reactions in the conversion process. Data for and from the experiments with HPO indicate that oil production from coal is increased by the use of a good hydrogen donor solvent. [Pg.2373]

May, D.L. and J.T Payne, Validate Process Data Automatically, Chemical Engineeiing, 1992, 112-116. (Validation)... [Pg.2545]

Rosenberg, J., R.S.H. Mah, and C. lordache, Evaluation of Schemes for Detecting and Identifying Gross Errors in Process Data, Indushial and Engineeiing Chemistiy, Reseaieh, 26(.3), 1987, 555-564. (Simulation studies of various detection methods)... [Pg.2545]

D.L. and J.T. Payne, Validate Process Data Automatically, Chemical Engineering, June 1992, 112-116). If a measurement is clearly inconsistent with equipment operation that is known to be true, the measurement must then be deemed suspect. Vahdation is the procedure of comparing a measurement to one or more of the following. [Pg.2566]

Figure 2.27 Statistical process data for dimension A of the cover support leg... Figure 2.27 Statistical process data for dimension A of the cover support leg...
BIOCHEMICAL UNIT MAIN PROCESS DATA LINE PHYSIOLOGICAL... [Pg.877]

The nuclear equipment failure rate database has not changed markedly since the RSS and chemical process data contains information for non-chemical process equipment in a more benign environment. Uncertainty in the database results from the statistical sample, heterogeneity, incompleteness, and unrepresentative environment, operation, and maintenance. Some PSA.s use extensive studies of plant-specific data to augment the generic database by Bayesian methods and others do not. No standard guidance is available for when to use which and the improvement in accuracy that is achieved thereby. Improvements in the database and in the treatment of data requires, uhstaiui.il indu.sinal support but it is expensive. [Pg.379]

You need an improvement system that causes improvement opportunities to be identified. Relying on chance encounters will not create the conditions needed for continuous improvement. The data that needs to be analyzed will be generated by a particular process and this process governed by particular documented procedures. By having already placed instructions in these procedures for certain data to be transmitted to your data analysts, you can cause opportunities to be identified. Other opportunities that are less dependent on product or process data may arise from the audit process and particular projects such as benchmarking, customer and supplier surveys. [Pg.112]

The object of a process control system is to make economic and sound decisions about the actions affecting the process. Data concerning the variations in process performance are collected and analyzed and decisions taken as to whether action on the process is or is not necessary to maintain production of conforming product (see Figure 9.1). However, process control and process capability are not one and the same, as illustrated in Figure 9.5. [Pg.366]

Your corrective action procedures need to cover the collection and analysis of product nonconformity reports and the collection and analysis of process data to reveal process nonconformities. The corrective action provisions of your internal audit procedure need to address the causes of the nonconformities and you will need an additional procedure to deal with external audits, investigating the cause of any nonconformities and recording the results. The procedure also needs to cover the investigation of customer complaints as the previous requirement only deals with the handling of complaints. [Pg.457]

FIGURE 7.5 Data for Process Data Recording System... [Pg.307]

These include identification of process equipment and instruments, interpretation of the meaning of their values and trends, navigation through different VDU pages by means of a selection menu, etc. The common feature of these tasks is handling the display system to search and locate relevant process data. In this respect, "classical" ergonomics checklists (see Chapter 4) are very useful in facilitating performance of such tasks. [Pg.328]

Some Data on the Reliability of Pressure Chemical Process Data derived from 1.4x10 vessel-year Process pressure vessels, pressure storage 44. [Pg.41]

Used to present the heat and material balance of a process. This may be in broad block form with specific key points delineated, or in more detailed form identifying essentially every flow, temperature and pressure for each basic piece of process equipment or processing step. This may and usually does include auxiliary services to the process, such as steam, water, air, fuel gas, refrigeration, circulating oil, etc. This type of sheet is not necessarily distributed to the same groups as would receive and need the piping flowsheet described next, because it may contain detailed confidential process data. [Pg.5]

Some companies do not allow the use of this sheet in their work primarily because of the confidential nature of some of the.process data. Wliere it is used, it presents a concise summary of the complete process and key mechanical data for assembly. This type of sheet requires more time for complete preparation, but like all engineering developments preliminary issues are made as information is available. Often the sheet is not complete until the piping and other detailed drawings are finished. This then is an excellent record of the process as well as a work sheet for training operators of the plant. [Pg.5]

The schedule sheet which summarizes the key reference data for a particular class of equipment such as pumps, but contains no process data. The latter type is prepared for job coordination with and in the various departments, i.e., engineering, construction, purchasing, production. It primarily serves for the construction period but, of course, does have lasting cross-reference value. [Pg.30]

In some cases, they may be anticipated by a knowledge of the status of the process data prior to the start of engineering acthity. The larger projects are somewhat easier to group than the smaller ones. Process engineering is not always handled as completely for the small jobs. This is to say that flowsheets may be simplified, detailed equipment and line schedules may not be required, and the over-all project can be completely visualized at the outset, which is not the case with large projects. [Pg.41]

To properly rate and design this type of unit, the process data should be submitted to the manufacturer, because adequate published correlation literature is not available. [Pg.229]

The steps in developing such a database are (1) collection of machine and process data and (2) database setup. Input requirements of the software are machine and process specifications, analysis parameters, data filters, alert/alarm limits, and a variety of other parameters used to automate the data-acquisition process. [Pg.713]


See other pages where Process data is mentioned: [Pg.887]    [Pg.309]    [Pg.322]    [Pg.418]    [Pg.80]    [Pg.531]    [Pg.534]    [Pg.743]    [Pg.2545]    [Pg.2545]    [Pg.2572]    [Pg.161]    [Pg.101]    [Pg.279]    [Pg.328]    [Pg.160]    [Pg.8]    [Pg.1012]    [Pg.11]    [Pg.211]    [Pg.697]   
See also in sourсe #XX -- [ Pg.390 , Pg.554 , Pg.584 ]

See also in sourсe #XX -- [ Pg.140 ]




SEARCH



AR(2) Process Data

Accelerator mass spectrometry data processing

Acquisition and Use of Process Design Data

Adsorption isotherms data processing

Automatic processing of standard data

Automation data processing

Based Data Processing

Biomedical Data Processing

Capital-cost data for processing plants

Cellulose processing data

Characteristics of Data Processing for Industrial Process Modeling

Chemical processing interpreting data

Chromatography data processing

Coal liquefaction process, data

Coherence during data processing

Column chromatography data processing

Common Data Processing System

Comparison of Process Technology Data for Bioreactors

Complex systems data processing

Computer, control data processing

Computers for data processing

Computers, mass spectral data processing

Core data management processes

Crystallography data processing

Cyclic voltammetry data processing

DATA PROCESSING IN 2D NMR

Data Analysis and Signal Processing

Data Process and Analysis

Data Processing Architecture for Target Tracking

Data Processing Issues

Data Processing and Assessment

Data Processing and Bioinformatics

Data Processing and Reporting

Data Processing in Bottom-Up Hydrogen Exchange Mass Spectrometry

Data The Prozac Approval Process

Data acquisition and processing

Data acquisition process

Data acquisition, transmission and processing. Survey networks

Data analysis continuous polymer process

Data collection and processing

Data collection chemical processing industry

Data conditioning process

Data extension different process conditions

Data fitting process

Data management process

Data mining process

Data mining process elements

Data mining process illustrative example

Data normalization process

Data pre-processing

Data process status

Data processing

Data processing

Data processing algorithms

Data processing and information management models

Data processing baseline correction

Data processing crystal lattice determination

Data processing detectors

Data processing for

Data processing geometry

Data processing methods

Data processing peak detection

Data processing phase correction

Data processing procedure

Data processing service center

Data processing software

Data processing software Biomap

Data processing software baseline correction

Data processing software implementation

Data processing spectra)

Data processing steps

Data processing system

Data processing systems 738 INDEX

Data processing techniques

Data processing techniques (digitized infrared

Data processing theory, parameters

Data processing, levels

Data processing/reduction

Data storage and processing unit

Data tape, processing

Data, acquisition processing

Data, format processing

Data-generation process

Data-processing parameters

Data-processing problems

Data-processing techniques microstructure studies

Decision-making process data sources

Depth resolution data processing

Detection, sensitivity and data processing

Developing data processing procedure

Dielectric relaxation data processing

Digital data processing

Discussion of Data for Specific Processes and Species

Drying process data examples

Dynamic data post processing

Electron data processing

Electronic data processing

Electronic nose data processing

Emission and consumption data from the continuous PA6 production process

Emission and consumption data from the textile yam process

Emission and consumption data of PET processing techniques

Enable processes data collection management

Entering the process data

Environmental data-generation process

Environmental processes, time series data

Epoxy processing data

Errors from data processing

Errors in data processing

Euclidean distance , data processing

Exact mass data processing

Example of Data Collection, Evaluation, and Processing

Experimental data processing, traditional

Experimental data processing, traditional approaches

Experiments and Data Processing

FllnS Data Processing and Verification

Fluid catalytic cracking data processing

Fourier transform data-processing techniques

Fourier transform infrared data processing

Fourier-transform infrared spectroscopy data-processing techniques

Frequency Domain Processing of NMR Data

Hierarchical classification, process data

High-performance liquid data processing

High-throughput ADME, automated data processing

How to Process ID and 2D NMR Data

Immunoassay data processing

Improved IE Accuracy from Data Post-Processing

Input analysis, process data

Input analysis, process data definition

Input analysis, process data example

Input analysis, process data filter

Input analysis, process data loadings

Input analysis, process data multivariate methods

Input analysis, process data steps

Input analysis, process data univariate methods

Input-output analysis, process data

Input-output analysis, process data regression

Instrument for Automatic Surface Tracking and Data Processing

Integrators data processing

Ion Detectors and Data Processing in MALDI-TOF Analyzers

Liquid crystal polymers processing data

Long data post processing

MA(3) Process Data

Magnetic data processing systems

Mass spectrometry data processing

Mass spectrometry imaging data processing

Maximum-likelihood method processing data

Mixing process data flow diagram

Multiple receivers data processing

Multiplexed data processing

Multivariate Data Processing

NMR Data Processing—Overview

National emissions inventory process data

Nuclear magnetic resonance data processing

Optical Data-Processing Devices

PIV Data Processing

PRELIMINARY DATA PROCESSING AND PHASE ANALYSIS

Panel level data processing

Peak area data processing

Performance data post processing

Peripherals data processing

Phenol-formaldehyde processing data

Physico-chemical data required for the design of near-critical fluid extraction process

Pilot plant data on processing

Plunger processing data

Polyacrylate processing data

Polyamide processing data

Polyethylene processing data

Polyethylene terephthalate processing data

Polymer data processing

Polymethyl methacrylate processing data

Polypropylene processing data

Polystyrene processing data

Polysulfone processing data

Polyvinyl chloride processing data

Practical Application of Investigation Data for Self-Ignition Processes

Prediction of Hepatic Efflux Process from In Vitro Data

Preliminary data processing

Principle of Atomic or Molecular Parameter-Data Processing Method

Process Behavior Charts (Technique attribute data

Process Behavior Charts (Technique variable data

Process Data Representation and Analysis

Process Equipment Data Bases

Process Equipment Data Sources

Process Modeling with Multiresponse Data

Process Modeling with Single-Response Data

Process automation data: Thermodynamic

Process control system Data Acquisition

Process control, automatic sampled data

Process data analysis

Process data interpretation

Process data sources

Process data, compression

Process data, qualitative/quantitative

Process design data

Process development compile data

Process development data

Process identification from plant data

Process real-time analytical data

Process trends data compression

Processing Spectroscopic Data

Processing and Analysis of ID NMR Data

Processing and Analysis of the NMR Data

Processing chromatographic data

Processing equilibrium sedimentation data

Processing experimental data

Processing of 2D NMR Data

Processing of mass spectral data

Processing of spectroscopic data

Processing the answers from raw to clean data

Processing, data errors

Protein data processing

Pulse Sequences and Data Processing

Quantitative data processing

Rate measurements experiments, data processing)

Raw data processing

Real-time data processing

Real-time optimization data processing

SVM Applied to Archeological Data Processing

Sedimentation data, processing velocity

Signal processing and data acquisition

Specific Data Processing

Stages of Data Processing

Static processing data from

Statistical process control data bounding

Statistical process control data collection

Styrene copolymers processing data

Support Vector Machine Data Processing Method for Problems of Small Sample Size

Tandem mass spectrometry data processing

Testing data from, processing

The Data Exchange Process

The Experimental Process and NMR Data of Total Synthesis

Time-domain spectroscopy data processing

Tools of the Trade VI. Ion Detection and Data Processing

Trace Element Science and Chemical Data Processing

Transient process data

Two dimensional NMR data processing

Two-Dimensional NMR Data-Processing Parameters

Understanding the FDA Data Collection Process

Vibrational spectroscopy data processing

Viruses data processing

X-ray data processing

Zircon data processing

© 2024 chempedia.info