Industrial process models maintenance

Soft sensors can be used for closed-loop control, but caution must be used to ensure that the soft-sensor model is applicable under all operating conditions. Presumably one would need to test any potential process condition to validate a soft-sensor model in the pharmaceutical industry, making their use in closed-loop control impracticable due to the lengthy validation requirements. An important issue in the use of soft sensors is what to do if one or more of the input variables are not available due, for example, to sensor failure or maintenance needs. Under such circumstances, one must rely on multivariate models to reconstruct or infer the missing sensor variable.45 A discussion of validating soft sensors for closed-loop control is beyond the scope of this book. 

System Architecture (CIMOSA), 301-302, 489 90, 507-509, 510-512 cube, CIMOSA, 511, 512 in process industry, 519 Computerized enterprise modeling, 303 Computerized maintenance management... 

Quality control laboratories may be equipped with instruments which indicate MW or MWD directly. The most common technique used for this purpose is gel permeation chromatography (GPC). Infrequent analysis is the rule. Such off-line measurements are most often used to update inferential models, or to effect open loop control of the polymerization by manual process adjustments based on GPC results. On-line GPC is available its application is not yet common in industrial practice, but applications of on-line measurement of MWD by GPC have been reported [26]. The difficulties encountered with on-line GPC are the maintenance, sampling and calibration problems associated with any process chromatography application. In addition, a compromise must be made between resolution of the MWD and time of analysis. As a rule of thumb, it is possible to determine an accurate average molecular weight in under 10 minutes. Determination of the MWD can take considerably longer. 

Limitations. The electrodeless conductivity technique using low-frecjuency inductive cells is available for analysis and control in the chemical process industries and in other continuous monitoring applications. Although its stability, freedom from maintenance, and accuracy, are superior to contacting conductivity techniques, lack of bench models of this type has hindered its laboratory use and application to date. 

What is OPC This is another tool for system integration. OPC is open connectivity in industrial automation for interoperability supported by the creation and maintenance of open standards and specifications. OPC is a standardized interface for accessing process data. Object linking and embedding (OLE), component object model (COM)/distributed component object model (DCOM), was developed by Microsoft. When this is applied to the process control, OPC (OLE for process control) is developed. OPC is based on the Microsoft COM/DCOM standard and has been expanded according to the manufacturer s requirements. 

Vinnem, J.E., Bye, R.J, Gran, B.A., Kongsvik, T, Nyheim, O.M., Okstad, E.H., Seljelid, X and Vatn, X 2012. Risk modelling of maintenance work on major process equipment on offshore petroleum installations. Journal of Loss Prevention in the Process Industries. 25(2). 274-292. 

The study of both cases above has shown that BBN eausal modeling and the developed R MM system are able to provide accurate reliability assessment and maintenance optimization for industrial systems and production processes. In fact, past experiments and industrial applications have validated that the generic R MM methodology can be applied in various industry areas. 

The degradation mechanisms affecting industrial systems, structures and components (SSCs) can be modeled as discrete-state transport processes (e.g., Baraldi et al., 2013 a and b Moghaddas Zuo, 2011). The stochastic transitions between the states obey known models (e.g., WeibuU distribution, exponential distribution, etc.), whose parameters (e.g., the scale and shape factors for the WeibuU distribution, the failure rate for the exponential distribution, etc.) need to be estimated. Degradation models are used in support to maintenance decision making, for example to optimize the inspection period in a preventive maintenance approach or to estimate the remaining useful life of a SSC in a predictive maintenance approach (Zio Compare, 2013). 

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