Abstract:
A metric based performance monitoring A process control system is disclosed in which diagnostics are performed at multiple levels of the plant, results of the diagnostics converted into Key Performance Indicators and compared to predetermined benchmarks such that an integrated and overall determination of the plants&#39; performance may be displayed.

Description:
FIELD 
       [0001]    The present invention relates to performance monitoring systems, and particularly systems designed for use in process plants. 
       BACKGROUND OF THE INVENTION 
       [0002]    Process plants such as chemical and petrochemical plants comprise hundreds of thousands of interrelated components ranging from individual devices, such as control valves, to complex plant equipment such as multi-stage compressors and heat exchangers, for example. Each of these components must operate continuously in a safe, efficient and effective mode in order for the entire plant to operate within predetermined levels of safety, quality and production. 
         [0003]    Accordingly, hundreds of such devices, loops and equipment are required to effectively control the plant, and in turn, these assets must be constantly monitored for their optimal operations. 
         [0004]    Countless prior art performance monitoring systems have been devised as attempted solutions, but all have had serious shortcomings and/or created problems themselves. For example, those based only on Key Performance Indicators (KPIs) do not produce an integrated presentation of the necessary information since they concentrate only on the process control loop level. Similarly, other systems focus on higher, supervising levels, but only by measuring against past performance and projected targets. These systems are not seamlessly integrated into the operation and maintenance layers, as does the present invention whereby an integrated and comprehensive view is provided of the total plant performance at the device level, control loop level and equipment level. 
         [0005]    Moreover, while there have been prior loop and device performance monitoring systems, such prior systems have required highly skilled operators to interpret the results, and the results do not directly tie to the KPIs currently in use as does the system of the present invention. Other prior attempts have suffered from converting data overload problems for the operators into information overload problems, whereas the system of the present invention normalizes the complex results into only 3 states such as, for example, “Excellent”, “Good/Deteriorating” and “Bad”. Further, these can be colour coded so that highly skilled operators are not required, and errors of interpretation are avoided. 
         [0006]    By way of example, a typical scenario is illustrated in  FIG. 1  wherein a production run is started at  40  and the production  42  continues, while quality checks  44  are performed, until the product is detected to be offspec as indicated at  46 . The operator then begins a trouble shooting program  48  in an effort to determine the cause of the problem. As illustrated by way of example, the problem may involve the PID (Proportional-Integrated-Derivative) tuning  50 , or the APC (Advanced Process Control)  52  may have become inactive, or a breakdown  52  may have occurred. Only after this determination is made can the problem be corrected, which may involve unacceptable downtime and/or loss of product before production may be resumed. 
         [0007]    Contrary to this conventional approach, the performance monitoring control system of the present invention compares all of the sensed conditions, at three different levels as will be more fully explained hereinafter, and produces an integrated, overall and deterministic presentation to the operators. In addition, the complete presentation may be broken down into information segments of particular concern to different classes of plant personnel such as, for example, maintenance, operations, and management. 
         [0008]    Other problems of prior art systems include such disadvantages as being limited to the diagnostics of the component supplier, or discounting the current health of the existing equipment and relying only on periodic maintenance, or an over reliance on RBI (Risk-Based Inspection) and RCM (Reliability Centered Maintenance) analysis rather than immediate identification a problem or potential problem before it occurs. These and other problems of prior art systems are solved by the present invention, along with providing other substantial advantages as will become clear from the following description of one preferred embodiment of the present invention. 
       SUMMARY 
       [0009]    The present invention comprises a system and method for monitoring the performance of a plant including performing diagnostics at more than one level of the plant, converting results of the diagnostics into KPIs, comparing the KPIs against predetermined benchmarks and providing integrated information as to the acceptability level of the plants&#39; performance. 
     
    
     
       BRIEF DESCRIPTION OF DRAWINGS 
         [0010]      FIG. 1  is a flow diagram illustrating a typical prior art system; 
           [0011]      FIG. 2  is a block diagram illustrating the system of the present invention; 
           [0012]      FIGS. 3-5  are illustrative examples of the displays of information which may be provided by the present invention to different types of personnel involved in the plant operation; 
           [0013]      FIG. 6  is a flow diagram illustrating the metric based performance monitoring system of the present invention in further detail; and 
           [0014]      FIG. 7  is a flow diagram illustrating the metric based performance monitoring system in a bottom up mode. 
       
    
    
     DETAILED DESCRIPTION 
       [0015]    Referring to  FIG. 2 , diagnostics are performed at plant level  10 , loop level  12  and device level  14  by diagnostic means  15 . For example, at the device level, factors such as the device healthiness, device and process interface, and the deviation between design condition and actual process conditions are formulated in diagnostic step  16 , and algorithms for the diagnostics are derived for example, from a combination of the equipment suppliers specifications and end users experience. At the loop level, various factors which influence quality and quantity of production are diagnosed in step  18 . At the plant or equipment level, methods such as Overall Equipments Effectiveness (OEE) or other known methods are modelled in step  20  to monitor production downtime as a factor of asset performance, production quality or turnaround. 
         [0016]    The diagnostic results  22 ,  24  and  26  of each of the three levels are converted by a converting means  27  into respective KPIs  28 . The KPIs  28  are then transmitted to comparator  30  which compares them against predetermined benchmarks  32 . Those performing at or above the benchmarks are then identified as “good performers” versus those below as “underperformers”. The performance levels of the former are then transmitted through feedback loop  34  to become the revised, current benchmarks for future comparison with newly sensed and analyzed outputs from the three levels. 
         [0017]    In addition to determining the problem; i.e. the underperformer(s), the performance levels of all of the other devices, loops and equipments are continuously determined and displayed for monitoring by the operators, and other personnel. For example, data such as quality and production rate may be segregated and displayed to personnel such as management and on-line operators, while the operators may also see other operating data such as that at the device and loop level.  FIGS. 3 ,  4  and  5  further illustrate this important feature as the segregated data may be displayed and viewed by three or more different types of personnel such as Management, Engineering and Operators, each of which groups is interested in entirely different types of data illustrated by way of example. 
         [0018]    A further example is shown in  FIG. 6  in which a user may use the present invention to manage plant performance KPI as previously described. In this scenario, the production KPI  60  for a given day is determined to be lower than the target, or lower than that of the previous day as illustrated at  62 . The user then uses the present invention to go to the next lower level; i.e. the loop level and identifies that the APC loops are operating in manual mode with the APC inactive as shown at  64 . Control valve controllability diagnostics are then used to identify that the control valve has been experiencing high deviation from the set point as shown at  66 , thereby forcing it to hunt as is displayed on the interface as shown at  68 . That is, the valve hunting has affected the production quality, and therefore, lowered the production KPI which has been brought to the user&#39;s attention by the present invention. The user is therefore able to identify a cause-effect relationship between the device and control loop diagnostics to take the necessary corrective actions. 
         [0019]    Accordingly, the problem has been determined to require correction of the loop tuning, as shown at  70 . The valve hunting is thus solved at  72 , and the controllability  74  is improved with the APC back to active mode at  76 . The production  78  is then on spec as shown at  80 . The present invention is therefore capable of allowing the user to identify the area for improvement by observing a correlation between the equipment, loop and device diagnostics. 
         [0020]    In another aspect of the present invention, as shown in  FIG. 7 , it will be assumed that there is a problem of inadequate air supply to one of the control valves which is displayed on the user interface at  90 . The personnel also see, at the loop level, that there is a deviation in the corresponding control loop between the set point and measured value as illustrated at  92 . Additionally, it is seen that there is an effect on the production quantity or quality KPI at  94 , and the overall effect on the KPI of the entire plant as shown at  96 . Therefore, it will be apparent that the present invention provides monitoring the plant in both a bottom up as well as the top down mode. 
         [0021]    In the foregoing examples it will be noted that the entire sequence is performed while the production continues, whereas in the previous example of the prior art, the user is not made aware of the identity of the problem until after there has been a device or equipment failure, after which more production time is lost in trouble shooting by trial and error. 
         [0022]    From the foregoing description of one embodiment of the invention, it will be apparent that numerous variations will be apparent to those skilled in the art without departing from the spirit and scope of the invention. Accordingly, it is to be understood that the foregoing description is intended to be illustrative of the principles of the invention rather than exhaustive thereof, and that the true invention is not intended to be limited thereby, nor limited in scope other than as expressly set forth in the following claims.