Method for detecting and displaying indicator representing process

Abstract

A method for detecting and displaying one or more key performance metrics representing a centrifugal separation process performed with an assembly comprising a centrifuge (2), the method comprising the steps of: performing a separation process with an assembly comprising a centrifuge; detecting one, two or more different operating parameters of the centrifugation process of the assembly having the centrifuge (2) with one or more detection means associated with the assembly; converting, with a data processing unit, the detected operating parameters into two or more corresponding specific key performance metrics; determining an aggregated key performance metric from the two or more specific key performance metrics by applying a predetermined set of rules to determine a weighted average of the two or more specific key performance metrics; and displaying at least the aggregated key performance metrics on a user interface. In addition to this, a system (1) comprising an assembly with a centrifuge (2) and a program is also disclosed.

Description

Technical Field

[0001] The present invention relates to a method for detecting and displaying one or more key performance indicators representative of a separation process. Background Art

[0002] A key performance indicator (KPI) is a quantifiable performance indicator used in industrial processes, which is based on one or more measurements and calculations. It can be used to monitor, analyze and optimize industrial processes, such as centrifugation processes. However, the time course of industrial centrifugation processes is affected by many influencing factors, which makes monitoring and analyzing centrifugation processes particularly difficult.

[0003] US 6,143,183 discloses a computerized system for monitoring, diagnosing, operating and controlling parameters and processes of a continuous feed centrifuge. Monitoring sensors sense processes and other parameters, including machine operating parameters and operating parameters related to the input and output streams of the centrifuge. An operator can monitor the real-time performance and history log of the centrifuge. The software used for this includes an operator screen for data display and message display. Preformatted reports present retrieved data to show information such as operating time, alarms generated, number of starts, number of trips, power used, maximum and minimum values ​​of measured variables, total processed feed, etc. Using operating data, centrifuge manufacturers can recommend measures to avoid downtime and optimize operating time. Moreover, maintenance procedures can be recommended based on operating logs of elapsed operating time and abnormal operating conditions (such as high bearing temperatures or frequent high torque trips). Therefore, operating data logs help troubleshoot various operating conditions of the centrifuge. However, since the amount of sensed parameter data that is usually presented to the user in the form of a report is relatively large, it is relatively difficult for the user to fully understand the measured parameters in order to monitor and analyze the process and respond in a timely manner when problems arise. Summary of the invention

[0004] It is therefore an object of the present invention to provide a method which allows a more efficient monitoring and analysis of a separation process, thereby allowing an operator or plant manager to take timely action in case the operation of the separation process is suboptimal.

[0005] This object is achieved by the subject matter of claim 1. Claim 1 creates a method for detecting and displaying one or more key performance indicators representative of a centrifugation process performed with an assembly comprising a centrifuge, the method comprising the following steps:

[0006] (A) performing a separation process using an assembly including a centrifuge;

[0007] (B) detecting one, two or more different operating parameters of a centrifugation process of a component having a centrifuge using one or more detection means associated with the component;

[0008] (C) converting the detected operating parameters into two or more corresponding specific key performance indicators using a data processing unit;

[0009] (D) determining an aggregate key performance indicator from the two or more specific key performance indicators by applying a predetermined set of rules to determine a weighted average of the two or more specific key performance indicators; and

[0010] (E) Displaying at least the aggregated key performance indicators on the user interface.

[0011] The aggregate key performance indicator is also abbreviated as AKPI in the following.

[0012] According to this method, the centrifugation process can be monitored and analyzed more easily than in the cited prior art. In a preferred embodiment, this information can in turn be used to optimize industrial processes. Preferably, at least steps C) to E) are computer-implemented method steps.

[0013] In a preferred embodiment, a centrifuge of the assembly can be provided for performing a separation process in which a fluid (suspension) is separated into components of different densities in a centrifugal field. Centrifuges in the context of the present disclosure particularly include separators and decanters. In separators and decanters, different separation operations can be performed, such as separation and / or clarification. Clarification is the separation of solids from liquids. In contrast, separation is the separation of two liquids, with or without separation of solids.

[0014] Centrifuges can be used for continuous separation processes. This means that the material being centrifuged is fed in uninterruptedly and one or more of the separated phases are discharged uninterruptedly. However, the solid phase as sludge or slurry can be discharged either continuously or discontinuously.

[0015] Although the time course of clarification or separation is affected by many influencing factors, the present invention improves the monitoring of the centrifugation process by converting the detected operating parameters into two or more corresponding specific key performance indicators with a data processing unit, determining an aggregate key performance indicator from the two or more specific key performance indicators by applying a predetermined set of rules to determine a weighted average of the two or more specific key performance indicators, and by displaying at least the aggregate key performance indicator on a user interface.

[0016] Thus, the user obtains a very good and improved understanding of the separator efficiency compared to the prior art and can more easily detect faults or even potential hazards, risks and areas of potential process improvements. Moreover, a direct indication of critical changes in plant efficiency is achieved.

[0017] Preferably, the corresponding specific key performance indicator is calculated from two or more sub-key performance indicators, wherein one or more sub-key performance indicators are respectively calculated from two or more different operating parameters. According to further advantageous embodiments of this variant, it is also possible that one or more of the corresponding sub-key performance indicators are calculated from one or more sub-sub-key performance indicators, wherein one or more sub-sub-key performance indicators are respectively calculated from one or more of two or more different operating parameters. These embodiments facilitate optimization analysis.

[0018] In a preferred embodiment of the present invention, the weighting of important KPI / sub-KPI / sub-sub-KPI can be increased compared to the equal weighting of all KPI / sub-KPI / sub-sub-KPI to ensure that when they deteriorate or enhance, they have a greater impact on the efficiency of the component. In contrast, the weighting of less important KPI / sub-KPI / sub-sub-KPI can be reduced compared to the equal weighting of all KPI / sub-KPI / sub-sub-KPI to ensure that when they deteriorate or enhance, they do not seriously affect the efficiency of the component. Therefore, weighting the KPI / sub-KPI / sub-sub-KPI enables the efficiency of the component to be monitored using more critical operating parameters. In this way, for example, the key operating parameter flow can have a greater impact on at least one key performance indicator, sub-key performance indicator, sub-sub-key performance indicator, etc. associated with it than other less important parameters. Therefore, critical process problems can be noticed faster than less important problems.

[0019] Therefore, alternatively, it is possible that one or more of the corresponding sub-key performance indicators can be directly calculated from one or more of the operating parameters, and one or more other of the corresponding sub-key performance indicators can be indirectly calculated from one or more of the sub-sub-key performance indicators.

[0020] In a preferred embodiment, different panels are opened one after another on the dashboard in order to expand one or more of the key performance indicators into at least two or more sub-key performance indicators. Thus, the user can scroll through one or more of the KPIs, sub-KPIs and / or sub-sub-KPIs, which also optimizes the analysis. It is also possible to display one or more operating parameters on a panel of the dashboard in this way.

[0021] This embodiment also provides the opportunity to view the calculation results in detail, since the KPI is split into sub-KPIs and preferably sub-sub-KPIs. This makes it possible for the operator or plant manager to directly detect possible deviations and immediately start eliminating negative impacts in order to prevent failures that would lead to additional downtime of components.

[0022] Furthermore, easy access to data evaluation by operators and plant managers is also achieved through this embodiment. AKPI combined with direct linking to the defined KPI structure improves operational risk assessment and mitigation as well as equipment troubleshooting.

[0023] Furthermore, the KPI structure can provide data output indicating areas of interest for a component (eg, a centrifuge) with greater specificity than would be possible with a less structured, unweighted measure of equipment efficiency.

[0024] In a preferred embodiment, the method comprises determining weights prior to step (B). The actual weighting factors may be determined empirically and may be easily adjusted to a user defined personal efficiency definition. Preferably, the weightings may be changed by the user.

[0025] Deviations in parameters related to the internal state of the system allow the operator to act quickly when a problem occurs with the equipment (particularly a component or a centrifuge). It may also be possible to increase the efficiency of the machine, since problems or malfunctions can be immediately eliminated and counteracted.

[0026] In different preferred embodiments, the centrifugal separation process performed with a component including a centrifuge can be one of the following: milk degreasing, milk clarification, sterilization of milk / whey, yeast separation in beer or fermentation medium (using a beer separator or a wine separator), juice separation, whey separation, whey degreasing, coffee or espresso separation, protein separation, animal-based fat separation, fermentation broth separation, chemicals separation, pharmaceutical separation, yogurt separation, butter separation, crude oil separation, wastewater separation and bilge water separation.

[0027] Preferably, one or more detection devices are associated with the centrifuge, said one or more detection devices comprising one or more sensors (the term "sensor" also includes counters).

[0028] One or more sensors for measuring can be arranged on or in the centrifuge.Thus, operating parameters can be determined in or on the centrifuge or in the environment of the centrifuge.

[0029] In a preferred embodiment, the one or more operating parameters include one or more of the following: volume per unit time, production time, discharge time, discharge volume, production temperature, discharge temperature, cleaning in place time, cleaning in place energy, energy production, start-up energy, energy disinfection, differentially standardized milk, differentially standardized cream, acid time, acid conductivity, acid temperature, caustic time, caustic conductivity, caustic temperature, total discharge, available time, cleaning in place time, start-up time, disinfection time, failure downtime, number of major failures and number of minor failures.

[0030] These operating parameters may be determined by measurements, preferably by measurements with one or more sensors.Single operating parameters may also be defined as KPIs or sub-KPIs or sub-sub-KPIs.

[0031] In a preferred embodiment, the one or more specific key performance indicators include one or more of the following KPIs: performance, quality, and availability.

[0032] In a preferred embodiment:

[0033] - Performance KPIs are calculated from at least one or more of the following sub-KPIs:

[0034] production, clean-in-place, energy; and / or

[0035] - the quality KPI is calculated from at least the following sub-KPIs: Quality Clean-in-Place and Quality Product; and / or

[0036] - The availability KPI is calculated from at least one or more of the following sub-KPIs:

[0037] Calculate: machine availability time and failures.

[0038] The invention also achieves the object by a system comprising a component having a centrifuge and one or more sensors, and also comprising a data processing unit, the data processing unit having a user interface unit connected thereto, the user interface unit comprising an electronic display with a graphical user interface, the system being configured to perform the method according to claim 1.

[0039] In a preferred embodiment, the data processing unit may include a programmable logic controller, a data acquisition unit, a storage unit and a data processor.

[0040] In a preferred embodiment, the data processing unit comprises a cloud computing unit comprising a storage unit.

[0041] In one embodiment, the data processing unit may include a cloud computing unit, which includes a storage unit. Preferably, the operating parameters from step (B) are stored in the storage unit of the cloud computing unit. In addition, in one embodiment, steps (C) and (D) are performed by the cloud computing unit.

[0042] In one embodiment, step (E) includes retrieving one or more of the specific key performance indicators and / or operating parameters from a cloud computing unit prior to displaying.

[0043] In one embodiment, the one or more sensors are one or more of a temperature sensor, a gyroscope, a pressure sensor, a microscope, an ammeter, a voltmeter, a humidity sensor, an accelerometer, a flow meter, a mass flow meter, a particle sensor, a scale, a chemical sensor or a biological sensor, an altimeter, an inertial measurement unit, an encoder, a proximity sensor, a spectrometer, a frequency sensor, or a speedometer.

[0044] In one embodiment, the one or more sensors are one or more of an infrared sensor, an ultrasonic sensor, an optical sensor, a capacitive sensor, a piezoelectric sensor, a piezoresistive sensor, a pyroelectric sensor, a triboelectric sensor, a resonator sensor, a magnetic sensor, an anemometer, an electromagnetic sensor, a Hall effect sensor, an inductive sensor, an electrostatic sensor, and / or an electro-optical sensor.

[0045] The present invention also provides a program provided with instructions for causing a system according to any one of the system claims to execute a method according to one of the method claims. BRIEF DESCRIPTION OF THE DRAWINGS

[0046] Below, the invention is described in more detail with reference to the accompanying drawings based on exemplary embodiments, from which further advantages of the invention will become clear. Single or multiple features are described below in conjunction with exemplary embodiments, but the invention is not limited thereto; rather, these features can also be used in other embodiments shown or not shown in the figures. Moreover, single or multiple features can be shown together in one exemplary embodiment. This is advantageous, but not mandatory. These features can also be used together with other features of other embodiments shown or not shown. The accompanying drawings show:

[0047] Figure 1 is a schematic representation of a first embodiment of a system comprising an assembly having a centrifuge and one or more sensors and a data processing unit having a user interface unit connected thereto, the data processing unit being configured to perform a method according to claim 1;

[0048] Figure 2is a schematic diagram of a second embodiment of a system, the system comprising an assembly having a centrifuge and one or more sensors and a data processing unit having a user interface unit connected thereto, the data processing unit being configured to perform the method according to claim 1;

[0049] Figure 3 is a schematic representation of a cross section of a third embodiment;

[0050] Figure 4 , Figure 5 are various exemplary user interfaces;

[0051] Figure 6 is a block diagram of AKPI determination based on two or more specific KPIs;

[0052] Figure 7 is a block diagram of exemplary KPIs and operating parameters; and

[0053] Figure 8 is another block diagram of exemplary KPIs and operating parameters; and

[0054] Fig. 9 is a block diagram illustrating scrolling between different pages of an exemplary user interface. DETAILED DESCRIPTION

[0055] Figure 1 An example system 1 is illustrated, which includes a component including a centrifuge 2, a plurality of sensors 261, 262, 263, 264, and a data processing unit 3 having a user interface unit 4 connected thereto, the data processing unit 3 being configured to perform a method for detecting and displaying one or more key performance indicators, the one or more key performance indicators representing a centrifugation process performed using the component including the centrifuge.

[0056] The centrifuge 2 of the provided assembly is used to carry out a separation process of separating a fluid (suspension) into components of different densities in a centrifugal field.

[0057] Figure 1 An example of a centrifuge 2 is shown in . This centrifuge 2 can be a continuous feed centrifugal separator. This centrifugal separator comprises a machine frame 20 having a housing 21 in which a rotor (not shown) is arranged. The rotor comprises a rotatable bowl. Preferably, the centrifuge is a disc stack separator or a decanter. In a disc stack separator, the bowl comprises a disc stack for effective separation.

[0058] The rotor of the centrifuge is rotated about an axis of rotation by means of a drive 22. The bowl comprises a separation chamber in which, during operation, the centrifugal separation of two or more components of a fluid (ie a suspension) takes place.

[0059] An inlet pipe 23 for feeding the fluid to be centrifuged extends in the drum. A first outlet pipe 24 for discharging a first component of the fluid extends from the drum. In addition, a second outlet pipe 25 for discharging a second component of the fluid extends from the drum. The drum may be provided with additional outlets, for example for continuous or discontinuous discharge of solid sludge from the drum or for separator cleaning.

[0060] According to the present invention, the assembly including the centrifuge 2 includes a detection device including several sensors 261 to 264. These sensors 261 to 264 may include one or both of an internal sensor provided in the drum and an external sensor provided outside the drum. In addition, the sensors may be provided on or inside all components of the assembly.

[0061] The electronic components of system 1 may include wired connections and / or may communicate wirelessly.

[0062] exist Figure 1 In the example, the centrifuge comprises four sensors 261, 262, 263, 264: all of these exemplary sensors 261 to 264 are provided outside the bowl.

[0063] A first sensor 261 is provided in the inlet pipe 23. This first sensor 261 can be designed as a flow meter, in particular as a volume flow meter or a mass flow meter. Figure 1 , the first outlet pipe 24 comprises a second sensor 263 and the second outlet pipe 25 comprises a third sensor 262. These second and third sensors 262, 263 can also be designed as flow meters. In addition, a fourth sensor 264 can be provided at the centrifuge. This sensor can be a vibration sensor designed to measure, for example, vibrations of the machine frame 20.

[0064] These sensors 261 , 262 , 263 , 264 are provided for detecting operating parameters (OP) of the process. They are connected to a data processing unit 3 .

[0065] The data processing unit 3 may include a data acquiring unit 31 .

[0066] The data processing unit 3 may include at least one or more electronic circuits, which include one or more of the following: discrete components, printed circuit boards or integrated circuits. The one or more integrated circuits may include one or more of application specific integrated circuits, microcontrollers, microprocessors or field programmable gate arrays.

[0067] This data acquisition unit 31 may form part of a control unit or may be connected to a control unit, such as a process controller for controlling the centrifugation process.The data acquisition unit 31 acquires measurement data from the sensors 261 , 262 , 263 , 264 .

[0068] In addition, the data acquisition unit 31 may include a gateway. The gateway may be designed to provide data transmission to the computing unit 32. This computing unit may include a data storage unit 321 and a data processor 322. The computing unit 32 may be connected to a user interface unit 4, which is preferably designed as a display unit 4.

[0069] The centrifugation process controller may use the data collected by the one or more sensors 261, 262, 263, 264 (ie, the detected operating parameters) to control the centrifugation process.

[0070] exist Figure 1 In the embodiment shown in , the computing unit 32 can also process the data collected by the sensors 261 to 264. The computing unit 32 uses these data to determine key performance indicators.

[0071] The computing unit 32 can be designed in different ways. In one embodiment, it can be designed as a computing unit located at or near the site where the centrifuge is arranged. However, it can also be located at a different remote location with a wired or wireless connection. Moreover, it can be designed as a remote computing unit, for example as a cloud computing unit. Figure 2 In the embodiment, the data acquisition unit 31 and the calculation unit 32 are part of a computer implementing the data processing unit 3, and the computer can be a local or cloud computer. In this case, the controller for controlling the centrifugation process can also be used as or include the data processor 322 for determining the key performance indicators.

[0072] The calculation unit 32 converts the detected operating parameters into two or more corresponding specific key performance indicators KPI1 and KPI2, and determines an aggregate key performance indicator AKPI from the two or more specific key performance indicators KPI and / or sub-KPI by applying a predetermined rule set to the two or more specific key performance indicators. When the equipment changes, the AKPI changes.

[0073] Figure 3 A schematic representation of a cross section of a third exemplary embodiment of the present invention is shown. The detected operating parameters (data) are transmitted to a data storage unit 322 (not shown) via an Internet of Things (IoT) gateway for data storage. Upon data retrieval, the stored data is processed for subsequent visualization on a user interface unit 4 (not shown). Alternatively, or in addition, an application programming interface may be provided for data transmission.

[0074] Figure 4 An exemplary embodiment of visualizing data by displaying aggregated key performance indicators on the user interface 4 is shown in FIG. It is also possible to display additional information, for example, two or more corresponding specific key performance indicators KPI1 and KPI2, such as Figure 5 as shown in . Figure 4 or Figure 5 The user interface in is configured as a touch display screen, allowing the user to access and view different stages of the calculation of the AKPI, such as operating parameters or KPI1 and KPI2. Thus, the user is able to determine the reason for the change of the AKPI.

[0075] Figure 6 A block diagram illustrating the data content of an AKPI is shown in FIG. AKPI is calculated by determining a weighted average of two or more specific KPIs: KPI1 and KPI2. KPI1 is determined by one or more sub-KPIs: sub-KPI1, sub-KPI2, and sub-KPI3. These in turn are determined by one or more system operating parameters: OP1, OP2, and OP3 are used to determine sub-KPI1, OP4 is used to determine sub-KPI2, and OP5 and OP6 are used to determine sub-KPI3. KPI2 is calculated as a weighted average of operating parameters OP7, OP8, and OP9. Figure 6 The topology of the block diagram in can be infinitely expanded and / or adapted to meet the precise needs of the system operator. Thus, the operator can access multiple levels of pooled machine data, making it easier to identify areas of concern.

[0076] like Figure 6 As shown in , a KPI (such as KPI1 and KPI2) or a sub-KPI (such as sub-KPI1) may be directly calculated from one, two or more different operating parameters, respectively. However, one or more of the corresponding sub-key performance indicators may also be calculated from one or more sub-sub-key performance indicators, respectively, and one or more of the sub-sub-key performance indicators are in turn calculated from one, two or more (different) operating parameters, respectively. Therefore, it is possible to calculate one or more of the corresponding KPIs, one or more of the sub-KPIs, or one or more of the sub-sub-key performance indicators, respectively, from two or more different operating parameters.

[0077] exist Figure 7 and Figure 8 In two more specific exemplary embodiments, the AKPI is calculated as a weighted average of the following specific KPIs:

[0078] - Performance, which can be calculated as a weighted average of the following specific KPIs: production, cleaning in place and energy;

[0079] - Quality, which can be calculated from the sub-KPI “Quality CIP” (Quality of Cleaning in Place);

[0080] - Availability, which can be calculated as a weighted average of the following sub-KPIs: Available Time and Failures.

[0081] exist Figure 7 In order to establish the sub-KPI "production", the sub-KPI "production" is determined by calculation as the weighted average of the following operating parameters: volume per hour, production time, discharge time and discharge volume.

[0082] exist Figure 7 In order to establish the KPI "Cleaning in Place" (CIP), the sub-KPI "Production" is calculated from the operating parameter "CIP Time".

[0083] Moreover, in Figure 7 The sub-KPI "energy" is calculated as the weighted average of the following operating parameters: cleaning-in-place energy, production energy, startup energy and disinfection energy.

[0084] The sub-KPI "Quality of Cleaning-in-Place" may be calculated as a weighted average of the following operating parameters: Acid Time, Alkaline Time and Total Blowdown.

[0085] Available time can be a directly measured operational parameter, or can be a sub-KPI and / or sub-sub-KPI. To establish the OP / sub-sub-KPI available time, it can also be calculated as a weighted average of the following operational parameters: Clean-in-place time, startup time, disinfection time, and downtime failures.

[0086] The sub-KPI "Failures" may be calculated as a weighted average of the following failure operation parameters: failure downtime, number of major failures, and number of medium failures.

[0087] The following describes the preferred embodiments (especially in Figure 7 and Figure 8In the embodiment of the invention, it is possible to easily determine several operating parameters. However, in other embodiments, this can also be done in other ways. The operating parameter "volume per hour" can be determined by flow measurement. The operating parameter "production time per hour" can be determined by the timer control unit. The operating parameter "discharge time per hour" can be determined by the timer control unit. The operating parameter "discharge volume per hour" can be determined by different kinds of measurements (e.g., speed measurement). The operating parameter "CIP time" can be determined by the timer control unit. The operating parameter "CIP energy" can be determined by energy measurement. The operating parameter "production energy" can be determined by energy measurement. The operating parameter "start-up energy" can be determined by energy measurement. The operating parameter "disinfection energy" can be determined by energy measurement. The operating parameter "acid time" can be determined by the timer control unit. The operating parameter "alkali time" can be determined by the timer control unit. The operating parameter "total discharge" can be determined by the counter control unit. The operating parameter "shutdown fault" is determined by the counter control unit and the timer control unit. The operating parameter "number of major faults" is determined by the counter control unit. The operating parameter "number of medium faults" is determined by the counter control unit.

[0088] In this embodiment, the system operator can therefore investigate not only whether his system as a whole or in terms of performance, quality or availability operates as expected, but also, for example, whether its performance is affected by the system's production, cleaning-in-place processes or energy consumption, and the direct causes of any changes in these sub-KPIs or sub-sub-KPIs with respect to determined operating parameters.

[0089] Furthermore, by applying weights, the present invention can take into account the relative importance of different key performance indicators and operating parameters better than the prior art. These factors lead to a more efficient use of limited maintenance and development resources.

[0090] AKPI may also be the average of weighted or unweighted KPIs. AKPI will be defined as but not limited to KPI performance, quality and availability.

[0091] Since weighting will be used, a weighting system similar to that for sub-sub- and sub-KPIs will be implemented

[0092] Weight w (1-5, or adapt as needed)

[0093] Then, the median of the weighted KPI gives AKPI

[0094] ·

[0095] The AKPI dashboard can also include measurements from separators and process-related data, especially for dairy and beverage applications.

[0096] By showing different KPIs (AKPIs and sub-KPIs and operating parameters ( Fig. 9 )), the user gets a better / faster overview of the efficiency of the separator. Also, when problems arise, the user can react faster.

[0097] In various preferred embodiments, the centrifugation process performed with the assembly comprising the centrifuge may comprise a further step of further processing the phase therethrough.

[0098] Figure 7 The block diagram of exemplary KPIs and operating parameters shown in and the above-described alternatives can be used with different kinds of centrifugation processes. However, the present invention can be implemented in a particularly advantageous manner in the processes listed in the introductory part of this description.

[0099] Within the individual processes listed above, it may be useful to consider further parameters.

[0100] A particularly advantageous example process (i.e., a particularly advantageous example centrifugation process that can be used to perform the claimed method) involves centrifuging milk and / or other dairy products into different product phases. As an example, by using a centrifugal separator, milk can be separated into two phases, namely, cream with a high fat content and skim milk with a lower fat content.

[0101] Many dairy processes require additional standardization of the composition of the milk phase. Standardized milk may require control of only one component (usually fat) while allowing other components to vary or control of two or more components.

[0102] Usually, in Figure 1 In the system shown in , the centrifuge is a disc separator for continuous processing. In addition, usually, at least one phase discharged from the separator can be added to another phase in a controlled manner.

[0103] Standardization may require the integration of a computerized control device (also referred to as a "standardization unit") into the degreasing separator.

[0104] The skim separator can be a milk skim separator, but can also be a whey separator. The normalization unit controls the flow of cream out of the milk skim separator and can measure the flow or mass and density of the cream with (one or more) of the sensor(s). Therefore, since the density is known, the fat content of the cream can be calculated by using formulas known in the art. The unit then adds cream according to the flow of skim milk and the desired fat content in the final milk. The remaining cream is then discharged into an additional "remaining cream" tank.

[0105] In this way, the variation in fat content in milk can be adjusted to meet the needs of uses such as cheese milk, drinking milk, etc.

[0106] Figure 8 Another block diagram shows exemplary KPIs and operating parameters that may be used if the centrifugation process includes normalization of one or more of the phases discharged from the centrifugal separator.

[0107] and Figure 7 compared to, Figure 8 Several fields have been added.

[0108] exist Figure 8 In order to establish the sub-KPI "production", the sub-KPI "production" is calculated as the weighted average of the following operating parameters: volume per hour, production time, discharge time, discharge volume, production temperature and discharge pressure.

[0109] exist Figure 8 In order to establish the KPI "Cleaning in Place" (CIP), the sub-KPI "Production" is calculated from the following operating parameters: Cleaning in Place time, which can be determined by a timer control unit.

[0110] Moreover, in Figure 8 The sub-KPI "energy" is calculated as the weighted average of the following operating parameters: cleaning-in-place energy, production energy, startup energy and disinfection energy.

[0111] In order to establish the additional sub-KPI “Quality product”, this can be calculated as a weighted average of the following operating parameters (which in this case can also be referred to as sub-sub-KPIs): Differential standardized milk and Differential standardized cream.

[0112] To establish the sub-KPI "Quality of Clean-in-Place", this may be calculated as a weighted average of the following operating parameters: Acid Time, Acid Conductivity, Acid Temperature, Base Time, Base Conductivity, Base Temperature, Discharge Pressure Overflow and Total Discharge.

[0113] To establish the sub-KPI "Machine availability time", this can be calculated as a weighted average of the OP (in this case also called sub-sub-KPI) "Available time", which in turn can be determined from the following operating parameters: CIP time, startup time, disinfection time and downtime failures.

[0114] To establish the sub-KPI "Failures", this may be calculated as a weighted average of the following operational parameters: downtime failures, number of major failures and number of medium failures.

[0115] The following describes Figure 8How to easily determine several operating parameters in the embodiments of the invention. The operating parameter "production temperature" can be determined by a temperature sensor. The operating parameter "discharge pressure" can be determined by a pressure sensor. The operating parameter "acid conductivity" can be determined by conductivity measurement.

[0116] The operating parameter "acid temperature" can be measured by a temperature sensor. The operating parameter "discharge pressure overflow" can be determined by pressure measurement.

[0117] The sub-sub KPI "Difference standardized milk" can be calculated from the operating parameters calculated from the set point milk standardization and the measurements on milk standardization.

[0118] The sub-sub KPI "Difference normalized cream" can be calculated from the set point cream normalization and the measurement of cream normalization.

[0119] In addition to the explanations given previously, the following list explains Figure 7 and Figure 8 Several terms used in (OP = operating parameter).

[0120]

[0121]

[0122]

[0123]

[0124] Preferably, the following operating parameters can be measured using sensors:

[0125]

[0126] As explained above in the preferred embodiment, for example in the embodiment according to the above figures, KPIs (e.g., performance, quality, and availability) can be split into sub-KPIs. In turn, sub-KPIs can be split into sub-sub-KPIs. The lowest level of the KPI can be calculated from the determined operating parameters.

[0127] Individual sub-sub-KPIs or sub-KPIs can be analyzed against a specific target time (determined by the user).

[0128] The KPI may be evaluated by using a model of deviations from previously archived target values.

[0129] The deviations are then used to scale the KPIs from 0 to 100% within target bands. The target bands are predefined when the system is started, but can also be adjusted afterwards, for example, to accommodate changes in user requirements.

[0130] Each KPI, sub-KPI and / or sub-sub-KPI may be set to a separate range and percentage.

[0131] deviation(%) KPI value (%) 0-5 100 5-10 90 10-15 80 15-20 70 20-25 60 25-30 50 30-35 40 35-40 30 40-45 20 45-50 10 50-100 1

[0132] One or more sub-KPIs or sub-sub-KPIs may then be assigned a weighting factor, for example 1 to 5 or equivalent.

[0133] The calculation method can be selected according to the type of KPI or sub-KPI or sub-sub-KPI and the type of operating parameter. This means that the KPI performance can be composed of different sub-KPIs and sub-sub-KPIs, which can be weighted according to the process and for the efficiency of the assembly.

[0134] This is explained below with respect to different examples.

[0135] For the evaluation of process effectiveness, the capacity view and the process view for product quality are usually more important than the typical time between sludge removal (sludge discharge). However, using the standard model without any weighting, a change in the sludge removal time will have the same impact on the KPI as all other parameters.

[0136] In order to explain the impact of the weighted KPI approach more clearly, the present invention is compared with an approach according to the prior art using unweighted KPIs (which means that all sub-KPIs and sub-sub-KPIs have the same weight).

[0137] Sub-KPIs can be single KPIs evaluated by comparing determined values ​​with target values, calculated values ​​with target values ​​or average values ​​of different sub-sub-KPIs (with or without weighted inclusion of single KPIs)

[0138] ○ Weighted KPI measurement:

[0139]

[0140] As an example, a sub-sub KPI "Production time" important for the sub-KPI "Production" may assign a higher weight (value of w) to "Volume produced per hour" and "Operation time" than to sludge removal time or amount of sludge removed.

[0141] ○ Unweighted KPI measurement average

[0142]

[0143] ○ KPIs that leverage multiplication:

[0144] KPI=Sub KPI1×Sub KPI2×...×Sub KPIn

[0145] An unweighted approach fails to reflect changes in some KPIs / sub-KPIs etc. more than changes in other KPIs / sub-KPIs etc.

[0146] Weight settings:

[0147] Preferably, the weights can be set based on past performance data, experience, and / or can be adjusted based on the user's focus area on the KPI / sub-KPI or sub-sub-KPI. In this way, the AKPI model can be easily adjusted to the customer's definition of assembly efficiency.

[0148] Thus, users get predefined definitions of AKPI with the possibility to adjust them according to their needs and requirements.

[0149] Furthermore, the weights of less important KPIs / sub-KPIs / sub-sub-KPIs may be reduced to ensure that these KPIs do not have a severe impact on the AKPI if they deteriorate.

[0150] As an example, important factors of a centrifugal separation process may be capacity and temperature. Less important factors of this process may be the sterilization time or the time between emptying the bowl of a self-draining centrifuge.

[0151] The user (e.g., production manager) can gain a more meaningful understanding of the separator performance by expanding the KPI structure (arrow UF) on the screen dashboard and can detect faults and / or potential hazards, such as Fig. 9 as shown in .

[0152] Weighting offers the possibility to ensure that more critical parameters (like flow rate) have a greater impact on OEE. In this way, a reduction in a KPI has a greater impact on OEE. - Critical process problems are seen sooner than less important ones.

[0153] The following is an example of calculating a KPI. The KPI to be calculated is the target feed flow rate (unit: volume per hour):

[0154] The target feed flow value to be achieved may have been previously defined, for example by a contract with the splitter, by manual adaptation of the customer or by definition (eg by AI or trial and error).

[0155] ○ For separators used for skimming (e.g. milk), the flow rate should reach 40m 3 / h;

[0156] ○ The average feed flow rate can be calculated by using the feed flow data;

[0157] ○ The average feed flow can be compared with the target feed flow;

[0158] ○ If the difference is less than 5%, then the KPI target feed flow value will be 100%;

[0159] ○ If the value is between 5% and 10%, then 90;

[0160] Example 1: Target value 40m 3 / h, average value = 37.5m 3 / h:

[0161]

[0162] Example 2: Target value 40m 3 / h, average value = 35.0m 3 / h:

[0163]

[0164] In order to fine tune the respective KPI and efficiency, the range of efficiencies can be adapted / changed based on ongoing experience. The values ​​shown are only examples to explain the method.

[0165] Sub-KPIs can be calculated based on different and / or differently weighted values:

[0166] Example 1:

[0167] Sub-KPI performance can be composed of the following sub-sub-KPIs:

[0168] ○ Volume per hour (KPI1) (Example value = 100%) - Weight 1 (W1) = 5

[0169] ○ Production time (KPI2) (Example value = 80%) - Weight 2 (W2) = 4

[0170] ○ Ejection time (KPI3) (Example value = 90%) - Weight 3 (W3) = 2

[0171] ○ Emission volume (KPI4) (example value = 70%) - weight 4 (W4) = 3

[0172] Each weight is then assigned a weight (i.e., weight 1 to 5, value between 2 and 5), and the denominator of the following equation is the sum of all weights.

[0173]

[0174] Example 2:

[0175] The weighting is the same as in Example 1, but the KPI value changes due to the operating parameters.

[0176] The sub-KPI "Performance" can be composed of the following sub-sub-KPIs:

[0177] ○ Volume per hour (KPI1) (Example value = 70%)

[0178] ○Production time (KPi2) (Example value = 60%)

[0179] ○ Ejection time (KPI3) (Example value = 100%)

[0180] ○Emission volume (KPI4) (Example value = 100%)

[0181]

[0182] The KPI may also be calculated by using a weighted sub-KPI average or an unweighted sub-KPI average.

[0183] Example 1b: KPI “Performance”:

[0184] The sub-KPI "Performance" can be composed of the following sub-sub-KPIs:

[0185] ○ Sub-KPI "Production" (KPI1), (Example value = 77%) - Weight 1 (W1)

[0186] =5

[0187] ○ Sub KPI "CIP" (KPI2) (Example value = 64%) - Weight 2 (W2) = 3

[0188] ○ Sub-KPI "Energy" (KPI3) (Example value = 85%) - Weight 3 (W3) = 5

[0189]

[0190] The AKPI is then calculated by using the weighted average of the three KPIs (performance, quality, and availability).

[0191] Example 2b:

[0192] The KPI "Performance" may consist of the following sub-sub-KPIs:

[0193] ○ KPI "Performance" (KPI1) (Example Value = 77%) - Weight 1 (W1) = 5

[0194] ○ KPI "Quality" (KPI2) (Example value = 92%) - Weight 2 (W2) = 3

[0195] ○ KPI "Availability" (KPI3) (Example Value = 54%) - Weight 3 (W3) = 3

[0196]

[0197] In the prior art, KPI is determined as follows:

[0198] KPI=KPI1×KPI2×KPI3=(0.77×0.92×0.54)×100=38.26%

[0199] Using existing techniques, changes to the KPI have a significant impact on the final KPI value.

[0200] The invention also enables comparison of assemblies with different capacity settings, for example, comparison of assemblies operating at a speed of 30 m 3 / h separator with a working speed of 50m 3 / h of separators. Moreover, the invention enables a more meaningful comparison of separators located at different locations or on different processing lines. In addition, the degradation of equipment over time can be indicated by comparing the aggregated key performance indicator value with a value indicative of the long-term performance of the equipment.

[0201] List of reference numbers

[0202] 1 System

[0203] 2 Centrifuge

[0204] 3 Data processing unit

[0205] 4 User interface unit

[0206] 20 Machine frame

[0207] 21 Housing

[0208] 22 Driver

[0209] 23 Inlet pipe

[0210] 24 outlet pipe

[0211] 25 outlet pipe

[0212] 261 Sensors

[0213] 262 Sensors

[0214] 263 Sensors

[0215] 264 Sensors

[0216] 31 Data acquisition unit

[0217] 32 computing units

[0218] 321 Data storage unit

[0219] 322 Data Processor

Claims

1. A method for detecting and displaying one or more key performance indicators representative of a centrifugation process performed with an assembly comprising a centrifuge (2), the method comprising the following steps: A) performing a separation process using an assembly including a centrifuge; B) detecting one, two or more different operating parameters of a centrifugation process of a component having a centrifuge (2) by means of one or more detection devices associated with the component; C) converting the detected operating parameters into two or more corresponding specific key performance indicators using a data processing unit; D) determining an aggregate key performance indicator from the two or more specific key performance indicators by applying a predetermined set of rules to determine a weighted average of the two or more specific key performance indicators; E) Displaying at least the aggregated key performance indicators on the user interface.

2. The method according to claim 1, characterized in that The corresponding specific key performance indicator is calculated from two or more sub-key performance indicators, wherein the one or more sub-key performance indicators are respectively calculated from the two or more different operating parameters.

3. The method according to claim 2, characterized in that One or more of the corresponding sub-key performance indicators are calculated from one or more sub-sub-key performance indicators, wherein the one or more sub-sub-key performance indicators are respectively calculated from one or more operating parameters of the two or more different operating parameters.

4. The method according to any one of the preceding claims, characterized in that The method includes, prior to step (B), determining weights for calculation of key performance indicators.

5. The method according to any one of the preceding claims, characterized in that Different panels are opened one after another on the dashboard so as to expand one or more of the key performance indicators into at least two or more sub-key performance indicators.

6. A method according to any one of the preceding claims, characterised in that The one or more detection devices are associated with the centrifuge, and the one or more detection devices include one or more sensors (261, 262, 263, 264).

7. The method according to any one of the preceding claims, characterized in that The centrifugal separation process is a separation process in which a fluid - a suspension - is separated into components of different densities in a centrifugal field.

8. The method according to any one of the preceding claims, characterized in that The centrifugal separation process performed with the assembly is one of the following: milk skimming, milk clarification, sterilization of milk / whey, separation of yeast in beer or fermentation media (beer separator or wine separator), juice separation, whey separation, whey skimming, separation of coffee or espresso, separation of proteins, separation of animal-based fats, separation of fermentation broths, separation of chemicals, separation of pharmaceuticals, separation of yogurt, separation of butter, separation of crude oil, separation of waste water, separation of bilge water.

9. The method according to any one of the preceding claims, characterized in that The one or more operating parameters include one or more of the following: volume per hour, production time, discharge time, discharge volume, production temperature, discharge pressure, clean-in-place time, clean-in-place energy, production energy, start-up energy, sterilization energy, differential standardized milk, differential standardized cream, acid time, acid conductivity, acid temperature, alkali time, alkali conductivity, alkali temperature, discharge pressure overflow, total discharge, clean-in-place time, start-up time, sterilization time, downtime failures, number of major failures and number of medium failures.

10. The method according to any one of the preceding claims, characterized in that The one or more specific key performance indicators include at least one or more of the following key performance indicators: performance, quality, and availability.

11. The method according to claim 10, characterized in that - the performance KPI is calculated from at least one or more of the following sub-KPIs: production, clean-in-place, energy; and / or -The quality KPI is calculated from at least the following sub-KPIs: quality cleaning-in-place; - and the availability KPI is calculated from at least one or more of the following sub-KPIs: machine availability time and failures.

12. The method according to claim 10 or 11, characterized in that The quality KPI is calculated from at least one or more of the following sub-KPIs: quality product and quality clean-in-place.

13. The method according to claim 10, 11 or 12, characterized in that - the production sub-KPI is calculated from one or more of the following operating parameters: volume per unit time, production time, discharge time, discharge volume, and production temperature, discharge pressure; and / or - The CIP sub-KPI is calculated from one or more of the following operating parameters: CIP time, acid time, acid conductivity, acid temperature, Alkali time, alkaline conductivity, alkaline temperature, and total discharge.

14. The method according to claim 10, 11, 12 or 13, characterized in that - The energy sub-key performance indicator is calculated from one or more of the following operating parameters: clean-in-place energy, production energy, startup energy, and disinfection energy; and / or -The product quality sub-key performance indicator is calculated from one or more of the following operating parameters: Difference from standardized milk and Difference from standardized cream.

15. The method according to claim 10, 11, 12, 13 or 14, characterized in that - The machine availability time sub-KPI is calculated from one or more of the following operating parameters: availability time, clean-in-place time, start-up time, disinfection time, and downtime; and / or - The failure sub-key performance indicator is calculated from one or more of the following operating parameters: failure downtime, number of major failures, and number of moderate failures.

16. A system (1) comprising an assembly having a centrifuge (2) and one or more sensors (261, 262, 263, 264), and comprising a data processing unit (3) having a user interface unit (4) connected thereto, the user interface unit (4) comprising an electronic display having a graphical user interface, characterized in that The system (1) is configured to perform the method according to claim 1.

17. System (1) according to claim 16, characterized in that The data processing unit (3) comprises a programmable logic controller, a data acquisition unit (31), a storage unit (322) and a data processor (321).

18. System (1) according to one of claims 16 to 17, characterised in that The data processing unit (3) includes a cloud computing unit, and the cloud computing unit includes a storage unit (322).

19. A program having instructions for causing the method according to one of claims 1 to 15 to be performed by a system according to one of claims 16 to 18.

Images