DESCRIPTION:

The “HeartBeat Generator” node is used to maintain information about the processing activity. In the case where data frames appear infrequently, the node generates frames with no variable values. The configuration should define the delay – the time interval between the present time and the moment of generating the frame, the interval – the time interval between the generated frames, the unit for which the delay was defined, and the interval. Additionally, you can select the “Adaptive delay” option, which will allow you to automatically adjust the delay size based on the data about the frequency of appearance of subsequent data frames, the delay will never be smaller than that specified by the user.

“Failmode” – In the event that frames containing data arrive with a delay greater than the predicted delay for generated heartbeats (empty frames), processing will stop. With this option disabled, the processing will continue, but the frame generation times will be artificially changed in order to keep the chronology of the readings.

EXAMPLE OF APPLICATION:

In the example shown, a Delay of 5, an interval of 1 and a unit of minute are defined. This denotes that when no frame has appeared in the last five minutes, the node will generate an empty frame with the generation time delayed five minutes from the current time. It will do this every minute, unless a data frame is provided for processing. Then the cycle will start all over again.

Checked “Adaptive delay” option will affect the time of generating frames without value. As an example, empty frames will start to appear no earlier than 5 minutes after the last frame containing a value appears. The function will cause that in case of greater delay in data delivery, the waiting time for late frames will be longer, then when they start arriving in a shorter time, the adaptive delay will gradually shorten to the user-defined delay value.

If the “failmode” option is selected, the processing will stop if there is a problem with determining the chronology of data frames and empty frames. Such a situation may arise when, for some reason, data frames are delivered with a delay greater than the scheduled empty frame generation delay time.

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DESCRIPTION:

The “Grouping” node allows to designate new variables based on the input variables in some user-defined groups, for example days/months/production line. For the correct configuration of the node, at least two variables are needed – aggregate and grouping. 

EXAMPLE OF APPLICATION:

According to the example given, 4 variables will be transferred to the next node. Variables AVG, COUNT, MAX and hours. The AVG, COUNT, MAX variables will be calculated for specific values of the variable hour. This denotes that the values of the variables will change within each hour (this results in a separate mean/sum/different type of aggregation for each hour).

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DESCRIPTION:

The “Calculator” node allows to perform calculations, process information or create new variables, which is why it has many applications.

EXAMPLE OF APPLICATION:

the input variables table allows to see all incoming variables in the frames and their data types.

AVAILABLE FUNCTIONS OF CALCULATOR:

The available functions of the calculator are a table containing ready-to-use functions in the “Formula definition area”, which, after selecting, can be placed at the cursor position using the “insert” button without the need to copy.

Math functions:

• math: round (value, scale) – rounds a number by the specified number of decimal places,
• math: power (value, exponent) – increases the number by the given exponent value.

Variable type conversions:

• string: toString (input) – converts a given numeric value to a text value,
• array: toString (array, separator) – converts an array to text,
• array: toJSON (array) – converts an array to JSON,
• array: toArray (string) – converts a text variable to an array of strings using the default separators “,;”,
• array: toArray (string, string) – converts a text variable to an array of strings using the given separators,
• array: toArray (string, separators, trimTokens, string) – converts a text variable to an array of strings using the given separators,
• date: parseDate (dateString, pattern) – returns the date created from a text variable according to the specified date format,
• date: parseTimestamp (timestampString, pattern) – returns a timestamp composed of a text variable according to the given format.

Operations on time variables:

• date: addDaysToDate (date, numberOfDays) – adds the number of days to the given date,
• date: addDaysToTimestamp (timestamp, numberOfDays) – adds the number of days to the given time stamp,
• date: addHoursToTimestamp (timestamp, numberOfHours) – adds the number of hours to the given time stamp,
• date: addMinutesToTimestamp (timestamp, numberOfMinutes) – adds the number of minutes to the given time stamp,
• date: addSecondsToTimestamp (timestamp, numberOfSeconds) – adds the number of seconds to the given time stamp,
• date: getYear (timestamp) – returns the year from the given timestamp,
• date: getMonth (timestamp) – returns the month from the given timestamp,
• date: getWeek (timestamp) – returns the week number from the given timestamp,
• date: getDay (timestamp) – returns the day from the given timestamp,
• date: getHour (timestamp) – returns the time from the given timestamp,
• date: getMinute (timestamp) – returns minutes from the given timestamp,
• date: getSecond (timestamp) – returns seconds from the given timestamp,
• date: getYear (date) – returns the year from a given date,
• date: getMonth (date) – returns the month of the given date,
• date: getWeek (date) – returns the week from a given date,
• date: getDay (date) – returns the day from a given date,
• date: truncateToDate (timestamp) – cuts the timestamp to date format,
• date: toDate (timestamp) – converts timestamp to date,
• date: diffTS (ts1, ts2) – calculates the time difference in milliseconds between the given time stamps,
• date: diffTSWithWeeklyBreaks (ts1, ts2, exclusionArray) – Calculates the time difference in milliseconds between the given timestamps, not including weekly breaks.

Time Variable Conversion Functions:

• date: formatDate (date) – converts date to text using the “yyyy-MM-dd” format,
• date: formatDate (date, format) – converts date to text using the specified format,
• date: formatTime (timestamp) – converts the timestamp to text using the “HH: mm: ss” format,
• date: formatTimestamp (timestamp) – converts timestamp to text using the format “yyyy-MM-dd HH: mm: ss”,
• date: formatDate (timestamp, format) – converts timestamp to text using the given format,

Data estimation:

• prod: estimateQty (startTime, endTime, actTime, soFar) – estimates the number of pieces produced after the specified period of time,
• prod: estimateEndTime (startTime, actTime, expectedQty, actualQty) – estimates the production end time,
• prod: avgProductionSpeed ​​(startTime, endTime, quantity) – Estimates the average production speed in [pieces/hour].

Functions related to dictionaries:

• dict: checkKey (dicionaryId, key) – checks if the specified key exists in the dictionary,
• dict: get (dicionaryId, key) – returns the name for the given key,
• dict: get (dicionaryId, key, defaultValue) – returns the name for the given key, or the given default value if such a key does not exist in the dictionary.

Inserting special characters:

• string: cr () – returns “\r” (carriage return),
• string: lf () – returns “\n” (line feed),
• string: eol () – returns “\r\n” (end of line).

Base64 coding:

• string: encodeBase64 (string) – encodes a text variable to base64,
• string: decodeBase64 (input) – decodes base64 to a text variable type.

PROGRAMMING LANGUAGE:

The calculator programming language is similar to Java with a few exceptions:

• When defining a new variable, its type should not be given, the calculator automatically assigns its form.

• Do not use line break (eol)
• Available math operations: addition (“+”), subtraction (“-”), multiplication (“*”), division (“/”), and the remainder of the division (“%”). Note that the character “^” is not exponentiation, but a logical xor!

In the calculator, you can use short if (“condition? True: false”), but remember that the variables used must be defined in the previous nodes and are located in the “input variables” table.

In the above example, we can see the use of such an expression, if the number ofPulses will be equal to 10 then theText variable = “true”, if not theText variable = “false”

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DESCRIPTION:

The node “Merge data streams” requires connecting two nodes with different input variables to work properly. It connects the frames based on the first input. This allows, for example, to save two parallel processing operations to one result set. The names of the input variables in individual processes must be different from each other.

EXAMPLE OF APPLICATION:

Based on the first input, the node will generate frames containing columns from the second input. That is, when a frame from the second input is delivered and the frame from the first input cannot be matched to it, that frame will be skipped. Frames containing columns from both inputs will be passed as output variables.

The figure below presents three situations showing how frames with data from two inputs can be generated.

In the first case, the frames from both inputs arrive at similar time intervals, however, the frames from the second input are slightly delayed with respect to the frames from the second input. In this situation, the last frame from the first input will connect to the last frame from the second input.

Another case may be the situation when data frames will arrive with different frequency – as shown in the figure. When the frequency of generating frames from the second input is less frequent than from the first input. As a result of this data frame generation, successive frames from the first input will link to the last frame from the second input until a new frame is generated on the second input.

The opposite situation will take place when frames from the first input will be generated less frequently than frames from the second input. In that case, frames from the second input that were generated while no frame was delivered from the first input will not merge with other frames and will be skipped.

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DESCRIPTION:

The “Aggregation window” node allows you to define a time window, determine new aggregated variables in a given window and group. As a result of using the node, the user may obtain various result variables (e.g., average, minimum value, counting frames with a given variable), within a defined time window (time backward from the current moment) and grouping variable. This allows for a detailed data analysis in a given period, such as day, month or hour (size of the time window) and in the context of, for example, Production line (grouping variable containing the line name). For correct configuration, it is required to define a time window and select an aggregated variable within the given time. Unlike the “Grouping” node, the “Aggregation Window” forwards all the input variables and the variables created as part of the aggregation. 

EXAMPLE OF APPLICATION:

As a result of the operation of this node, the next node will receive all input variables and the AVG variable will appear, being the average of the A variables provided over the last day, the SUM variable – the result of adding B values from the last twenty minutes, and the SUM_5 variable containing the sum of A from the last five incoming frames.

The node also enables grouping operations. In this example, the Product variable has been selected as the grouping variable. This means that the average value for the AVG variable and the sum values for the SUM and SUM5 variables will be calculated within the same product.

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DESCRIPTION:

The “Machine operating periods” node is used to obtain relevant data for the Gantt chart type analysis. It allows to specify the cycles in which the machine has worked and to define an alternative variable containing data on downtime. The node, on the basis of the frames with the variable selected as the “pulse variable”, generates and transmits to the subsequent nodes information about the date, series name, start and end time of the work period and the number of pulses.

The determination of the machine working time can be considered on two planes. In the case where the “Changes only” option is turned off, the work period will include all frames containing the pulse variable for which the difference between one and the next is within the time limit. Otherwise, for the variable to enter the period, apart from the necessity to meet the timeout condition, the value of the pulses variable must differ from the previous one recorded in the period.

The user also has the option to select the “split by date” option. After using this function, if the operation period will be at the turn of two dates, it will be split into two separate periods at 00:00:00, which will facilitate filtering based on dates later.

EXAMPLE OF APPLICATION:

According to the example given, two data series have been added. Pulse variables were selected for them – line_A and line_B, and then named – Machine_A, Machine_B. A time limit of 30 seconds has been set for the Machine_A series and the change only option is selected. This denotes that one work period will include the variables for which the time difference between the previous and the current frame is within thirty seconds and the value of the pulse variable in the current frame has changed in relation to the previous one in the given period. For the Machine_B series, the timeout is one minute, and the “changes only” option is disabled. Thus, the variables will only be counted as periods if the time difference between two consecutive frames is within one minute. Unlike the Machine_A series, the difference in the value of the pulse variable is irrelevant here.

The alternate series name “STOP” was selected. It will be displayed in the graph in case the pulse variables of both series fail to meet the conditions of the time difference or the value change (Machine_A).

The example also selects “Split by Date”. If one of the periods begins on one day and ends on the next, it will be divided into 2 periods, which will facilitate later filtering based on dates.

The last option selected is grouping. The grouping variable “day” has been selected here. This means that the generated variables will be counted within the individual values of the day variable.

According to the given example, the following variables will be generated: date (date), seriesName (text), startTS (timestamp), endTS (timestamp), pulses (integer). After assigning all the mentioned variables to the destination – using the “Result table” node, it is possible to create an analysis of the “Gantt chart” type.

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DESCRIPTION:

The “Column transformation” node allows to:

• rename existing columns,
• define constant values,
• and to set default values for existing columns.

Renaming a column updates its name and causes the column to appear under the new name given by the user in subsequent processing nodes. This procedure allows to easily personalize the names of variables within the created processing.

In the node, it is possible to define a new variable with a selected data type (logical value, integer, floating-point number or text) and assign it a constant value that will appear in the entire created processing.

The node also allows to add default values to the existing columns (with the data type boolean value, integer, floating point number or text). In a situation, when a new variable is added to the existing installation channel, then the data frames generated before adding it will be incomplete. By specifying the default values in the “Column transformation” node, in the frames where the selected variable has no value, the value specified by the user will be entered, which will allow the correct operation of the entire processing

EXAMPLE OF APPLICATION:

The configuration of the “Column transformation” node is divided into 3 sections. In the first one, it is possible to rename the existing columns. After selecting the variable from the previous node, the user provides a new name that will be valid in subsequent processing nodes. According to the presented example, the variable A_01 will be further processed under the name variable_1, variable C_03 under the name variable_3, and variable G_07 under the name variable_7.

In the next section, the user has the option to declare new variables with a selected data type and a fixed value of a constant. 4 data types are available – Boolean, Integer, Floating Point, or Text.

In the last section, the user can set default values for individual columns. This means that for frames with the above-mentioned variables, missing value will be replaced with the default value for both past and current frames. According to the presented example, in the case where the frames do not contain values in any of the variables (variable_A, variable_B, variable_C or variable_D), the lack of value will be replaced by the value specified by the user (respectively 9, 9.99, Product_C, false).

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DESCRIPTION:

The “Repeat Data” node is used when the time between incoming frames is long enough that the analysis would not properly reflect the controlled process. By using the “Repeat data” node, it is possible to set an interval during which the node will repeat sending frames containing the last recorded value.

The “Repeat Data” node also includes the “HB mode” option which causes empty frames to be sent instead of duplicate frames. This informs the next processing nodes about the elapsed time.

EXAMPLE OF APPLICATION:

If an interval of 5 is set in a node, in the unit of minute, unless a newer data frame arrives, the previous frame will be repeated every 5 minutes.

Enabling “HB mode” will send empty frames instead of frames with repeated variable. Thanks to this, the other processing nodes will receive information about the expiration of time.

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DESCRIPTION:

The “Cycle time intervals” node is used to obtain the appropriate data for the Gantt chart type analysis. The configuration of the node is very similar to “Machine Operation Times”, however, with cycle time intervals the aim is to represent the performance of a particular machine rather than showing its operating or idle times.

The node specifies:

• Pulse variable – based on the value of this variable in a given frame, it is determined whether the machine is working or idle.
• “Value change only” option – if the value of the pulse variable for two frames does not change, the second one will not be counted as working time.
• Split by date option After using this function, if the operation period will be at the turn of two dates, it will be split into two separate periods at 00:00:00, which will facilitate filtering based on dates later.
• Time limit and interval unit – the maximum time interval from the previous frame considered as the working time required to qualify for a given series.
• Interval code – the name of the series in the Gantt chart for the given interval.
• Alternative series name – the name of the series generated when the period between the delivery of frames is longer than the defined time limits – downtime.
• Grouping variables – input variables for which the result variables will be divided into groups.

On the basis of the entered data, the user receives variables containing information about the date, series name, start and end time of the work period and the number of pulses.

EXAMPLE OF APPLICATION:

In the given example, the pulse variable “Machine No. 1” was selected, the “Value change only” option was selected, and 3 ranges of intervals were added – High with a time limit of 20 seconds, Medium with a limit of 40 seconds and Low with a limit of 1 minute. This denotes that if consecutive frames are delivered with an interval shorter than 20 seconds and the value of the variable changes, they will be included in the “High” series, if the interval of 20 seconds is exceeded and the variable value changes, the frame goes to the Medium series, after after exceeding 40 seconds and changing the variable value will go to the Low series, and after exceeding the defined minute, an alternative series will be generated – “Downtime”.

If the value of the variable does not change in subsequent frames, they are treated as if they had not been delivered.

According to the given example, the following variables will be generated: date (date), seriesName (text), startTS (timestamp), endTS (timestamp), pulses (integer). After assigning all the mentioned variables to the destination – using the “Result table” node, it is possible to create an analysis of the “Gantt chart” type.

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DESCRIPTION:

“Empty Transformation” node forwards the frames without making any changes to them.

EXAMPLE OF APPLICATION:

All incoming variables in frames and their data types can be seen there.

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DESCRIPTION:

The “Time Difference” node outputs a new variable specifying the millisecond time difference between each incoming frame. Moreover, the node enables grouping based on the designated input variables (time differences are divided into groups according to the value of the selected variable, differences are counted for frames belonging to the same group). The grouping function is not required for the correct operation of the node configuration.

EXAMPLE OF APPLICATION:

The time differences between frames within the value of Line_1 will be written to the result variable. Time differences are divided into groups – in this case they will be counted separately for each value of the Line_1 variable. For example, for the variable Line_1 equal to 4, the difference may be 3000 milliseconds, after changing the value of the variable Line_1 to 5, the difference will no longer be taken into account, because we start to calculate the difference for the variable Line_1 with the value 5.

If no variable is selected in the “Grouping Variables” section, then the time difference will be calculated for each subsequent frame relative to the previous frame.

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DESCRIPTION:

The “Time stamp” node allows to generate additional variables that define the time of frame registration. With its help, output variables such as minutes, seconds, timestamp, sequence or date can be obtained.

EXAMPLE OF APPLICATION:

The “Time Stamp” node finds practical application in a processing containing a “Operation change” node. For the correct operation of the “Operation change” node, a variable with the time stamp data type is needed, which can be obtained by selecting the “Date and time” option in the “Time stamp” node.

The “Time Stamp” node can be used when we want to know the exact time or compare data in a similar period.

The “Time Stamp” node can also be used in processing using grouping nodes by grouping a given variable or input variables into a selected time unit. In order to obtain the required time unit, an adequate output variable should be selected in the configuration.

In the example shown, the A variables counted will be grouped by days.

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DESCRIPTION:

The “Union” node is used to combine variables in frames coming from several streams.

EXAMPLE OF APPLICATION:

After connecting several channels to the “Union” node, all incoming variables in the frames and their data types from each of the connected channels are visible in it. The variables from the first input should be assigned the variables from the successive inputs so that their data types are the same. The order of inputs depends on the user, who can modify it in any way.

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DESCRIPTION:

The node “Delta transformation” determines new variables that determine the difference of values between the current and the previous frame. It allows to specify the maximum time interval between frames from which the values are calculated and for grouping based on the supplied variables.

EXAMPLE OF APPLICATION:

Increments of the value (difference between the previous and next value) of variable A within the value of the Hour variable will be written to the C variable. The increments are divided into groups – in this case they will be counted separately for each hour. At 11:59:59 the increment may be, for example, 30, at 12:00:00 the frame with the previous increment will no longer be taken into account, because we start to calculate the increments for the variable Hour with a value of 12. An additional condition for calculating the increments is the time difference between the current and the previous frame (in the same group), which cannot be more than 10 minutes. 

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DESCRIPTION:

The “Signal shape” node allows the user to analyse the changes in the signal shape. In particular, it allows to define the high and low value. On this basis, the node registers changes and informs about exceeding the set thresholds. Thanks to this, the user can, for example, monitor the number of times the machine process from which the data is collected has been fully performed.

EXAMPLE OF APPLICATION:

The “Signal shape” node can be used in a situation where the user is not able to specify the exact value, the exceeding of which would mean the execution of a full machine cycle. “Signal shape” makes it possible to count the number of cycles on the basis of exceeding the threshold values, from values– low, high or both of them, depending on the user’s needs.

In the presented example, the input variable A was selected, the low value – 10 and the high value – 20 were specified. In the first case (for the result name Number of Cycles), the signal shape was set to raisingand the result type – count. This denotes that the node will count the number of occurrences of situations in which it will register the exceeding of the high value (20), when the low value (10) was previously exceeded. However, in the second case (for the resulting name CycleMoment), the signal shape was set to falling and the result type – flag. This denotes that the node will return the value –1 every time the low value (10) is exceeded, when the high value (20) has been exceeded previously.

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DESCRIPTION:

The “Shift transformation” node allows to define a shift work pattern in a production plant. Based on a time stamp variable, the node sends frames containing user-specified details, such as the exact time, number, or shift start date.

EXAMPLE OF APPLICATION:

In order to properly configure the “Change of work” node, it is necessary to define the work shift scheme, entering the hours of their start. On this basis, the end times will be generated after clicking the “Calculate changes” button.

The user should select the variable containing the timestamp from the available variables.

The final step is to select and name the change result variables and save the node.

According to the presented example, on the basis of the provided frames, the node will generate two additional output variables, containing information about the start date and shift numbers. The output variables will match the shift pattern created.

OPTIONS: