Machine uptime refers to the time for which a machine, or an equipment, remains operational and available for use. It's a measure of reliability and efficiency, indicating how long a machine has been running without experiencing any unplanned downtime or failures. Uptime is usually expressed as a percentage of total time, with higher percentages indicating better reliability.
The uptime is computed as the sum of:
UPTIME = IDLE_TIME + WORKING_TIME
Operation Managers track uptime metrics to assess the reliability of their machines and to identify any potential issues that may affect performance.
Machine uptime is crucial for maintaining productivity and minimizing disruptions in manufacturing processes. Manufacturers often monitor uptime closely to optimize equipment maintenance schedules and prevent costly downtime that can impact production schedules and profitability.
The algorithm computation is based on the Standard System Status, which can be configured in the Thing Definition, by mapping machine statuses to standard statuses (e.g. HEATING → WORKING).
You can define Insight Metrics based in the Uptime built-in algorithm described below.
This feature is available for the following modules:
VALUE-ADDED DIGITAL SERVICES, SMART AFTER SALES & ADVANCED SERVICES
Inputs
Here is the list of inputs required by this Algorithm.
INPUTS | |
|---|---|
Standard System Status | The uptime algorithm takes as input the Standard System Status, available by default on each product registered in the DPS, and which may assume these states:
The Standard System Status requires to be configured on the Thing Definition, by mapping the machine states to standard states (e.g. WARM_UP → IDLE, HEATING → WORKING). Type: STANDARD_SYSTEM_STATUS | Mandatory |
Outputs
Here is the list of outputs provided by this Algorithm.
OUTPUTS | |
|---|---|
Uptime | Provides the daily time (in milliseconds) the machine is up and available to work. Uptime is calculated by summing the time spent by the machine in any operational states (e.g. WORKING, STANDBY or WARM-UP), and excluding any planned and unplanned down state. A high value indicates that the product is reliably. Conversely, a low value indicates that the product is prone to fault and problems. A product that is always DOWN has an uptime of 0 hours a day, while if it is always UP without problems the uptime is 24 hours a day.
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Uptime Percentage | Provides the daily percentage time the machine is up and available to work. A high value indicates that the product is reliably. Conversely, a low value indicates that the product is prone to fault and problems. A product that is always DOWN has an uptime percentage of 0%, while if it is always UP without problems the uptime percentage is 100%.
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Idle Time | Provides the daily time (in milliseconds) the machine is not performing productivity operations. Idle time is calculated by summing the time spent by the machine in non-operational states, such as STANDBY or WARM-UP. A high value indicates that the product is ready to work but not used as its maximum availability. Conversely, a low value indicates that the product is well-used.
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Idle Time Percentage | Provides the daily percentage time the machine is ready to work. A high value indicates that the product is not used as its maximum capability. A product that is always WORKING has an idle time percentage of 0%, while if it is always into a non-productive state (down excluded) the idle time percentage is 100%.
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Insight Configuration
To use this Algorithm in an Insight Metric, you need to:
Go to the Insight / Insight Metrics page.
Select the Thing Definitions tab.
Select the Thing Definition where to create the insight metric.
Click the Add Metric button.
Select the Uptime algorithm.
Configure the Algorithm required inputs.
Select the output for which you want to calculate the metric.
Displaying Insight Values
You can use any widget supporting metric data loading, for instance:
Value: to display a single value, also aggregated on a period.
Benchmark: to compare your machine with similar ones.
Time Series Chart: to display the trend on a period.
Bar Chart: to display aggregated data through statistics.