--- title: "Downtime" slug: "downtime" updated: 2024-10-25T10:59:51Z published: 2024-10-25T10:59:51Z canonical: "learn.servitly.com/downtime" --- > ## Documentation Index > Fetch the complete documentation index at: https://learn.servitly.com/llms.txt > Use this file to discover all available pages before exploring further. # Downtime Machine downtime refers to the period during which a machine or equipment is not operational or available for use due to various reasons such as maintenance, repairs, breakdowns, changeovers, or any other unplanned interruptions in production. It is a critical metric in manufacturing and other industries where machinery plays a crucial role in the production process. Downtime can be categorized into two main types: 1. **Planned Downtime**: This is scheduled downtime that occurs when machines are intentionally taken offline for preventive maintenance, upgrades, or other planned activities. During planned downtime, production schedules are adjusted to accommodate the maintenance or upgrades without significantly impacting overall productivity. 2. **Unplanned Downtime**: This type of downtime is unexpected and occurs due to equipment failures, breakdowns, shortages of input materials, power outages, or other unforeseen events. Unplanned downtime can have significant negative impacts on production schedules, leading to delays, loss of revenue, and increased maintenance costs. The Downtime is computed as: > DOWNTIME = PLANNED_DOWNTIME + UNPLANNED_DOWNTIME Reducing machine downtime is a key objective for manufacturing companies as it directly affects productivity, efficiency, and overall profitability. Strategies for minimizing downtime include implementing preventive maintenance programs, training personnel for quick troubleshooting and repairs, and maintaining adequate spare parts inventory. Additionally, analyzing downtime data to identify root causes and implementing corrective actions can help in continuously improving equipment reliability and reducing downtime in the long term. The algorithm computation is based on the [*Standard System Status*](/docs/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 Downtime built-in algorithm described below. > [!WARNING] > This feature is available for the following modules: > > VALUE-ADDED DIGITAL SERVICES, CONNECTED FIELD SERVICES ## Inputs Here is the list of inputs required by this Algorithm. | | INPUTS | | --- | --- | | *Standard System Status* | The [*Standard System Status*](/docs/standard-system-status), available by default on each product registered in the DPS, and which may assume these states: - *OFFLINE*: the product is offline ([**Connection Status**](/docs/connection-status) != 1) - *DOWN_UNPLANNED*: the product is in FAILURE and so not able to work. - *DOWN_PLANNED*: the product is not able to work due to a planned reason, for instance, a cleaning session is running. - *IDLE*: the product is not working (e.g. standby, warm-up, startup). - *WORKING*: the product is working. The [*Standard System Status*](/docs/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 | | --- | --- | | *Downtime* | The daily total downtime (in milliseconds) due to PLANNED and UNPLANNED stoppages. Type: LONG **\|** Insight Properties: [SUM LAST_30_DAYS, SUM LIFETIME](/docs/insight-properties) | | *Downtime Percentage* | The daily total downtime percentage due to PLANNED and UNPLANNED stoppages. Type: FLOAT **\|** Insight Properties: [AVG LAST_30_DAYS, AVG LIFETIME](/docs/insight-properties) | | *Planned Downtime* | The daily downtime (in milliseconds) due to a planned down (e.g. Maintenance). Type: LONG **\|** Insight Properties: [SUM LAST_30_DAYS, SUM LIFETIME](/docs/insight-properties) | | *Planned Downtime Percentage* | The daily downtime percentage due to a planned down (e.g. Maintenance). Type: FLOAT **\|** Insight Properties: [AVG LAST_30_DAYS, AVG LIFETIME](/docs/insight-properties) | | *Unplanned Downtime* | The daily downtime (in milliseconds) due to an unplanned down (e.g. Failure). Type: LONG **\|** Insight Properties: [SUM LAST_30_DAYS, SUM LIFETIME](/docs/insight-properties) | | *Unplanned Downtime Percentage* | The daily downtime percentage due to an unplanned down (e.g. Failure). Type: FLOAT **\|** Insight Properties: [AVG LAST_30_DAYS, AVG LIFETIME](/docs/insight-properties) | ## Insight Metric Configuration To use this Algorithm in an [Insight Metric](/docs/insight-metrics), you need to: 1. Go to the *Insight / Insight Metrics* page. 2. Select the *Thing Definitions* tab. 3. Select the Thing Definition where to create the insight metric. 4. Click the Add Metric button. 5. Select the *Downtime* algorithm. 6. Configure the Algorithm required inputs. 7. 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](/docs/value-widget): to display a single value, also aggregated on a period. - [Benchmark](/docs/benchmark-widget): to compare your machine with similar ones. - [Time Series Chart](/docs/time-series-chart-widget): to display the trend on a period. - [Bar Chart](/docs/bar-chart-widget): to display aggregated data through statistics.