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:
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.
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, which can be configured in the Thing Definition, by mapping machine statuses to standard statuses (e.g. HEATING ā WORKING).
You can define Insight Metrics based in the Downtime 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 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 ā IDLE, HEATING ā WORKING).
|
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.
|
Downtime Percentage | The daily total downtime percentage due to PLANNED and UNPLANNED stoppages.
|
Planned Downtime | The daily downtime (in milliseconds) due to a planned down (e.g. Maintenance).
|
Planned Downtime Percentage | The daily downtime percentage due to a planned down (e.g. Maintenance).
|
Unplanned Downtime | The daily downtime (in milliseconds) due to an unplanned down (e.g. Failure).
|
Unplanned Downtime Percentage | The daily downtime percentage due to an unplanned down (e.g. Failure).
|
Insight Metric 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 Downtime 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.