Engineering in AI Process Monitoring
Comments Off on Engineering in AI Process MonitoringMachine Supervision Module
The Machine Supervision module provides access to information related to the current operation of connected machines and lines.
It is divided into four subsections:
- Remote Monitoring: near real-time information on the status of the machine/line (in production, idle, etc.) and monitoring of key variables also with respect to tolerance setpoints (current speed, film thickness, etc.).
- Alarms: table displaying all active and past blocking alarms, with the ability to perform analysis by filtering by time period, operator, alarm category, etc.
- Warnings: table displaying all active and past non-blocking alarms, with the ability to perform analysis by filtering by time period, operator, alarm category, etc.
- State Timeline: visualization of the total time spent in each machine state in the form of a GANTT chart, with the possibility of drill-down analysis down to the comparison of machine states at the occurrence of any alarms/messages.
Lean Analytics Module
The Lean Analytics module provides statistical information covering the entire production process.
It is divided into five subsections:
- OEE Trend: identification of productivity loss causes through analysis of the OEE trend and its related components (performance, availability, and quality).
- Production Trend: quantitative analysis of production over time by comparing actual versus ideal production, correlated with the possible causes of the “delta” (scrap, downtime, etc.).
- Production Traceability: traceability of production events with a level of detail down to the individual shift or production order.
- Scrap Analytics: detailed analysis of production scrap, broken down by individual “cause.”
- Breakdown Analytics: immediate reporting of the most impactful machine downtime causes (vital few) and suggestions on which breakdowns to address.
- Fault Trend: detailed analysis of alarm trends, together with key information such as alarm code, message, duration, count, and duration/count ratio.
Consumption Analytics Module
The Consumption Analytics module enables analysis of machine resource consumption, both in terms of utilities and raw materials as well as consumables, identifying the production factors that have the greatest impact on their consumption:
- Analysis of absolute and relative consumption (e.g., kWh/m).
- Ability to configure any “consumable.”
- Comparison of current consumption with previous periods (indication of improvement/deterioration).
- Ability to compare consumption by: product code / operator / shift / recipe, etc.
Machine Recorder Module
The Machine Recorder module makes it possible to implement a true machine “black box” to support diagnostic activities.
The dashboard is dominated by a chart that allows the behavior of variables to be contextualized with the events that occurred during the process.
This functionality enables a complete diagnosis of every event that occurred on the machine and of the impact it had on the process.
- Acquisition of process variables (setpoints and actual values) with a configurable sampling rate (up to 30 ms).
- Acquisition of machine state changes.
- Acquisition of alarm and signal activations/deactivations.
- Detection of machine parameter changes made by the operator.
- Adaptive zoom on data thanks to multi-level aggregation logic.
Smart Notifications
The Smart Notifications module allows configuration of email notifications related to specific events in the machine’s operating context:
- Configuration of events related to KPIs (OEE, downtime, etc.) and analog or discrete process variables.
- Ability to configure different events for each machine.
- Ability to customize the mailing list for each machine.