Analytics case study / Manufacturing monitoring

Machine Monitoring

A Power BI dashboard for recurring review of machine performance, OEE, and downtime.

Context

Internship project at PT Mattel Indonesia focused on manufacturing machine-performance monitoring.

Business Problem

Machine-generated data needed a more structured monitoring view so key performance indicators could be reviewed more easily.

Objective

Consolidate machine-performance information into a Power BI dashboard for recurring monitoring and analysis.

My Contribution

Gathered, transformed, and visualized machine-generated data; developed and maintained the reporting dashboard; and supported related user requests.

Analysis Coverage

OEE and downtime monitoring, alongside reject and performance views.

Selected Dashboard Views

Gauges above ranked downtime and machine-reject bar charts.
OEE summary A consolidated view of OEE, availability, performance, quality, utilization, downtime, and rejects.
Four trend charts with date and machine filters in a left sidebar.
OEE trend OEE, performance, availability, and quality trends shown together for review over time.
Bar-chart breakdowns and downtime totals arranged across a yellow dashboard.
Downtime Downtime duration and frequency broken down by reason, toy number, and machine.
Two bar charts on a teal dashboard with a filter sidebar.
Reject Reject PPM compared by reject reason and machine.
Stacked columns above a table containing dates, machine IDs, and reject records.
Reject analysis Reject types by machine, with a detailed record table below the chart.
Blue performance dashboard combining trend charts, a record table, and ranked bars.
Performance Average performance by date and machine, alongside output records and part-number variance.

Decision Support

Helped users monitor machine performance and identify areas requiring further investigation.

Business Impact

Provided a centralized monitoring view for machine-performance data.

Tools

Power BI.