Practical guides on calculating OEE, building downtime dashboards, shift reporting, and using data to improve production efficiency.
Overall Equipment Effectiveness is the gold standard KPI for manufacturing — but 80% of factories calculate it incorrectly. Here is the right way.
In most factories, supervisors spend the first two hours of every morning compiling shift reports from paper logs. Here is how to automate this completely.
Energy is typically the third-largest cost in manufacturing after materials and labour. Most factories track total energy but have no idea which machines or products consume the most.
Most factories fix machines after they break. A predictive maintenance programme uses machine data to catch problems 1–4 weeks before failure — here is how to build one.
Downtime is the single biggest OEE loss in most factories. Here is how to build a system that captures every stop, classifies the reason, and alerts supervisors instantly.
You do not need to install new sensors to start counting production automatically. Most PLCs already generate signals that indicate cycle completion — here is how to use them.
Quality rejections are the most expensive waste in manufacturing — but most factories only discover quality problems hours after they start. Real-time quality analytics catches defects at the source.
Most BI dashboards are built with every metric available. Then nobody uses them. Here is what plant managers actually look at — and how to design around their real workflow.