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Reports & Analytics

Turn your production data into clear, useful insights. OpenMES gives you OEE breakdowns, scrap analysis, work order history, cost tracking, non-conformance reports, and MRP planning. Each report answers a real manufacturing question and helps you keep improving.

OEE Report

OEE (Overall Equipment Effectiveness) is the top way to measure how well your factory runs. The OEE Report in OpenMES breaks it down for each line into three parts – Availability, Performance, and Quality. It also shows the combined OEE score: OEE = A × P × Q.

OEE Report showing per-line breakdown with Availability, Performance, Quality percentages, OEE score, produced units, scrap count, and downtime minutes

Here are the metrics shown for each line and time period:

MetricFormulaWhat It Measures
Availability (A)Run Time / Planned Production TimeWas the line running when it should have been? Losses come from downtime, changeovers, and breakdowns.
Performance (P)Actual Output / Theoretical Maximum OutputWas the line running at full speed? Losses come from slow cycles, minor stops, and reduced speed.
Quality (Q)Good Units / Total Units ProducedHow many units passed quality checks? Losses come from scrap, rework, and rejects.
OEEA × P × QThe overall score. World-class factories aim for 85% or higher.

You also see Produced Units (total output), Scrap Count (rejects broken down by reason), and Downtime (minutes of unplanned stops). Filter by date, line, product, or shift to dig into the details.

OEE data is calculated automatically. Every time a line starts, stops, makes units, or creates scrap, the system logs it. Break times (set up in HR & Factory Structure) are excluded so they do not lower your Availability score.

Use Case 1 – Weekly Management Review: Every Monday, the manager checks last week's OEE for all lines. Line 2 shows 62% OEE – way below the 80% target. Availability is fine at 95%, but Performance (78%) and Quality (84%) are low. Low Performance means speed issues worth investigating. Low Quality means checking the scrap reasons for that line.
Use Case 2 – Shift Comparison: A factory thinks the night shift is less efficient. Filtering by shift shows the day shift at 81% OEE and the night shift at 68%. The gap is mostly in Performance – night operators run machines slower. This data helps plan targeted training for the night crew.
Use Case 3 – Before/After Equipment Upgrade: After adding a new servo motor on Line 4, the team compares OEE before and after. Performance jumped from 72% to 91%. That proves the upgrade was worth it and supports future investment decisions.

Scrap Reports

Scrap Reports use Pareto analysis to show you where waste comes from. They help you find the biggest scrap reasons hurting your Quality score and material costs. The 80/20 rule says that about 80% of scrap usually comes from just 20% of the reasons. This report makes that easy to see.

Scrap Reports with Pareto chart showing top scrap reasons ranked by frequency, cumulative percentage line, and scrap rate per production line

The Pareto chart shows bars for each scrap reason, sorted from most to least common. A cumulative line shows how much of total scrap each reason explains. Below the chart, a table shows the scrap rate per production line (scrap units / total units). This makes it simple to compare quality across lines.

Scrap data links to the standard Scrap Reasons set up in Products & Traceability. This keeps categories consistent and lets you track trends over weeks, months, and quarters.

Use Case – Targeted Quality Improvement: Pareto analysis shows "dimensional out of tolerance" causes 45% of scrap on Line 1. "Visual defects" add another 25%. Together, these two reasons make up 70% of waste. The quality team focuses on calibrating cutting tools and checking the coating process. The other 30% of reasons are too small to tackle individually.

Work Order History

Work Order History is your factory's production logbook. It stores all completed work orders in one place. Unlike the active Work Orders screen, this report focuses on past data and how orders actually ran.

Work Order History report showing completed orders with planned vs actual quantities, execution times, and on-time delivery status

For each finished order, you see: Order Number, Product, Planned Quantity vs. Actual Quantity, Planned Start/End vs. Actual Start/End, Execution Time (total hours), On-Time Delivery status (green = on time, red = late), and the Line used.

This helps with capacity planning. You can see how long orders really take versus the estimate. If a product is always late, the planned cycle time or changeover time probably needs fixing. Filter by date, product, line, or on-time status.

Use Case – Delivery Performance KPI: Sales needs the on-time delivery rate for Q3. Filter Work Order History to July–September and count green vs. red statuses. Result: 87% on time. The 13% late orders reveal the bottleneck – most delays happened on Line 3 during changeovers.

Production Cost

The Production Cost report splits each work order's cost into three parts: Material Cost (raw materials used, based on BOM and unit prices), Labor Cost (operator hours times wage rates), and Additional Costs (overheads, tooling, energy, and any extra items you add).

Production Cost report showing cost breakdown per work order with material, labor, and additional cost columns and total cost per unit

The report shows Total Cost Per Unit by dividing total cost by good units produced. Use it for pricing, margin checks, and spotting orders that cost more than expected. Over time, you can see trends. Are material costs going up? Are some products always more expensive to make than planned?

Use Case – Margin Analysis: A manufacturer makes products for three customers at different prices. The report shows Customer C's product costs 15% more per unit than expected. The cause: higher scrap and longer changeovers. Sales can use this to renegotiate the price or suggest design changes that are easier to produce.

Non-Conformance Report

The Non-Conformance Report collects all quality issues and deviations into a Pareto chart by type. It goes beyond the Scrap Report (which only covers discarded units). It also includes problems fixed on the line, items sent for rework, and issues escalated for investigation.

Non-Conformance Report with Pareto chart of issue types, corrective action status, and trend over time

Each record links to the work order, the production line, the issue type (from the standard reasons list), any corrective action taken, and the status (open, in progress, closed). The Pareto view shows which issues happen most. The trend view tells you if your fixes are actually working over time.

Use Case – CAPA (Corrective and Preventive Action): An ISO 9001 audit needs proof that you track and fix quality issues. The Non-Conformance Report has the data. It shows the top five issue types, the corrective actions taken, and a trend chart with a 22% drop in non-conformances last quarter. That proves your quality system works.

Net Requirements (MRP)

The Net Requirements report is a simple MRP (Material Requirements Planning) tool. It checks how many components your planned work orders need against what you have in stock and what is on the way (pending purchases or transfers). It flags any shortages you need to fix before production starts.

Net Requirements MRP report showing components, required quantity, stock on hand, expected receipts, net requirement (shortage), and earliest need date

For each component, you see: Material Name, Total Required Quantity (across all planned orders), Stock On Hand, Expected Receipts, Net Requirement (shortage = required minus on hand minus expected; a positive number means you are short), and the Earliest Need Date (when the first order needs this material).

This is not a full MRP system (that would include lead times, lot sizing, and multi-level BOM explosion). But it gives you the key daily check: "Can we build what we planned?" If you use an external ERP with full MRP, this report works as a handy shop-floor cross-check.

Use Case 1 – Daily Planning Check: Each morning, the planner opens Net Requirements for the week. Component X needs 200 kg, but only 50 kg is in stock with nothing on the way. The planner either reschedules those orders or rushes a purchase order to the supplier.
Use Case 2 – What-If Scenario: Before confirming a big customer order, the planner creates a draft work order and checks Net Requirements. Two critical components would be short. The planner uses this info to quote a realistic delivery date based on material lead times.
Export & Integration: Every report can be filtered, sorted, and exported to CSV or PDF. Share them with anyone who does not have OpenMES access. Need automated reporting? The OpenMES API lets you pull report data into BI tools like Power BI, Tableau, or Grafana.