Real-time production quality control — powered by data and AI

Hapo QC Hub collects, standardizes, and analyzes quality data from every workshop. Catch anomalies early, alert the right stakeholders, and decide with statistical process control (SPC).

Today's defect rate

6.2%

Alert: Machine M07 over threshold

Control chart — Fabric width (WIDTH)

Built by Haposoft — software partner for Japanese and global enterprises.

AWS Select Tier PartnerISO 9001:2015ISO 27001200+ engineers

Is quality data scattered and acted on too late?

Inspection data lives in emails and dozens of Excel files — hard to consolidate.

Defects are found late — by the time you know, the batch has already run through.

No control charts (SPC) to see when the process is drifting out of spec.

Alerts don't reach the right people; no one tracks whether issues were resolved.

One platform for the full quality control loop

Collect & standardize

Web entry or Excel import from templates; master-data rules and instant validation.

Analytics & SPC

Control charts, Cp/Cpk, top defects and machines; compare shifts and workshops.

Tiered alerts

Auto-alert on threshold breaches; route to the right role with follow-up tracking.

Automated reports + AI

Scheduled reports with AI commentary; natural-language Q&A; Excel/PDF export.

Four steps to run QC

From data entry to decisions — one continuous workflow on a single platform.

1

Capture data

Inspection records from the shop floor — web entry or Excel import using a standard template.

2

Analyze & SPC

Dashboards and control charts update automatically by machine, characteristic, and fabric type.

3

Alert

Notifications to the right tier when thresholds are exceeded or points are out of control.

4

Report & decide

PDF reports with AI commentary to support data-driven decisions.

Control the process with statistics, not gut feel

I-MR control charts, Cp/Cpk by characteristic × fabric type, and automatic out-of-control detection — so the plant reacts before defects spread.

  • I-MR charts by machine and characteristic
  • UCL / LCL with highlighted out-of-control points
  • Process capability analysis (Cp/Cpk)

Sample — Fabric width M07

AI-assisted decisions

Auto-written report commentary

AI summarizes KPIs and writes commentary for daily, weekly, and monthly reports.

Chat with your data

"Which workshop had the highest defect rate this week?" — answered from aggregated data.

Root-cause suggestions

Analyze top defects and machines to suggest where to investigate.

Ask your data (AI)

Which workshop had the highest defect rate this week?
In the last 7 days, Workshop PX3 had the highest defect rate (~7.2%). Machine to watch: M07 (WIDTH drifting). Recommend checking the dryer section and fabric width alignment.

Outcomes

Catch anomalies early and reduce defective lots running through the line.

Standardize data and stop manual consolidation from email/Excel.

Transparency by machine, team, shift, and workshop with clear accountability.

Improvement decisions grounded in data and SPC.

Ready to see Hapo QC Hub on your data?

Book a 30-minute demo with the Haposoft team.