How a USA Global Power Technology Manufacturer Achieved 95% Defect Detection Recall in Exhaust Weld Inspection with Jidoka

Jidoka’s KOMPASS two-camera system enabled lift-hook weld inspection with 95%+ defect recall, 99%+ frame selection and a ≤5% false call rate.

Use Case

Lift-Hook Weld Inspection

Result 1

At least 95% defect detection recall

Deployments

KOMPASS with two industrial cameras, auto-focus lenses and dynamic lift-hook frame selection

Result 2

At least 99% automatic frame selection with a false call rate of 5% or less

Overview

A U.S.-headquartered global power technology manufacturer develops engines, power systems and related component technologies for customers worldwide. Its emission solutions portfolio includes exhaust aftertreatment systems designed to support performance, reliability and regulatory compliance.

Lift hooks are welded to exhaust components during manufacturing. The existing quality check relied on operator observation and manual judgment. Differences in component variants, hook positions and weld appearance made consistent inspection difficult and limited the availability of image-linked quality records.

Opportunity

The manufacturer needed an inspection process capable of:

Locating the lift hook automatically within a continuous image stream
Inspecting the weld zone across two exhaust component variants and two hook types
Detecting a mislocated hook, incomplete or uneven welds, porosity, spatter, undercut and weld geometry deviations
Identifying surface-visible defects above 1 mm
Applying consistent acceptance criteria to every inspected component
Providing clear OK and NG decisions with visual evidence

The goal was to replace a variable manual check with consistent, evidence-backed weld inspection while supporting future expansion across additional variants.

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Jidoka’s Approach

Jidoka configured a KOMPASS-powered inspection system combining continuous image capture, automatic frame selection, AI-based weld analysis and traceable quality reporting.

Continuous Two-Camera Image Capture

Two industrial cameras with auto-focus lenses continuously capture each passing exhaust component at the inspection station, removing the need for manual image triggering.

Automatic Lift-Hook Frame Selection

KOMPASS ignores frames without the lift hook and automatically selects the image containing the hook for AI inference. The process achieved at least 99% accuracy across two exhaust variants and two hook types.

KOMPASS-Powered Weld Inspection

The selected images are processed on an edge computer using an AI deep-learning model. KOMPASS identifies a mislocated lift hook, incomplete or uneven weld distribution, porosity, spatter, undercut, weld geometry deviations and other surface-visible anomalies.

The system detects surface-visible defects above 1 mm within the lift-hook weld zone. It complements existing NDT and destructive checks used to assess weld penetration, subsurface conditions and mechanical strength.

Configurable Criteria and Variant Support

Quality teams can configure model confidence thresholds, minimum defect sizes and acceptance criteria for individual defect classes. This helps convert visual standards into objective and repeatable inspection decisions.

KOMPASS’s guided DOJO self-training workflow also enables additional component variants to be introduced without coding or specialist AI knowledge.

Automated OK/NG Decisions

KOMPASS classifies each inspected component as OK or NG. For rejected parts, the operator interface displays an annotated image showing the detected defect and its location.

The system architecture also supports line interlocks, Andon alerts through PLC and REST-based access to defect insights.

Traceable Quality Insights

Inspection results and images can be linked to the relevant part identity. KOMPASS provides reporting by batch, part name and defect type, helping quality teams review recurring weld issues and support root-cause analysis.

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Big Wins

A repeatable weld-inspection process combining automatic image selection, consistent AI decisions and visual quality evidence.

At Least 95% Defect Detection Recall

Reliable identification of the surface-visible weld defect classes.

At Least 99% Automatic Frame Selection

Consistent selection of the frame containing the lift hook from the continuous image stream.

Surface-Visible Defects Above 1 mm

Detection of small weld anomalies within the lift-hook inspection zone.

5% or Lower False Call Rate

Reduced unnecessary rejection and additional review of conforming components.

With Jidoka’s KOMPASS-powered system, the manufacturer established a repeatable and evidence-backed approach to lift-hook weld inspection. Automatic frame selection removes dependence on manually identifying the inspection moment, while configurable AI criteria support consistent OK and NG decisions. Annotated defect images and structured reports provide clearer quality evidence and create a scalable foundation for inspection across additional exhaust component variants.

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