AiVibe

Industry 4.0 & Manufacturing Operations

OEE Quality

Quality is the OEE factor that measures the share of produced parts that are good the first time, calculated as good count divided by total count, so both scrap and parts needing rework count as losses.

The quality factor compares good count with total count produced during run time. Good parts are those that meet specification on the first pass without rework; rejected parts include scrap and items that must be reworked, even if they are later sold. Because OEE multiplies its factors, a quality loss carries the same weight as an equal percentage loss in availability or performance.

Quality losses correspond to two of the six big losses: startup rejects, produced while a process stabilises after a changeover or start-up, and production rejects, produced during steady-state running. Tracking them separately is useful because startup rejects point to changeover and warm-up practices, while production rejects point to process capability, materials or equipment condition.

Defects must be attributed to the machine or line being measured and to the correct time period, which can be difficult when inspection happens later or at a different station. Automated inspection and product genealogy data improve accuracy. The OEE quality factor is closely related to first pass yield, and process capability studies and statistical process control are common tools for reducing the underlying defects.

Key points

Where AiVibe comes in

AiVibe designs and manufactures the AiAmbA AI Factory as the OEM: edge devices plus AI agents that let people talk to PLC, CNC and robot controllers in plain language. Existing lines are retrofitted with edge devices, and a trained operator confirms every change an agent proposes.

Explore AiVibe’s work in Industry 4.0 & Manufacturing Operations →

Related terms

Terms that refer to OEE Quality

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