Acceptance sampling plan of quality inspection for ocean dataset

Abstract

Compared with the dataset of industrial products, ocean datasets have several distinct characteristics, such as large quantities and being multi-source, multi-dimension and multi-type. Based on the acceptance quality level (AQL) and limit quality level (LQL), we designed an acceptance sampling plan of quality inspection for ocean datasets (ASP-OD), used this plan to inspect ocean dataset quality, and evaluated its advantage. ASP-OD has a consistent and stable discriminatory power independent of lot size, which solves the problem of ‘strictness for large lot size, toleration for small lot size’ in the percent sampling plan. ASP-OD establishes a relationship between lot size and sampling size, and provides a plan for a given lot size. This plan overcomes the deficiency of ISO 2859-based sampling plans, different lot size corresponding to the same sampling plan, in the quality inspection of ocean datasets. Collectively, this study suggests that ASP-OD is a suitable sampling plan for the inspection of ocean dataset quality.

Keywords::

• ocean dataset
• quality inspection
• AQL
• LQL
• acceptance sampling plan

Disclosure statement

No competing financial interests exist.

Additional information

Funding

This work was supported by the National Science Foundation, China (grants number 61272098 to D.-M. H.), and the Natural Science Foundation of Shanghai, China (grant number 13ZR1455800 to 22 Z.-H. W.).