MULTI REFERENCE SKIP-LOT SAMPLING PLAN

Title

MULTI REFERENCE SKIP-LOT SAMPLING PLAN

Creator

Manoj, Meby Joseph; Azarudheen, S.

Description

Skip-lot sampling plans have become significant in modern quality control due to rising production volumes and the demand for cost-effective inspection methods that will yield high-quality outputs. When inspecting a submitted lot, a skip-lot plan is economically favourable and guarantees high quality. Thus, this approach benefits both producers and consumers. The skip-lot sampling plan generally utilizes the same sampling plan as the reference plans for both skipping and normal inspection. However, using the same plan in both phase favours either the producer or the consumer in the most essential situations. This article introduces a novel approach, the Multi Reference Skip-Lot Sampling Plan with the provision of having two different reference plans in the normal and skipping phases of the skip-lot plan. The paper explores the efficacy of this approach by deriving performance measures using a power series approach. To evaluate the proposed plan, a comparison is made with existing skip-lot sampling plans that use single sampling plans or double sampling plans as reference plans. This comparison is based on operational characteristics and average sample number values, accompanied by graphical representations. The comparative analysis demonstrates that the new plan effectively balances the satisfaction of both producers and consumers. Additionally, the study offers a strategy for selecting the plan parameters using the unity value approach, supported by a table providing unity values. 2025, Gnedenko Forum. All rights reserved.

Source

Reliability: Theory and Applications;Volume;20;Issue;2;pp.447-455

Date

01-01-2025

Publisher

Gnedenko Forum

Subject

acceptance sampling plan; average sample number; operational characteristic function; Quality control; skip-lot sampling plan

Coverage

Manoj M.J., Department of Statistics and Data Science CHRIST (Deemed to be University), Bengaluru, India; Azarudheen S., Department of Statistics and Data Science CHRIST (Deemed to be University), Bengaluru, India

Rights

Restricted Access; Hardcopy may be available in the library

Relation

ISSN: 19322321;

Format

online

Language

English

Type

Article

Identifier

https://doi.org/10.24412/1932-2321-2025-284-447-455

https://www.scopus.com/pages/publications/105010325797?origin=resultslist