Research Article Designing and Selection of Mixed Relational Complete Chain Sampling Plan Using Variance Principle (RCCSP-VP) K. Rebecca Jebaseeli Edna, 1 V. Jemmy Joyce, 1 K. Martin Sagayam, 1 S. Elizabeth Amudhini Stephen , 1 Hatira GunerhanIt , 2 and Homan Emadifar 3 1 DepartmentofMathematics,KarunyaInstituteofTechnologyandSciences,DeemedtobeUniversity,Coimbatore641114,India 2 Department of Mathematics, aculty of Education, Kafkas University, Kars, Turkey 3 Department of Mathematics, Hamedan Branch, Islamic Azad University, Hamedan, Iran Correspondence should be addressed to Homan Emadifar; homan_emadi@yahoo.com Received 17 July 2022; Revised 13 January 2023; Accepted 16 March 2023; Published 21 April 2023 Academic Editor: Amitava Mukherjee Copyright © 2023 K. Rebecca Jebaseeli Edna et al. Tis is an open access article distributed under the Creative Commons Attribution License, which permits unrestricted use, distribution, and reproduction in any medium, provided the original work is properly cited. Tere are many measurable dimensions for products in industries, and their quality should not deviate too much from the established norm. Terefore, a big part of the consignment’s acceptance is determined by the variance of distributions. In the production of surgical or critical care equipment, measurable dimensions are very important, since each part of the equipment should meet the indicated specifcation with tolerable variance. Terefore, a procedure for constructing a combined (mixed) sampling plan with a variance measure is provided in this module. Tis sampling plan supports the medical device engineer in establishing the target dimensions for the quality control of medical instruments because many variations in dimensions result in heavy losses for manufacturers. Te relational complete chain sampling plan (RCCSP) is utilized in the II phase inspection to have a signifcant impact on production quality. Te performance measures, algorithm, and design of the mixed sampling plan are provided. Te plan is indexed through AQL. In order to choose the plan easily, the table is set up with an example. 1. Introduction Several acceptance sampling inspections through vari• ables are developed with the mean. However, medical device engineers feel that variance is the most powerful tool to improve variable sampling plans. Many quality control experts also argue that quality compromises are not desirable, as defects in many industries can lead to signifcant losses. Terefore, nonconformities are main• tained in the manufacturing process to persist in com• petitive markets. Measuring and irradiating deviations help reduce production costs and improve the quality of the product. In mixed sampling inspections, there are two phases that consider both the quality of the variable and attribute factors when deciding whether a lot should be accepted or rejected. Mixed sample plans are frequently applied at many production phases due to contemporary quality control systems. Variable criteria play an important part in the control point in industries. Many items in industries have measurable dimensions, and their quality should not difer signifcantly from the specifed standard. As a result, the process variation has a sub• stantial impact on the decisions made by lots. Both the variability and the number of nonconformities must be decreased in several quality control areas. Te combined variable•attribute sampling plan has two phases. Te frst phase is inspection through variables, and the second phase is through attributes. Te test in the second phase plays an important role because a relational complete chain sampling plan correlates current consignment re• sults with the results of previous consignment quantities. Tistypeofinspectiongivesmoresecuritytotheproducer and the consumer, since the second•phase inspection depends on the current consignment results and the re• sults of previous consignment quantities, which has a high efect on the quality of the product. Hindawi Mathematical Problems in Engineering Volume 2023, Article ID 5406966, 8 pages https://doi.org/10.1155/2023/5406966