scholarly journals Formulation of Measurement Sampling Plan for Small and Medium Batch Products in Supply Chain

2021 ◽  
Vol 14 ◽  
pp. 123-127
Author(s):  
Yuanpeng Sun

The article studies the supply chain of suppliers and manufacturers, considering the overall benefits of the supply chain, the measurement sampling plan is the small batch sampling plan with the smallest amount of sampling and the strongest discriminative ability. If the quality characteristic data is a measurement value, and the inspection workload is large and the inspection cost is high, it is recommended to adopt the measurement sampling plan based on the Laplace distribution. On the premise of ensuring quality, try to reduce the number of inspected samples as much as possible to reduce the workload and cost of inspection.

Symmetry ◽  
2018 ◽  
Vol 10 (11) ◽  
pp. 653 ◽  
Author(s):  
Saeed Dobbah ◽  
Muhammad Aslam ◽  
Khushnoor Khan

In this paper, we propose a new synthetic sampling plan assuming that the quality characteristic follows the normal distribution with known and unknown standard deviation. The proposed plan is given and the operating characteristic (OC) function is derived to measure the performance of the proposed sampling plan for some fixed parameters. The parameters of the proposed sampling plan are determined using non-linear optimization solution. A real example is added to explain the use of the proposed plan by industry.


2017 ◽  
Vol 40 (7) ◽  
pp. 2240-2248 ◽  
Author(s):  
Saminathan Balamurali ◽  
Jambulingam Subramani

Skip-lot sampling plans have been widely used in industries to reduce the inspection efforts on products that have an excellent quality history. These skip-lot sampling schemes are economically advantageous and useful to minimize the cost of the inspection of the final lots. Also, the skip-lot concept is sound and useful in the design of sampling plans. In this paper, we propose a designing methodology to determine the optimal parameters of a skip-lot sampling plan of type SkSP-2 when the quality characteristic under study follows a normal distribution. The optimal plan parameters are determined to minimize the average sample number subject to satisfying the producer’s and consumer’s risks simultaneously at the acceptable and limiting quality levels, respectively. An optimization problem is formulated in order to construct tables for determining the optimal parameters of the proposed sampling plan for both known and unknown standard deviation cases and the results are compared with the variables single sampling plans.


2012 ◽  
Vol 2012 ◽  
pp. 1-14 ◽  
Author(s):  
Lie-Fern Hsu ◽  
Jia-Tzer Hsu

Supply Chain Management, which is concerned with material and information flows between facilities and the final customers, has been considered the most popular operations strategy for improving organizational competitiveness nowadays. With the advanced development of computer technology, it is getting easier to derive an acceptance sampling plan satisfying both the producer's and consumer's quality and risk requirements. However, all the available QC tables and computer software determine the sampling plan on a noneconomic basis. In this paper, we design an economic model to determine the optimal sampling plan in a two-stage supply chain that minimizes the producer's and the consumer's total quality cost while satisfying both the producer's and consumer's quality and risk requirements. Numerical examples show that the optimal sampling plan is quite sensitive to the producer's product quality. The product's inspection, internal failure, and postsale failure costs also have an effect on the optimal sampling plan.


2016 ◽  
Vol 2016 ◽  
pp. 1-14 ◽  
Author(s):  
Biswajit Sarkar

This paper illustrates a channel coordination and quantity discounts between a vendor and a buyer with single-setup multi-delivery (SSMD) strategy to reduce the joint total cost among supply chain players. The benefit of the coordination between a buyer and a vendor is considered as the vendor requests to the buyer for changing the ordering quantity such that the vendor can be benefited from lower inventory costs. After accepting the buyer’s condition, the vendor compensates the buyer for his increased inventory cost and gives consent for additional savings by offering a quantity discount. The centralized decision making is examined for the effect of this strategy with the presence of backorder for buyer and inspection cost for the vendor. The quantity discount strategy, with the presence of variable backorder and inspections, can allow more savings for all players of supply chain. Some numerical examples, sensitivity analysis, and graphical representations are given to illustrate more savings from existing literature and comparisons between the several demand values.


2016 ◽  
Vol 2016 ◽  
pp. 1-10 ◽  
Author(s):  
Aijun Yan ◽  
Sanyang Liu

Acceptance sampling plans are useful tools to determine whether the submitted lots should be accepted or rejected. An efficient and economic sampling plan is very desirable for the high quality levels required by the production processes. The process capability indexCLis an important quality parameter to measure the product quality. Utilizing the relationship between theCLindex and the nonconforming rate, a repetitive group sampling (RGS) plan based onCLindex is developed in this paper when the quality characteristic follows the Weibull distribution. The optimal plan parameters of the proposed RGS plan are determined by satisfying the commonly used producer’s risk and consumer’s risk at the same time by minimizing the average sample number (ASN) and then tabulated for different combinations of acceptance quality level (AQL) and limiting quality level (LQL). The results show that the proposed plan has better performance than the single sampling plan in terms of ASN. Finally, the proposed RGS plan is illustrated with an industrial example.


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