A multiphase acceptance sampling model by attributes to investigate the production interruptions in batch production within tobacco industry

Abstract

Purpose

This paper aims to create a new decision-making procedure that uses “Lot-by-Lot Acceptance Sampling Plan by Attributes” methodology in the production processes when any production interruption is observed in tobacco industry, which is a significant example of batch production.

Design/methodology/approach

Based on the fish bone diagram, the reasons of the production interruptions are categorized, then Lot-by-Lot Acceptance Sampling Plan by Attributes is studied to overcome the reasons of the production interruptions. Furthermore, managerial aspects of decision making are not ignored and hence, acceptance sampling models are determined by an Analytical Hierarchy Process (AHP) among the alternative acceptance sampling models.

Findings

A three-phased acceptance sampling model is generated for determination of the reasons of production interruptions. Hence, the necessary actions are provided according to the results of the proposed acceptance sampling model. Initially, 729 alternative acceptance sampling models are found and 38 of them are chosen by relaxation. Then, five acceptance sampling models are determined by AHP.

Practical implications

The current experience dependent decision mechanism is suggested to be replaced by the proposed acceptance sampling model which is based on both statistical and managerial decision-making procedure.

Originality/value

Acceptance sampling plans are considered as a decision-making procedure for various cases in production processes. However, to the best of our knowledge Lot-by-Lot Acceptance Sampling Plan by Attributes has not been considered as a decision-making procedure for batch production when any production interruption is investigated.

Citation

Yüksel, D., Kazancoglu, Y. and Sarma, P.R.S. (2022), "A multiphase acceptance sampling model by attributes to investigate the production interruptions in batch production within tobacco industry", International Journal of Quality & Reliability Management, Vol. 39 No. 3, pp. 836-858. https://doi.org/10.1108/IJQRM-03-2021-0078