Browsing by Author "Sarma, P. R. S."

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Citation - WoS: 2
A multiphase acceptance sampling model by attributes to investigate the production interruptions in batch production within tobacco industry
(EMERALD GROUP PUBLISHING LTD, 2022) Damla Yuksel; Yigit Kazancoglu; P. R. S. Sarma; Yuksel, Damla; Kazancoglu, Yigit; Sarma, P. R. S.
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 - WoS: 27
Citation - Scopus: 34
Evaluating resilience in food supply chains during COVID-19
(Taylor and Francis Ltd., 2024) Yigit Kazancoglu; Muruvvet Deniz Sezer; Melisa Ozbiltekin-Pala; Çisem Lafci; P. R.S. Sarma; Ozbiltekin-Pala, Melisa; Sezer, Muruvvet Deniz; Lafci, Cisem; Kazancoglu, Yigit; Sarma, P. R. S.
The COVID-19 outbreak has revealed weaknesses in the supply chains (SCs) and how easily it can be influenced by these disruptions. Food supply chains (FSCs) is one of the most affected SCs and it needs to be more resilient against SC disruptions because their vulnerable structure such as having perishable products. Therefore this article aims to uncover the need for resilience in FSCs during the COVID-19 outbreak. For this purpose the enablers of resilience on FSCs are determined after a detailed examination of the current literature. Then the graph theory matrix approach has been used to reveal the relationships between these enablers and investigate importance of enablers of resilience in FSCs during COVID-19 outbreak. It is significant to determine preference of enablers and rank of importance to take actions effectively. Depending on the results the rank orders of the enablers are classified as readiness collaboration with stakeholders IT alignment risk aware responsiveness flexibility appearance and sustainability respectively. Suggested implications can be provided benefits for policymakers and managers in FSCs. © 2024 Elsevier B.V. All rights reserved.