A bivariate replacement policy (T, N) under partial product process
Downloads
Published
15-06-2024
DOI:
https://doi.org/10.58414/SCIENTIFICTEMPER.2024.15.2.15Keywords:
Partial Product Process, Replacement Policy, Shock Models.Dimensions Badge
Issue
Section
SECTION B: PHYSICAL SCIENCES, PHARMACY, MATHS AND STATS
License
Copyright (c) 2024 The Scientific Temper
This work is licensed under a Creative Commons Attribution-NonCommercial-ShareAlike 4.0 International License.
Considering an extreme shock maintenance model for a degenerative simple repairable system, explicit expressions for the long-run average cost under the bivariate replacement policy (T, N) has been obtained. The existence of the optimal value of (T, N) has been deduced. A numerical example is included to illustrate the theoretical results.Abstract
How to Cite
Raajpandiyan, T. R., Hussainy, S. T., & Rizwan, U. (2024). A bivariate replacement policy (T, N) under partial product process. The Scientific Temper, 15(02), 2065–2069. https://doi.org/10.58414/SCIENTIFICTEMPER.2024.15.2.15
Downloads
Download data is not yet available.
Similar Articles
- Y. Mohammed Iqbal, M. Mohamed Surputheen, S. Peerbasha, Swarm intelligence-driven HC2NN model for optimized COVID-19 detection using lung imaging , The Scientific Temper: Vol. 16 No. 03 (2025): The Scientific Temper
- Kanchan Chaudhary, Saurabh Charaya, The Implementation of Artificial Intelligence-Based Models of Postoperative Care in Paediatric Healthcare Settings , The Scientific Temper: Vol. 16 No. 12 (2025): The Scientific Temper
- Tursunova N. Isroilovna, Dilbar M. Almuradova, Orifjon A. Talipov, Features of diagnosing ovarian tumors in women of pre- and postmenopausal age , The Scientific Temper: Vol. 14 No. 04 (2023): The Scientific Temper
- A. Rukmani, C. Jayanthi, Fuzzy optimization trust aware clustering approach for the detection of malicious node in the wireless sensor networks , The Scientific Temper: Vol. 15 No. spl-1 (2024): The Scientific Temper
- Amanda Quist Okronipa, Lucy Ewuresi Eghan, A theoretical investigation of students’ adoption of artificial intelligence chatbots using social cognitive theory and uses and gratification theory , The Scientific Temper: Vol. 16 No. 02 (2025): The Scientific Temper
- Mayur Vyas, Piyush Mehta, The sentimental and financial journey of women navigating e-commerce , The Scientific Temper: Vol. 16 No. Spl-1 (2025): The Scientific Temper
- A. MURLIDHAR RAO, AIR POLLUTION AND URBAN HEALTH : SOME ISSUES , The Scientific Temper: Vol. 3 No. 1&2 (2012): The Scientific Temper
- Sivakumar S, Rajasekaran Kondareddy, Kalyani Ayyemperumal, Building SaaS solutions using microsoft azure for achieving safe and secure tax related software , The Scientific Temper: Vol. 14 No. 02 (2023): The Scientific Temper
- N. Saranya, M. Kalpana Devi, A. Mythili, Summia P. H, Data science and machine learning methods for detecting credit card fraud , The Scientific Temper: Vol. 14 No. 03 (2023): The Scientific Temper
- R. Gomathi, Balaji V, Sanjay R. Pawar, Ayesha Siddiqua, M. Dhanalakshmi, Ravi Rastogi, Ensuring ethical integrity and bias reduction in machine learning models , The Scientific Temper: Vol. 15 No. 01 (2024): The Scientific Temper
<< < 20 21 22 23 24 25 26 27 28 29 > >>
You may also start an advanced similarity search for this article.
