Refine your search
Collections
Co-Authors
Journals
Year
A B C D E F G H I J K L M N O P Q R S T U V W X Y Z All
Das, Ankur
- A Comparative Analysis of Different Multi-Criteria Inventory Control Methods for a Pump Manufacturing Company
Abstract Views :293 |
PDF Views:0
Authors
Ankur Das
1,
Santanu Das
2
Affiliations
1 Global Institute of Management & Technology, Krishnanagar, Nadia, West Bengal, IN
2 Kalyani Government Engineering College, Kalyani, Nadia, West Bengal, IN
1 Global Institute of Management & Technology, Krishnanagar, Nadia, West Bengal, IN
2 Kalyani Government Engineering College, Kalyani, Nadia, West Bengal, IN
Source
Manufacturing Technology Today, Vol 21, No 3-4 (2022), Pagination: 3-9Abstract
In today’s highly competitive environment, several inventory control strategies are introduced in different manufacturing organizations or supply chain perspective. Multiple criteria based inventory control technique is required to achieve efficient inventory management system which contemplate the different aspects of inventory as well as supply chain management system. In this context, monthly demand, inventory consumption value and lead time are considered as the inventory performance measuring criteria. Here, different multiple criteria based ‘ABC’ inventory control methods have been utilized to categorize the stock items properly. In addition, the overall inventory service costs and average fill rate are computed for different MCIC techniques. These inventory control approaches have been applied to raw material inventories of a pump manufacturing company. Ng-model performs better than ZF and H-models where the overall fill rate of stock items has been considered. ZF-model and H-model ensure better results from Ng-model regarding total safety stock inventory cost.Keywords
Inventory Control, ABC Analysis, Inventory Consumption Value, MCIC, Pump Manufacturing.
References
- Arikan, F., & Citak, S. (2017). Multiple criteria inventory classification in an electronics firm. International Journal of Information Technology & Decision Making, 16, 1-17.
- Babai, M. Z., Ladhari, T., & Lajili, I. (2014). On the inventory performance of multi-criteria classification methods: empirical investigation. International Journal of Production Research, 53, 279-290.
- Das, A., & Das, S. (2016). Supplier selection for a pump manufacturing organization by hybrid AHP-TOPSIS technique and its impact on inventory. International Journal of Analytic Hierarchy Process, 8, 334-352.
- Das, A., & Das, S. (2019). Application of a multi criteria inventory control technique over conventional ABC analysis in a pump manufacturing organization. Journal of the Association of Engineers, India, 89, 1-7.
- Ernst, R., & Cohen, M. A. (1990). Operation related groups (ORGs): a clustering procedure for production/inventory system. Journal of Operation Management, 9, 574-598.
- Flores, B. E., Olson, D. L., & Dorai, V. K. (1992). Management of multicriteria inventory classification. Journal of Mathematical and Computer Modelling, 16, 71-82.
- Hadi-Vencheh, A. (2010). An improvement to multiple criteria ABC inventory classification. European Journal of Operational Research, 201, 962-965.
- Iqbal, Q., Malzahn, D., & Whitman, L. (2017). Statistical analysis of multi-criteria inventory classification models in the presence of forecast upsides. International Journal of Production & Manufacturing Research, 5, 15-39.
- Kaabi, H., & Jabeur, K. (2016). A new hybrid weighted optimization model for multi criteria abc inventory classification. Proceedings of the Second International Afro-European Conference for Industrial Advancement, 261-270.
- Mallick, B., Das, S., Sarkar, B., & Das, S. (2019). Application of the modified similarity-based method for multi-criteria inventory classification. International Journal of Decision Science Letters, 8, 455-470.
- Mallick, B., Dutta, O. N., & Das, S. (2012). A case study on inventory management using selective control techniques. Journal of the Association of Engineers, India, 82, 10-24.
- Ng, W. L. (2007). A simple classifier for multiple criteria ABC analysis. Europian Journal of Operational Research, 177, 344-353.
- Parnianianifard, A., Zemouche, A., Imran, M. A., & Wuttisittikulkij, L. (2020). Robust simulation-optimization of dynamic-stochastic production/inventory control system under uncertainty using computational intelligence. International Journal of Uncertain Supply Chain Management, 8, 633–648.
- Partovi, Y. F., & Anandarajan, M. (2002). Classifying inventory using an artificial neural network approach. International Journal of Computers & Industrial Engineering, 41, 389-404.
- Ramanathan, R. (2006). ABC inventory classification with multiple criteria using weighted linear optimization. Journal of Computers & Operations Research, 33, 695-700.
- Rao, R. V., & Lakshmi, R. J. (2021). Ranking of Pareto-optimal solutions and selecting the best solution in multi- and many-objective optimization problems using R-method. International Journal of Soft Computing Letters, 3, 100-115.
- Rezaei, J., & Davoodi, M. (2005). Multi-item fuzzy inventory model with three constraints: genetic algorithm approach. [Lecture Notes in Artificial Intelligence, 3809], 1120-1125.
- Zhou, P., & Fan, L. (2007). A note on multi-criteria abc inventory classification using weighted linear optimization. Europian Journal of Operational Research, 182, 1488-1491.