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Tytuł artykułu

Adaptive Stochastic Approach for Evaluating Service Level Using a (SIM-ESL) Module Developed for Optimizing Product Availability and Order Accuracy

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Warianty tytułu
Języki publikacji
EN
Abstrakty
EN
Inventory decisions are both high risk and high benefit throughout supply chain. Inventory management plays a crucial role since it assists manufacturing firms enhance their efficiency and competitiveness. Service level is a basic performance indicator of shortage inventory when an order is placed. Precise forecasts and optimum level of inventory can decrease the stock-outs and enhance the inventory service level. Finished goods are most common form of inventories have direct related with customer. Thus, the importance of specifying the suitable level of finished goods inventory assets for right planning and control of factory operations and optimization of the overall process to optimize production cost and time and consequently to improve service level. So, inventory management system supported by real time is requisite to ensure consistently both product availability and order accuracy. In this study, adaptive stochastic inventory management approach for evaluation service level was modelled which addressed inventory policies in order to optimize service level as a realistic value. This approach developed a Stochastic Inventory Management for Evaluating Service Level (SIMESL) module basically formulated Computational Intelligent (CI) in such a way that evaluated Availability Of Product (AOP) and Accuracy Of Order (AOO). It is structured with two models are: Evaluation Dynamic Maximum Economic Order Quantity (EDEOQ) model developed Artificial Neural Network (ANN) to evaluate the optimum inventory level of finished goods as a function of product varied demand and lead time. The second one, Variability Between-Among Dynamic Economic Order Quantity (VB-ADEOQ) is modeled a fuzzy logic to estimate the performance measures (AOP and AOO) that make sure the required order is being processed and delivered on time. Finally, the effectively of the adaptive approach is evaluated through a tested theoretical data. The obtained results were proof it’s efficiently in exactly evaluating of an unavailable the required demand about 46.937% and delivered to their final destination without errors about 56.655%. While, Taguchi method used to optimize and determine relative magnitude of the effect of various factors and their interactive. The obtained results were proved and reliability in determining the customer satisfaction score in real-world. Finally, the developed module was proved their reliability and accurately in addressing the vague data, uncertainty, no formulas, and varied inputs in determining the customer satisfaction score in real-world. Consequently, it clearly makes the developed module a better choice for inventory level forecasting, and then it will assist manufacturing industries improve their business process procedures without incurring significant capital expenditure.
Wydawca
Rocznik
Tom
Strony
220--228
Opis fizyczny
Bibliogr. 30 poz., rys., tab.
Twórcy
  • Production Engineering and Metallurgy Department University of Technology, Baghdad, Iraq
autor
  • Production Engineering and Metallurgy Department University of Technology, Baghdad, Iraq
  • Production Engineering and Metallurgy Department University of Technology, Baghdad, Iraq
Bibliografia
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  • [7] E.A. Silver, H. Naseraldin, D.P. Bischak. “Determining the reorder point and order-up-to-level in a periodic review system so as to achieve a desired fill rate and a desired average time between replenishments,” Journal of the Operational Research Society, vol. 60, no. 9, pp. 1244-1253, Sep. 2009, https://doi.org/10.1057/pal-grave.jors.2602655.
  • [8] S. Moradizadeh, “Economic Order Quantity (EOQ) Measurement Using Intelligent Systems Techniques” MSc. Thesis, the Faculty of Graduate Studies and Research, Industrial Systems Engineering, University of Regina, 2019.
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  • [10] E.G. Tarradellas, E. Babiloni, M.J. Canós-Darós, L.C. Darós, S.E. Miguel. “Fuzzy modeling approach to on-hand stock levels estimation in (R, S) inventory system with lost sales,” Journal of Industrial Engineering and Management, vol. 13, no. 3, p. 464, Sep. 2020, https://doi.org/10.3926/jiem.3071.
  • [11] J.-C.B. Munyaka, S.V. Yadavalli. “Inventory management concepts and implementations: A systematic review,” South African Journal of Industrial Engineering, vol. 32, no. 2, Jan. 2022, https://doi.org/10.7166/33-2-2527.
  • [12] Md. R.I. Slam, M. Monjur, T. Akon. “Supply Chain Management and Logistics: How important interconnection is for business success,” Open Journal of Business and Management, vol. 11, no. 05, pp. 2505-2524, Jan. 2023, https://doi.org/10.4236/ojbm.2023.115139.
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  • [30] K.M.J. Rashid, “Optimize the Taguchi method, the signal-to-noise ratio, and the sensitivity,” International Journal of Statistics and Applied Mathematics, vol. 8, no. 6, pp. 64-70, Nov. 2023, https://doi.org/10.22271/maths.2023.v8.i6a.1406.
Uwagi
Opracowanie rekordu ze środków MNiSW, umowa nr POPUL/SP/0154/2024/02 w ramach programu "Społeczna odpowiedzialność nauki II" - moduł: Popularyzacja nauki i promocja sportu (2025).
Typ dokumentu
Bibliografia
Identyfikator YADDA
bwmeta1.element.baztech-32e0f96e-0a54-4c7a-9c16-8f5155eba044
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