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Determining the Optimum Replacement Time of Dosing Pump Components Using the Age Replacement Model (Case Study at PDAM Tirtawening Bandung) Julita Nahar
International Journal of Quantitative Research and Modeling Vol. 6 No. 4 (2025): International Journal of Quantitative Research and Modeling
Publisher : Research Collaboration Community (RCC)

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.46336/ijqrm.v6i4.1138

Abstract

The increase in population over time has a direct impact on the rising demand for clean water supply services, making the availability and management of water resources an increasingly critical aspect. To maintain water quality and supply continuity, reliable production machines are required. One of the machines used is a dosing pump, whose critical component is the valve ring. To ensure continuous operation without machine failure during the production process, appropriate maintenance is required by determining the optimum replacement time interval for the valve ring component using the Age Replacement model. The results of the data analysis show that the failure of the valve ring component follows a Nonhomogeneous Poisson Process (NHPP) with a Power Law Process (PLP) failure model. The optimum replacement time for the valve ring component based on the Age Replacement model is every 103.87 days of operation with a total replacement cost risk of Rp. 925,063.20, and this model is able to reduce the replacement cost of the valve ring component by 46.72%.
Green Economy-Based Multi-Objective Optimization Model for Agricultural Supply Chain Network Design Using Lexicographic Method Febrian, Rizky; Chaerani, Diah; Nahar, Julita
Jurnal Matematika Integratif Vol 22, No 1: April 2026
Publisher : Department of Matematics, Universitas Padjadjaran

Show Abstract | Download Original | Original Source | Check in Google Scholar | DOI: 10.24198/jmi.v22.n1.69577.119-132

Abstract

This Article presents a multi-objective optimization model for agricultural supply chain network design that incorporates green economy principles. The problem is formulated as a Many-to-Many Location Routing Problem (MMLRP) to address strategic decisions including Regional Food Hub site selection, commodity flow allocation between producers and hubs, distribution routing to consumer zones, and warehouse capacity planning. Two objective functions are solved hierarchically using the Lexicographic Method: maximizing demand fulfillment as the primary objective, followed by minimizing total costs comprising shipping, warehousing, and hub construction expenses. The model incorporates flow conservation constraints, capacity limits for producers and demand zones, and logical constraints linking distribution activities to hub establishment. Environmental considerations are integrated through carbon tax components and vehicle emission factors in transportation activities, enabling decision-makers to account for the environmental impact of logistics operations. Results demonstrate that the optimal network configuration identifies strategic hub locations and efficient distribution patterns characterized by short-distance delivery clusters that minimize carbon emissions, while maintaining cross-regional shipments from major production centers to satisfy demand requirements.