International Journal of Industrial Engineering & Production Research

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This paper presents a new formulation for warehouse inventory management in a stochastic situation. The primary source of this formulation is derived from FP model, which has been proposed by Fletcher and Ponnambalam for reservoir management. The new proposed mathematical model is based on the first and the second moments of storage as a stochastic variable. Using this model, the expected value of storage, the variance of storage, and the optimal ordering policies are determined. Moreover, the probability of within containment, surplus, and shortage are computable without adding any new variables. To validate the optimization model, a Monte Carlo simulation is used. Furthermore, to evaluate the performance of the optimal FP policy, It is compared to (s*,S*) policy, as a very popular policy used in the literature, in terms of the expected total annual cost and the service level. It is also demonstrated that the FP policy has a superior performances than (s*,S*) policy.

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Productions of the industries around the world depend on using equipment and machines. Therefore, it is vital to support the supply of equipment and spare parts for maintenance operations, especially in strategic industries that separate optimization of inventory management, supplier selection, network design, and planning decisions may lead to sub-optimal solutions. The integration of forward and reverse spare part logistics network can help optimize total costs. In this paper, a  mathematical model is presented for designing and planning an integrated forward-reverse repairable spare parts supply chain to make optimal decisions. The model considers the uncertainty in demand during the lead-time and the optimal assignment of repairable equipment to inspection, disassembly, and repair centers. A METRIC (Multi-Echelon Technique for recoverable Item Control) model is integrated into the forward-reverse supply chain to handle inventory management. A case study of National Iranian Oil Company (NIOC) is presented to validate the model. The non-linear constraints are linearized by using a linearization technique; then the model is solved by an iterative procedure in GAMS. A prominent outcome of the analyses shows that the same policies for repair and purchase of all the equipment and spare parts do not result in optimal solutions. Also, considering supply, repair, and inventory management decisions of spare parts simultaneously helps decision-makers enhance the supply chain's performance by applying a well-balanced repairing and purchasing policy.

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The construction industry is one of the high-demand industries related to business and projects. Robust materials management that is subject to inventory management is the highest factor to enhance the Supply chain management (SCM) performance that will indicate the project's success within the complexity of the project. This research aims to measure the performance of Supply Chain Management at PT Cahaya Amal Taqwa as a new housing developer who focuses on subsidized housing that faces a project delay because they have less data documentation and analysis from previous projects. The issue is most newcomer construction projects never analyze and measure their supply chain management (SCM) which leads them to confusion about the project improvement. The research uses the Supply Chain Operational Reference (SCOR) method to know how much inventory management impacts supply chain management performance and how it overcomes the issues.   Most studies only measure the SCM performance and show which aspects need to be developed without any scheme of solution offered. This research presents the scheme of improvement for the inventory model and provides forecasting for the whole SCM performance after the implementation of a new model of inventory management. The findings confirm that inventory management significantly impacts the whole supply chain management performance in the construction industry. The development of a solution system brought comprehensive results by classifying KPIs for inventory management and an interdependence network was created to define the new model of inventory system for the solution. This research proves that improving an aspect will impact significantly the whole SCM performance instead of improving KPIs one by one.