What is it about?
This paper tackles the challenge of planning production over multiple periods in systems that combine manufacturing and remanufacturing processes. It deals with the complexity of managing inventory that isn't fully visible and uncertain conditions. By using advanced mathematical techniques, the authors turn a complicated, uncertain problem into a simpler one that can be more easily solved. They also propose a method for regularly updating the solution to adapt to changing conditions, which improves decision-making. The study finds that this approach leads to better management compared to methods that don’t update regularly. Additionally, the research shows how manufacturing and remanufacturing costs significantly influence planning decisions. The insights from this paper are valuable for decision-makers in managing production in complex, hybrid systems.
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Why is it important?
This research is important for the following contributions: (1) Improved Decision-Making: By transforming a complex, uncertain problem into a more manageable one, the proposed methods help managers make better-informed decisions, leading to more efficient and effective production planning. (2) Cost Efficiency: Understanding the impact of manufacturing and remanufacturing costs on planning allows companies to optimize their resources, reducing waste and improving overall cost efficiency. (3) Adaptability: The open-loop updating method allows production plans to be adjusted regularly based on new information, making the system more adaptable to changes and uncertainties in the market or production process. (4) Sustainability: By integrating manufacturing and remanufacturing processes, the research supports sustainable practices. Remanufacturing can reduce waste and resource consumption, contributing to environmental sustainability. (5) Theoretical Contribution: The application of advanced mathematical techniques, such as the certainty-equivalence principle and Kalman estimator-derived statistics, adds to the body of knowledge in production planning, providing a foundation for future research and practical applications.
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This page is a summary of: Aggregate production planning problem for a hybrid stochastic system under partially observed state variables, International Journal of Business Performance and Supply Chain Modelling, January 2023, Inderscience Publishers,
DOI: 10.1504/ijbpscm.2023.10062153.
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