A cost minimization model for a multi-component product closed loop supply chain considering big data dimensions

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ID: 286322
2021
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Abstract
The integration of forward and reverse flows in a closed loop supply chain has led to more uncertainties such as order forecasting, information distortion, demand forecasting, and varying return and return quality behavior. The rise of digitization in supply chain management holds reasonable cause to believe that the adoption of Big Data Analytics (BDA) into the CLSC would be a viable solution. Big Data, through its dimensions of Variety, Velocity, and Volume, has the potential to increase the accuracy of decision-making in procurement, create more precise forecasts in demand, increase the probability and quality of returns. Despite the abundant gains that may be realized, current literature and mathematical modelling on BDA capable CLSCs are scarce and barely tackle the potential effect on the operational decisions a manufacturer must make when facing the aforementioned uncertainties. To address this gap, a mixed integer nonlinear programming mathematical model for a multicomponent product in a CLSC with BDA integration was constructed from the manufacturer’s point of view. The system considers uncertainties across Procurement, Demand Management, Collection, and Recovery, such as order allocation, demand forecasting, return uncertainty, and recovery failure. The unique feature of this study includes the operationalization of the three dimensions of Big Data, which take on intensity values among low (0.00-0.34), medium (0.35-0.66), or high categories (0.67-1.00). These intensity levels are further integrated into per activity effects, which are observed across the aforementioned uncertainties. Due to the integrative nature of Big Data wherein the dimensions of Variety, Velocity, and Volume coexist, a sensitivity analysis was conducted across seven key combinations (MMM, MLH, MLM, HLM, HLH, HML, HMM) that demonstrated behaviors with the most variation. It was found that the systems with BDA prioritized recycled raw materials and met order targets across 6/7, excluding MLH. This revealed that the system benefits from the order flexibility provided by the procurement effect only when the reverse flow activity effects are at par or supersede the average. Further, regardless of linear or seasonal, it was found that the uplift to actual market demand is proportional to the demand effect. Across all systems, the demand forecast was at par with the actual market, showing that BDA maximizes demand potential for optimality. In terms of collection, BDA was able to uplift return behavior, with more growth experienced in the customer segment with low initial return probability. This shows that BDA is able to transform underutilized areas to enhance
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persistent_1760658230_68f1833637d72 Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors Reyes, Ysabel Dominique L.
Journal Malay Journal
Year 2021
DOI
DOI not found
URL
https://animorepository.dlsu.edu.ph/etdb_induseng/1
Keywords Keywords not found

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