Linking forward and backward product quality in a manufacturing/remanufacturing inventory system with price-quality-dependent demand and return rates
Bibliographic record
Abstract
• Interrelationships between forward and backward product quality levels are modeled. • Dynamic demand and return functions, rather than fixed rates, are considered. • A time-dependent return policy, which is more practical in industry, is considered. • Results show that higher quality generally leads to a more profitable strategy. • It is shown that linking forward and backward quality leads to greener strategies. The concepts of remanufacturing and reusing products in a reverse supply chain have garnered significant attention in recent decades. Numerous studies have focused on creating frameworks to model and optimize manufacturing/remanufacturing strategies and inventory levels, accounting for forward and reverse flows. Economic Order/Production/Manufacture Quantity models have consistently provided a solid foundation for scholars to design and enhance closed-loop supply chains across various industries. However, one crucial aspect often overlooked in the literature is the initial quality level of the product and its relationship with the end-of-use quality of returns. Higher quality levels allow for extracting more value from returned items but also demand more investment and higher prices. This study presents a model that addresses the link between forward and reverse quality while ensuring cost-effectiveness. It models the impact of product quality and selling price on demand as observed in practice. It also considers an acceptable return period, aligning with what is commonly practiced in the industry by well-known companies. The findings emphasize the importance of linking forward quality with salvage value and indicate that disregarding this connection can lead to suboptimal strategies. Several numerical analyses and randomized simulations were conducted to explore the model’s behavior and the influence of key factors on the outcomes. The results indicate that producing at a quality level above the minimum standard is not only more environmentally friendly (thanks to increased returns and remanufacturing) but also tends to be more profitable in most cases. The developed model will aid decision-makers in developing optimal supply chain designs and identifying effective remanufacturing and reverse supply chain strategies.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".