Co-processing recycled waste during cement production, i.e., using alternative materials such as secondary raw materials or secondary raw fuels, is widely practiced in developed countries. ...Alternative raw materials or fuels contain high concentrations of heavy metals and other hazardous chemicals, which might lead to the potential for dangerous heavy metals and hazardous chemicals to be transferred to clinker or cement products, resulting in exposure and emissions to people or the environment. Managing input materials and predicting which inputs affect the final concentration is essential to prevent potential hazards. We used the data of six heavy metals by input raw materials and input fuels of cement manufacturers in 2016–2017. The concentrations of Pb and Cu in cement were about 10–200 times and 4 to 200 times higher than other heavy metals (Cr, As, Cd, Hg), respectively.
We profiled the influence of heavy metal concentration of each input material using the principal component analysis (PCA), which analyzed the leading causes of each heavy metal. The Random Forest (RF) ensemble model predicted cement heavy metal concentrations according to input materials. In the case of Cu, Cd, and Cr, the training performance showed R square values of 0.71, 0.71, and 0.92, respectively, as a result of predicting the cement heavy metal concentration according to the heavy metal concentration of each cement input material using the RF model, which is a machine learning model. The results of this study show that the RF model can be used to predict the amount and concentration of alternative raw materials and alternative fuels by controlling the concentration of heavy metals in cement through the concentration of heavy metals in the input materials.
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•Heavy metal concentrations in South Korean cements were assessed.•The role of inputs materials used was an important influence factor.•RF model can expect the concentration of Cu, Cr, Cd in input materials.•This model is only applied to analyzable inputs.
In this paper, we consider demand management decisions for an assemble-to-order production system in which both the availability of intermediate material and assembly capacity are limited. For each ...incoming order, the manufacturer must decide whether to accept it and what due date to quote for an accepted order. The actual assembly dates are still subject to change after these decisions, and a production schedule must be maintained to guarantee that the quoted due dates are met. Therefore, the decisions on accepting orders and quoting due dates must be made with incomplete knowledge of the actual resources used to fulfill the orders. To address these factors, we model this situation and develop a novel revenue management approach using bid prices. An extensive numerical study demonstrates the good performance of the proposed approach in comparison with benchmark algorithms and an ex-post optimal solution applied over a wide range of different supply and demand scenarios. Our results suggest that the consideration of assembly capacity constraints is more vital than the consideration of intermediate material constraints in our test cases.
In the bag-packing problem, several items are selected so that the sum weight should be closest to the target weight. However, in some cases, the sum weight might be far from the target weight. To ...avoid such an insufficient outcome, the method of dividing the input materials by a certain weight is proposed. Its weight for division is decided so that the number of feasible solutions should be increased. For each of the divided groups, which items to be included in the contents of a bag is determined. Many of the simulation results seem to prove the proposed method to be effective.
Pyroprocessing is a promising technology for managing spent nuclear fuel. The nuclear material accounting of feed material is a challenging issue in safeguarding pyroprocessing facilities. The input ...material in pyroprocessing is in a solid-state, unlike the solution state in an input accountability tank used in conventional wet-type reprocessing. To reduce the uncertainty of the input material accounting, a double-stage homogenization process is proposed in considering the process throughput, remote controllability, and remote maintenance of an engineering-scale pyroprocessing facility. This study tests two types of mixing equipment in the proposed double-stage homogenization process using surrogate materials. The expected heterogeneity and accounting uncertainty of Pu are calculated based on the surrogate test results. The heterogeneity of Pu was 0.584% obtained from Pressurized Water Reactor (PWR) spent fuel of 59 WGd/tU when the relative standard deviation of the mass ratio, tested from the surrogate powder, is 1%. The uncertainty of the Pu accounting can be lower than 1% when the uncertainty of the spent fuel mass charged into the first mixers is 2%, and the uncertainty of the first sampling mass is 5%. KCI Citation Count: 0
The paper presents a new problem class, the Economic Lot and Supply Scheduling Problem (ELSSP). The ELSSP deals with the simultaneous vehicle routing and production planning and is an extension of ...the well known Economic Lot Scheduling Problem (ELSP). To solve the described problem the junction point method of Yao and Elmaghraby (2001) for the solution of the ELSP under a power-of-two policy is modified and extended in order to consider the vehicle routing problem caused by the deliveries of the input materials.
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