In today's manufacturing settings, a sudden increase in the customer demand may enforce manufacturers to alter their manufacturing systems either by adding new resources or changing the layout within a restricted time frame. Without an appropriate strategy to handle this transition to higher volume, manufacturers risk losing their market competitiveness. The subjective experience-based ad-hoc procedures existing in the industrial domain are insufficient to support the transition to a higher volume, thereby necessitating a new approach where the scale-up can be realised in a timely, systematic manner. This research study aims to fulfill this gap by proposing a novel Data-Driven Scale-up Model, known as DDSM, that builds upon kinematic and Discrete-Event Simulation (DES) models. These models are further enhanced by historical production data and knowledge representation techniques. The DDSM approach identifies the near-optimal production system configurations that meet the new customer demand using an iterative design process across two distinct levels, namely the workstation and system levels. At the workstation level, a set of potential workstation configurations are identified by utilising the knowledge mapping between product, process, resource and resource attribute domains. Workstation design data of selected configurations are streamlined into a common data model that is accessed at the system level where DES software and a multi-objective Genetic Algorithm (GA) are used to support decision-making activities by identifying potential system configurations that provide optimum scale-up Key Performance Indicators (KPIs). For the optimisation study, two conflicting objectives: scale-up cost and production throughput are considered. The approach is employed in a battery module assembly pilot line that requires structural modifications to meet the surge in the demand of electric vehicle powertrains. The pilot line is located at the Warwick Manufacturing Group, University of Warwick, where the production data is captured to initiate and validate the workstation models. Conclusively, it is ascertained by experts that the approach is found useful to support the selection of suitable system configuration and design with significant savings in time, cost and effort. 相似文献
The performance of a venturi scrubber in the removal of tar from gas in updraft gasification has been studied. The gasifier has been operated with a husk feed rate of 1.6 × 10?4 kg/s. The venturi scrubber has been operated at a superficial gas velocity of 56.4 m/s at the throat. A wide variety of scrubbing liquids having surface tensions ranging from 0.026 to 0.072 N/m have been used. The Qg/Ql, has been varied in the range of 1000–8000. The tar separation efficiency η has been found to vary from 51 to 98.5%. A mathematical model, assuming steady-state operation, has been developed considering very high pseudosolubility of tar in the scrubbing liquids. The predicted values of η have been compared with experimental results. The model satisfactorily explains the tar removal efficiency of the venturi for Qg/Ql values ranging from 4000 to 8000 for all scrubbing liquids. The following correlation has been developed for predicting venturi scrubber efficiency: . 相似文献
Monocarboxylate transporters (MCTs) are of great research interest for their role in cancer cell metabolism and their potential ability to transport pharmacologically relevant compounds across the membrane. Each member of the MCT family could potentially provide novel therapeutic approaches to various diseases. The major differences among MCTs are related to each of their specific metabolic roles, their relative substrate and inhibitor affinities, the regulation of their expression, their intracellular localization, and their tissue distribution. MCT4 is the main mediator for the efflux of L-lactate produced in the cell. Thus, MCT4 maintains the glycolytic phenotype of the cancer cell by supplying the molecular resources for tumor cell proliferation and promotes the acidification of the extracellular microenvironment from the co-transport of protons. A promising therapeutic strategy in anti-cancer drug design is the selective inhibition of MCT4 for the glycolytic suppression of solid tumors. A small number of studies indicate molecules for dual inhibition of MCT1 and MCT4; however, no selective inhibitor with high-affinity for MCT4 has been identified. In this study, we attempt to approach the structural characteristics of MCT4 through an in silico pipeline for molecular modelling and pharmacophore elucidation towards the identification of specific inhibitors as a novel anti-cancer strategy. 相似文献
The present study aimed to synthesize novel polycationic polymers composed of N-substituted L-2,3-diaminopropionic acid residues (DAPEGs) and investigate their cell permeability, cytotoxicity, and DNA-binding ability. The most efficient cell membrane-penetrating compounds (O2Oc-Dap(GO2)n-O2Oc-NH2, where n = 4, 6, and 8) showed dsDNA binding with a binding constant in the micromolar range (0.3, 3.4, and 0.19 µM, respectively) and were not cytotoxic to HB2 and MDA-MB-231 cells. Selected compounds used in the transfection of a GFP plasmid showed high transfection efficacy and minimal cytotoxicity. Their interaction with plasmid DNA and the increasing length of the main chain of tested compounds strongly influenced the organization and shape of the flower-like nanostructures formed, which were unique for 5/6-FAM-O2Oc-[Dap(GO2)]8-O2Oc-NH2 and typical for large proteins. 相似文献