PHASE STABILITY AND EQUILIBRIUM CALCULATIONS IN REACTIVE SYSTEMS USING DIFFERENTIAL EVOLUTION AND TABU SEARCH

Reactive separations processes (RSPs), where separation and reaction units are combined, have received considerable interest from chemical engineer

A computational study of the effect of lamp arrangements on the performance of ultraviolet water disinfection reactors

Chemical Engineering Science122299-30

Retrofitting of heat exchanger networks involving streams with variable heat capacity: Application of single and multi-objective optimization

10.1016/j.applthermaleng.2014.09.067Applied Thermal Engineering75677-68

Performance analysis of dividing wall column model for fractionation of oleochemical fatty acid

Fractionation process of oleochemical products in Malaysia normally uses conventional distillation columns (CDC). Due to the considerable amount of energy used in the separation process, there is a need to have an intensified process. Dividing wall column (DWC) is an attractive option which offers big advantages with reduced cost and energy consumption. However, research on its feasibility for oleochemical fractionation is scarce. In this article, we conducted a model-based performance analysis of DWC for oleochemical fatty acid fractionation. The model was designed and simulated using a customised four column configurations in Aspen Plus. A step-by-step design procedure was introduced to aid the model development. Economic and environmental assessment was performed and compared with conventional distillation columns. Hydraulic analysis of several packing type was also performed to gain insights on the column hydrodynamic behaviour. Our result shows that the major economic advantage is in the operating cost with savings of up to 16.9% and 10.2% on cooling and heating utilities, respectively while reduces 10.2% of CO2 emissions. Overall, our study shows the feasibility of fractionating fatty acids in oleochemical industry using DWC. Such assessment is important to assess its feasibility especially during the early stage of technology development prior to industrial implementation

Multi-objective optimization applications in chemical process engineering:tutorial and review

10.3390/PR8050508Processes8550

Comparison of fuzzy and crisp decision matrices: An evaluation on PROBID and sPROBID multi-criteria decision-making methods

The use of multi-criteria decision-making (MCDM) methods to select the most appropriate one from a range of alternatives considering multiple criteria is a suitable methodology for making informed decisions. When constructing a decision or objective matrix (DOM) for MCDM procedure, either crisp numerical values or fuzzy linguistic terms can be used. A review of relevant literature indicates that decision experts often prefer to give linguistic terms (instead of crisp numerical values) based on their domain knowledge, to establish a fuzzy DOM. However, previous research articles have not adequately studied the selection between fuzzy and crisp DOM in MCDM, especially under the context of assessing the financial performance (FP) of listed firms – a notably complex decision-making problem. As such, the primary motivation of this study is to bridge this research gap through comparative analyses of fuzzy and crisp DOM in MCDM. Along this path, and in order to handle fuzzy DOM, this work also proposes two new fuzzy MCDM methods: fuzzy preference ranking on the basis of ideal-average distance (PROBID) and fuzzy sPROBID (simpler PROBID), extending the applicability of the original crisp PROBID and sPROBID methods. Moreover, for the first time in the literature, this work compares the FP rankings obtained using fuzzy MCDM methods with an objective benchmark we have identified, i.e., the real-life stock return (SR)-based ranking. The case study of ranking the FP of 32 listed firms demonstrates that the fuzzy MCDM methods produce higher correlation results with the SR-based ranking. The results also suggest that the proposed fuzzy sPROBID method with triangular fuzzy DOM performs the best for assessing the FP of firms in terms of Spearman’s rank correlation coefficient with the SR-based ranking. Overall, the contributions of this work are three-fold: first, it proposes two new fuzzy MCDM methods (i.e., fuzzy PROBID and fuzzy sPROBID); second, it advances the application of fuzzy MCDM methods in assessing and ranking the FP of listed firms to make rational investment decisions in the financial market; third, it studies the selection between fuzzy and crisp DOM through comparisons with an objective benchmark