Single traditional multi-criteria decision-making (STMCDM) methods are weak in evaluating consistent criteria weights for industrial site selection. As a result, unfavourable industrial locations could not attract new industries, giving rise to brownfields with high carbon emissions. To solve the constraints of STMCDM, integrated multi-criteria decision-making (IMCDM) method was developed. The interaction of the analytic network process (ANP) and the triangular fuzzy numbers of the fuzzy-analytic hierarchy process (F-AHP) were integrated to create the Network Fuzzy-hierarchy Analytic Process (NFh-AP). Tanjung Langsat Industrial Area spatial criterion data for 2009 and 2019 were collected using GIS to test for the weighting consistency of the ANP, F-AHP, and NFh-AP. The Euclidean distance, raster layer reclassification, and land use and land cover data collected from PLANMalaysia were prepared. The weights and spatial data were submitted to weighted overlay analyses by the GIS. With the 2009 dataset, the ANP, F-AHP, and NFh-AP identified all water bodies as suitable EIP sites, highlighting the constraints of the methods with sparse criteria. The 2019 data with ANP, F-AHP, and NFh-AP identified 2 %, 3 %, and 25 % as the best sites with well-defined boundaries. Due to the poor best suitable areas produced, even with dominant criteria, single approaches have inconsistencies in criterion weighting. The NFh-AP algorithm's weighting consistency is due to networking and fuzzy logic interaction, and it is presented to assist evaluate consistent criteria weights and a simple modelling approach for brownfield-EIP (BF-EIP) site selection. Using spatial criteria for BF-EIP site selection collected elsewhere, the NFh-AP consistency can be tested.