Plant location selection of a manufacturing industry using analytic hierarchy process approach

Gothwal, Suman; Saha, Rajeev

doi:10.1504/ijsom.2015.071531

Cited by 17 publications

(13 citation statements)

References 38 publications

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“…Some techniques have been developed for criteria ranking like AHP method, 48,49 technique for order preference by similarity to ideal solution (TOPSIS) 50 and fuzzy modeling technique 51,52 . However, AHP has been mostly used in many studies due to its simplicity, easy computation, ability to follow intuitive problem solving technique and its ability to integrate qualitative and quantitative criteria 53,54 .…”

Section: Methodsmentioning

confidence: 99%

Hybrid neurofuzzy wind power forecast and wind turbine location for embedded generation

et al. 2020

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Wind energy uptake in South Africa is significantly increasing both at the micro-and macro-level and the possibility of embedded generation cannot be undermined considering the state of electricity supply in the country. This study identifies a wind hotspot site in the Eastern Cape province, performs an in silico deployment of three utility-scale wind turbines of 60 m hub height each from different manufacturers, develops machine learning models to forecast very short-term power production of the three wind turbine generators (WTG) and investigates the feasibility of embedded generation for a potential livestock industry in the area. Windographer software was used to characterize and simulate the net output power from these turbines using the wind speed of the potential site. Two hybrid models of adaptive neurofuzzy inference system (ANFIS) comprising genetic algorithm and particle swarm optimization (PSO) each for a turbine were developed to forecast very short-term power output. The feasibility of embedded generation for typical medium-scale agricultural industry was investigated using a weighted Weber facility location model. The analytical hierarchical process (AHP) was used for weight determination. From our findings, the WTG-1 was selected based on its error performance metrics (root mean square error of 0.180, mean absolute SD of 0.091 and coefficient of determination of 0.914 and CT = 702.3 seconds) in the optimal model (PSO-ANFIS). Criteria were ranked based on their order of significance to the agricultural industry as proximity to water supply, labour availability, power supply and road network. Also, as a proof of concept, the optimal location of the industrial facility relative to other criteria was X = 19.24 m, Y = 47.11 m. This study reveals the significance of resource forecasting and feasibility of embedded generation, thus improving the quality of preliminary resource assessment and facility location among site developers.

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Section: Methodsmentioning

confidence: 99%

Hybrid neurofuzzy wind power forecast and wind turbine location for embedded generation

et al. 2020

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“…PROMETHEE, TOPSIS and MAUT have been used to select the location of a new casino (Ishizaka, Nemery, & Lidouh, 2013). AHP was used for selecting a plant location (Gothwal & Saha, 2015). As it can be seen, there are a high number of studies on location selection.…”

Section: Locational Decision In Offshore Outsourcing Processmentioning

confidence: 99%

A hybrid FCM-AHP approach to predict impacts of offshore outsourcing location decisions on supply chain resilience

López

Ishizaka

2019

Journal of Business Research

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“…Among the most prevalent applications of the AHP is the risk assessment of industrial parks (Liang and He [15]) as well as at the plant location of manufacturing industries [16]. Particularly, Liang and He [15] examined the risk control of chemical industrial parks as one of the most important managerial goals of chemical enterprises.…”

Section: Analytical Hierarchy Process (Ahp)mentioning

confidence: 99%

“…Among the feasible methods to practically evaluate the risk control in chemical industrial parks is AHP, being a classical multiple attribute decision-making method that has been structured on the key construction of a judgment matrix to determine the success or failure of the procedural analysis. In a similar industrial context, Gothwal and Saha [16] introduced an AHP that can simplify complex decision problems into simpler hierarchies, having flexibly incorporated financial and non-financial factors that determine the decision alternatives in a systematic way upon consensus. These authors structured an AHP modeling to examine a real case study under which industrial manufacturing plant to be valued and selected.…”

Section: Analytical Hierarchy Process (Ahp)mentioning

confidence: 99%

Development of a Holistic Assessment Framework for Industrial Organizations

et al. 2019

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The evaluation and selection among the best production practices beyond the conventional linear models is, nowadays, concerned with those holistic approaches drawn toward environmental assessment in industry. Therefore, researchers need to develop an analysis that can evaluate the performance of industrial organization in the light of their environmental viewpoint. This study implemented a pilot co-integrated scheme based on an innovative in-house Holistic Assessment Performance Index for Environment (HAPI-E) industry tool while assimilating the principles of circular economy through the Eco-innovation Development and Implementation Tool (EDIT). For the latter, nine qualitative indicators were motivated and enriched the weighting criteria of the questionnaire. The decomposition of the complexity and preferences mapping was accompanied by a multi-criteria holistic hierarchical analysis methodology in order to synthesize a single index upon a need-driven scoring. This multi-criteria decision approach in industry can quantify the material and process flows, thus enhancing the existing knowledge of manipulating internal resources. The key-criteria were based on administrative, energy, water, emissions, and waste strategies. Subsequently, the HAPI-E industry tool was modeled on the food industry, being particularly focused on pasta-based industrial production. Then, the parameters of this tool were modeled, measured, and evaluated in terms of the environmental impact awareness. The magnitude of necessary improvements was unveiled, while future research orientations were discussed. The HAPI-E industry tool can be utilized as a precautionary methodology on sustainable assessment while incorporating multifaceted and quantification advantages.

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Plant location selection of a manufacturing industry using analytic hierarchy process approach

Cited by 17 publications

References 38 publications

Hybrid neurofuzzy wind power forecast and wind turbine location for embedded generation

Hybrid neurofuzzy wind power forecast and wind turbine location for embedded generation

A hybrid FCM-AHP approach to predict impacts of offshore outsourcing location decisions on supply chain resilience

Development of a Holistic Assessment Framework for Industrial Organizations

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