Analytic Hierarchy Process Approach Research Articles

Factors influencing communication of virtual teams in times of pandemic: a case study in engineering education

ABSTRACT The COVID-19 pandemic has forced most universities to shift from traditional face-to-face teaching to remote learning. This sudden transition has presented numerous challenges for institutions that were unaccustomed to remote work, particularly in the context of senior design projects in engineering. Therefore, this study aimed to identify the influencing factors and their relative importance in affecting team communication in senior design projects during remote work. The study used the Analytical Hierarchy Process (AHP) approach to measure the level of importance of each factor using pairwise comparison in a structured questionnaire. The survey was distributed among group leaders of senior engineering design projects and faculty members who supervised these projects. The study identified five influencing factors: interaction and relations, trust, technology, time, and working environment. The pairwise comparison revealed that interaction and relations were the most important factor in influencing the communication process during remote work. Based on the identified influencing factors, strategies to improve the effectiveness and collaboration of remote meetings were established, providing a roadmap for universities to better prepare for future disruptions and maintain effective communication within student teams during remote work. Furthermore, these findings could have implications for other areas of higher education and the broader workplace.

Resource supply and demand model of military settlements in the cold weapon era: case of Zhenbao Town, Ming Great Wall

As an important military defense project in Chinese history, the Ming Dynasty Great Wall and its associated military settlements played a crucial role in maintaining border security. A systematic analysis of how military settlements allocated resources based on external threats and geo-strategic needs is essential to understanding their settlements defense systems. However, this aspect has been relatively under-explored in existing research. Therefore, a resource allocation assessment model for Great Wall military settlements during the Cold Weapon era is established to facilitate a more scientific analysis and quantitative assessment of Military Defense Capabilities(MDC) and Military Requirements(MR). This study employs a combined Analytical Hierarchy Process (AHP) and Principal Component Analysis (PCA) approach to determine the weight of each indicator for both military defense capability and military requirement. Spatial clustering using K-means is conducted to visualize the distribution of these strengths and weaknesses. An Ordinary Least Squares (OLS) regression model links military requirements with defense capabilities, assessing the relationship between settlement locations and historical battle sites. Residual analysis is utilized to identify areas of resource over-allocation or under-allocation. The study reveals that the regional differences in military defense capabilities and requirements within the Zhenbao Town area during the Ming Dynasty correspond closely with the locations of frequent conflicts. This finding suggests that the distribution of defensive capabilities were strengthened in areas with challenging terrain, while the effectiveness and allocation of defense capabilities were determined by logistical support and transportation conditions. This study enhances our understanding of historical military strategies from a historical geography perspective and offers innovative insights for analyzing Great Wall settlement, moving beyond mere sensory intuition and historical experience.

The effect of wildfires on flood risk: a multi-hazard flood risk approach for the Ebro River basin, Spain

Abstract. Climate change increases the risk of wildfires and floods in the Mediterranean region. Yet, wildfire hazards are often overlooked in flood risk assessments and treated in isolation, despite their potential to amplify floods. Indeed, by altering the hydrological response of burnt areas, wildfires can lead to increased runoff and amplifying effects. This study aims to comprehensively assess flood risk using a multi-hazard approach, considering the effect of wildfires on flood risk, and integrating diverse socio-economic indicators with hydrological properties. More specifically, this study investigates current and future flood risks in the Ebro River basin in Spain for the year 2100 under the Shared Socioeconomic Pathway 1-2.6 (SSP1-2.6) and SSP5-8.5 scenarios, taking into account projected socio-economic conditions and the effect of wildfires. An analytical hierarchy process (AHP) approach is employed to assign weights to various indicators and components of flood risk based on insights gathered from interviews with seven experts specializing in natural hazards. Results show that the influence of wildfires on the baseline flood risk is not apparent. Under the SSP1-2.6 scenario, regions with high flood risk are expected to experience a slight risk reduction, regardless of the presence of wildfires, due to expected substantial development in adaptive capacity. The highest flood risk, almost double compared to the baseline, is projected to occur in the SSP5-8.5 scenario, especially when considering the effect of wildfires. Therefore, this study highlights the importance of adopting a multi-hazard risk management approach, as reliance solely on single-risk analyses may lead to underestimating the compound and cascading effects of multi-hazards.

Capabilities toward adoption of outcome-based contracts

PurposeManufacturing enterprises have started to offer the “outcome” derived from machines with the help of outcome-based contracts (OBCs). Offering OBCs leads to benefits such as increased revenues, stronger customer relationships and sustainability. However, implementing OBCs requires critical capabilities. Existing literature has focused on identifying these necessary capabilities, but the prioritization and interrelationships among them remain unexplored. This study aims to address this gap.Design/methodology/approachOur study employs a hybrid analytical hierarchy process and interpretative structural modeling approach to prioritize and map interrelationships among OBC-related capabilities within small and medium-sized enterprises (SMEs).FindingsThe findings highlight the importance of digitalization capabilities such as data privacy and security, remote monitoring, and data analytics; and organizational and governance capabilities, including quantifying, controlling, and monitoring risks, teamwork, and leadership, are highlighted.Research limitations/implicationsWe quantitatively prioritize OBC capabilities and establish their level-wise structural interrelationships, which will facilitate a more effective and efficient implementation of OBCs. Due to the emergent nature of OBCs, our study could identify just one SME case company meeting our selection criteria.Originality/valueExisting OBC literature focusses on the design of OBCs in large companies. Similarly, earlier capability-related OBC literature is oriented toward identifying the OBC capabilities to perform specific functions. However, in the current study, we propose a systematic decision-making approach that comprehensively prioritizes and identifies the interrelationships among the capabilities necessary to provide OBCs, thus complementing the existing scientific literature on OBCs. In addition, we focus on SMEs, that have specific limitations and characteristics.

Exploring Internet of Things adoption challenges in manufacturing firms: A Delphi Fuzzy Analytical Hierarchy Process approach.

Innovation is key to gaining a sustainable edge in an increasingly competitive global manufacturing landscape. For Bangladesh's manufacturing sector to survive and thrive in today's cutthroat business environment, adopting transformative technologies such as the Internet of Things (IoT) is not a luxury but a necessity. This article tackles the formidable task of identifying and comprehensively evaluating the impediments to IoT adoption in the Bangladeshi manufacturing industry. We delve deeply into the complex terrain of IoT adoption challenges by synthesizing expert insights and a meticulously selected body of contemporary literature. We employ a robust methodology combining the Delphi method with the fuzzy Analytical Hierarchy Process to systematically analyze and prioritize these challenges. Using this methodology, we leveraged the combined expertise of domain specialists and subsequently employed fuzzy logic techniques to address the inherent ambiguities and uncertainties within the data. Our findings highlight this clear path. They reveal that among the myriad barriers, "Lack of top management commitment to implementing new technology" (B10), "High initial implementation investment costs" (B9), and "Risks associated with switching to a new business model" (B7) loom most extensive, demanding immediate attention. These insights are not confined to academia but serve as a pragmatic guide for industrial managers. Armed with the knowledge gleaned from this study, managers can craft tailored strategies, set well-informed priorities, and embark on a transformational journey toward harnessing the vast potential of IoT in the Bangladeshi industrial sector. This article provides a comprehensive understanding of IoT adoption challenges and industry leaders with the tools necessary to navigate these challenges effectively. This strategic navigation, in turn, contributes significantly to enhancing the competitiveness and sustainability of Bangladeshi manufacturing in the IoT era.

Identifying and Prioritizing the Educational Needs Professors of Medical Sciences in the Field of E-Learning with the Analytic Hierarchy Process Approach

Background: Professors in universities and educational institutions hold a crucial role in crafting educational approaches utilizing cutting-edge technologies. They need to possess significant expertise in e-learning and tackle the obstacles associated with delivering education and utilizing Information and communication technologies within higher education. To effectively navigate these challenges and adaptations, professors need to equip themselves with new educational techniques through training and readiness to adeptly incorporate emerging technologies into their teaching practices, thus enhancing the educational journey for students. By identifying, understanding, and ranking professors' requirements and preferences, effective and diverse educational initiatives can be tailored to meet their needs. Objectives: This research aimed to recognize the educational needs of medical science professors in the field of e-learning from the experts' point of view and prioritize these needs utilizing the analytic hierarchy process (AHP). Methods: This practical study was conducted in 2022 using a process-oriented approach and AHP. The main stages included the creation of a hierarchical structure, comparative judgment, and determining priorities. In the first step, 13 criteria were identified, which were derived from scientific articles and previous research. In the second step, the pairwise comparison matrix was used for comparative judgment, and the weight of each criterion was calculated. The third step involved determining priorities based on the weight of each criterion and the inconsistency ratio. The participants of this study included professors of basic and clinical sciences from different faculties. Results: The results of this study demonstrated that from the point of view of experts and participants, among the 13 criteria, the skills of virtual teaching (with weights of 0.146 and 0.148), electronic content production (with weights of 0.093 and 0.092), and holding online training courses (with the weights of 0.092 and 0.100) formed the three main needs of medical science professors in the field of e-learning and had the highest degree of importance and necessity compared to other criteria. Conclusions: Identifying the educational needs of medical science professors for organizing and designing necessary programs to enhance knowledge, skills, and empowerment will lead to improving the quality of e-learning, and eventually, reducing professors’ concerns in this area.

Emergency Capability Evaluation of Port-Adjacent Oil Storage and Transportation Bases: An Improved Analytic Hierarchy Process Approach

The large-scale storage and stable supply of oil products are essential for national energy security and economic development. As the economy expands and energy demands rise, centralized storage and supply systems become increasingly vital for ensuring the efficiency and reliability of oil product distribution. However, large oil storage depots present substantial safety risks. In the event of fires, explosions, or other accidents, emergency response efforts face stringent demands and challenges. To enhance the emergency response capabilities of oil storage and transportation bases (OSTBs), this paper proposes an innovative approach that integrates the improved analytic hierarchy process (IAHP) with the Entropy Weight Method (EMW) to determine the combined weights of various indices. This approach reduces the subjective bias associated with the traditional analytic hierarchy process (AHP). The emergency response capabilities of OSTBs are subsequently evaluated through fuzzy comprehensive analysis. An empirical study conducted on an OSTB in the Zhoushan archipelago quantitatively assesses its emergency preparedness. The results show that the base excels in pre-incident prevention, demonstrates robust preparedness and response capabilities, and exhibits moderate recovery abilities after incidents. These findings provide a theoretical foundation for reducing the likelihood of accidents, enhancing emergency response efficiency, and mitigating the severity of consequences. Practical recommendations are also offered based on the results.

Multi-hazard modeling of erosion and landslide susceptibility at the national scale in the example of North Macedonia

Abstract Due to favorable natural conditions and human impact, the territory of North Macedonia is very susceptible to natural hazards. Steep hillslopes combined with soft rocks (schists on the mountains; sands and sandstones in depressions), erodible soils, semiarid continental climate, and sparse vegetation cover give a high potential for soil erosion and landslides. For this reason, this study presents a multi-hazard approach to geohazard modeling on the national extent in the example of North Macedonia. Utilizing Geographic Information Systems, relevant data about the entire research area were employed to analyze and assess soil erosion and susceptibility to landslides and identify areas prone to both hazards. Using the Gavrilović Erosion Potential Method (EPM), an average value of 0.36 was obtained for the erosion coefficient Z, indicating low to moderate susceptibility to erosion. However, a significant area of the country (9.6%) is susceptible to high and excess erosion rates. For the landslide susceptibility assessment (LSA), the Analytical hierarchy process approach is combined with the statistical method (frequency ratio), showing that 29.3% of the territory belongs to the zone of high and very high landslide susceptibility. Then, the accuracy assessment is performed for both procedures (EPM and LSA), showing acceptable reliability. By overlapping both models, a multi-hazard map is prepared, indicating that 22.3% of North Macedonia territory is highly susceptible to erosion and landslides. The primary objective of multi-hazard modeling is to identify and delineate hazardous areas, thereby aiding in activities to reduce the hazards and mitigate future damage. This becomes particularly significant when considering the impact of climate change, which is associated with increased landslide and erosion susceptibility. The approach based on a national level presented in this work can provide valuable information for regional planning and decision-making processes.

Optimising the feeding system for improving pellet distribution levels in gas-based shaft furnace based on the improved analytic hierarchy process

To improve the gas flow distribution inside the gas-based shaft furnace and ensure the chemical reaction, the discrete element method was used to calculate the effects of revolving chute inclination, particle size mass distribution, particle size distribution width, and hopper angle on the pellet distribution indicators (particle segregation, porosity, gas permeability and feeding time). An improved analytic hierarchy process was presented to fully analyse the nine schemes set up as part of the research. The findings demonstrated that the positive segregation of small particles at the furnace's centre and wall occurred with several feeding systems. The largest influences on porosity were differences in particle size mass distribution and particle size distribution width, and an increase in the proportion of small particles resulted in a significant decrease in porosity. The increase of the mass ratio of large particles made the highest permeability, but also caused uneven distribution of the furnace charge along the radial direction. The simulation results and the ranking of benefits and drawbacks produced by the improved analytic hierarchy process approach agree, demonstrating the applicability of the method to optimise the feeding system as well as its value in identifying the major influences on the feeding system.

Optimizing marine vehicles industry: a hybrid analytical hierarchy process and additive ratio assessment approach for evaluating and selecting IoT-based marine vehicles

Rapid developments in the Internet of Things (IoT) have opened the door for game-changing applications in numerous sectors, especially the vehicle industry. There is a rising demand for efficient assessment and decision-making methodologies to pinpoint the most promising choices for the vehicle sector with the introduction of IoT-based maritime vehicles. To overcome this issue, the integrated multi-criteria decision-making analysis (MCDA) paradigm proposed in this research combines the additive ratio assessment (ARAS) and analytic hierarchy process (AHP) approaches to evaluate and choose IoT-based maritime vehicles based on their performance- and authenticity-related criteria in the vehicle sector. The selection issue is hierarchically organized, and the assessment criteria are prioritized using the AHP approach. There are seven performance and authentication related criteria are selected that might aid in the selection procedure. Using the AHP, we are assigned these criteria proportionate weights that reflect their respective significance and interrelationships. AHP, however, falls short of offering a thorough analysis of the alternatives that exist. To overcome these restrictions, this research presents the integration of AHP with the ARAS approach for the ranking of alternatives according to how well they perform against the set criteria. By using the ARAS technique, it is possible to get over the restrictions of AHP and achieve a more thorough assessment of maritime IoT-based vehicles. The efficiency of the framework is proven using empirical data and professional judgment. The findings show that the hybrid method successfully encapsulates the intricate relationships between the factors being evaluated and objectively appraises the potential of IoT-based maritime vehicles for the automotive sector. This study extends to the area by providing an organized and thorough method for assessing and choosing IoT-based maritime vehicles. Considering several factors and their mutual dependence, the hybrid AHP and ARAS technique gives decision-makers a powerful tool for evaluating the potential of IoT-based maritime vehicles in the automotive sector. Smart decisions on the deployment of IoT-based marine vehicles and maximizing the potential they present may be made by beneficiaries in the automotive sector using the study’s results.

Multi-Criteria Analysis in Circular Economy Principles: Using AHP Model for Risk Assessment in Sustainable Whisky Production

As the whisky industry applies circular economy principles to maximize resource utilization and minimize environmental impact, companies become exposed to several risks, which require complex assessments to ensure reliable outcomes. This study provides an organized framework to identify, prioritize, and rank various risk factors commonly observed in the whisky industry through the development of an analytical hierarchy process (AHP) multi-criteria analysis model. Experts from 18 small European distilleries identified five main risk criteria and nineteen sub-criteria from brainstorming workplace observations and categorized them as: environmental (5), operational (4), technological innovation (3), food safety (3), and economical (4) risks. The analytical hierarchy process (AHP) approach was used to determine the weights and ranks of the main criteria and sub-criteria based on the survey responses received from experts from each distillery. The final judgements are consistent, as indicated by consistency values (CR) of less than 0.1 for all risk criteria. Unlike traditional risk assessment methods, the AHP model effectively integrates qualitative and quantitative data, aiding strategic decision making in the whisky industry by breaking down complex problems into manageable sub-problems. Future research directions may expand the criteria and explore additional sustainable practices.

Exploring a GIS-based analytic hierarchy process for spatial flood risk assessment in Egypt: a case study of the Damietta branch

Floods are the most common and costly disasters worldwide, while spatial flood risk assessment is still challenging due to fewer observations and method limitations. In this study, the flood risk zonation in the Nile districts of the Damietta branch, Egypt, is delineated and assessed by integrating remote sensing with a geographic information system, and an analytical hierarchy process (AHP). Twelve thematic layers (elevation, slope, normalized difference vegetation index, topographic wetness index, modified normalized difference water index, topographic positioning index, stream power index, modified Fournier index, drainage density, distance to the river, sediment transport index, and lithology) are used for producing flood susceptibility zonation (FSZ) and six parameters (total population, distance to hospital, land use/land cover, population density, road density, and distance to road) are utilized for producing flood vulnerability zonation. Multicollinearity analysis is applied to identify highly correlated independent variables. Sensitivity studies have been used to assess the effectiveness of the AHP model. The results indicate that the high and very high flood risk classes cover 21.40% and 8.26% of the area, respectively. In 14.07%, 27.01%, and 29.26% of the research area, respectively, flood risk zones classified as very low, low, and moderate are found. Finally, FSZ is validated using the receiver operating characteristics curve and area under curve (AUC) analysis. A higher AUC value (0.741) in the validation findings demonstrated the validity of this AHP approach. The results of this study will help planners, hydrologists, and managers of water resources manage areas that are susceptible to flooding and reduce potential harm.

Integrated Geospatial and Analytical Hierarchy Process Approach for Assessing Sustainable Management of Groundwater Recharge Potential in Barind Tract

Groundwater depletion in Bangladesh’s Barind tract poses significant challenges for sustainable water management. This study aims to delineate groundwater recharge potential zones in this region using an integrated geospatial and Analytical Hierarchy Process (AHP) approach. The methodology combines remote-sensing data with GIS analysis, considering seven factors influencing groundwater recharge: rainfall, soil type, geology, slope, lineament density, land use/land cover, and drainage density. The AHP method was employed to assess the variability of groundwater recharge potential within the 7586 km2 study area. Thematic maps of relevant factors were processed using ArcGIS software. Results indicate that 9.23% (700.22 km2), 47.68% (3617.13 km2), 37.12% (2816.13 km2), and 5.97% (452.70 km2) of the study area exhibit poor, moderate, good, and very good recharge potential, respectively. The annual recharge volume is estimated at 2554 × 106 m3/year, constituting 22.7% of the total precipitation volume (11,227 × 106 m3/year). Analysis of individual factors revealed that geology has the highest influence (33.57%) on recharge potential, followed by land use/land cover (17.74%), soil type (17.25%), and rainfall (12.25%). The consistency ratio of the pairwise comparison matrix was 0.0904, indicating acceptable reliability of the AHP results. The spatial distribution of recharge zones shows a concentration of poor recharge potential in areas with low rainfall (1200–1400 mm/year) and high slope (6–40%). Conversely, very good recharge potential is associated with high rainfall zones (1800–2200 mm/year) and areas with favorable geology (sedimentary deposits). This study provides a quantitative framework for assessing groundwater recharge potential in the Barind tract. The resulting maps and data offer valuable insights for policymakers and water resource managers to develop targeted groundwater management strategies. These findings have significant implications for sustainable water resource management in the region, particularly in addressing challenges related to agricultural water demand and climate change adaptation.

Decision making with analytical hierarchy process approach to select feedstock type for bioethanol production: Is 3G more sustainable than others?

Feedstock selection for bioethanol production is challenging because of the multidimensional considerations of the wide range of resources. The present study applies the analytical hierarchy process (AHP) for the first time to select the most sustainable feedstock type for bioethanol production based on 28 sub-criteria categorized under four main criteria, including technical, economic, environmental, and social. The method included the use of literature surveys, brainstorming, and expert consultation. Expert opinions revealed that the most important sub-criteria within these four main criteria are fuel product quality, value-added by-product formation, impact on biodiversity, and contribution to the circular economy. Overall scores suggest that the third-generation feedstock, which is algal biomass, is economically more sustainable and environmentally friendly than the other feedstocks evaluated in the present study. Because of the environmental damage caused by chemicals used for pretreatment, the score on the environmental aspect of lignocellulosic bioethanol is slightly lower than that of algal bioethanol. The application of AHP enabled the comparison of three different generations of bioethanol production in a scientifically acceptable manner and reached a reliable decision that can be used by governments and stakeholders in establishing future renewable energy policies.

Prioritisation of Specific Wheat Sowing Technologies Based on AnalyticHierarchy Process and Farmers’ Perceptions

Selection of an appropriate wheat-sowing technology in the combine harvested paddy fields is essential for the timely sowing of wheat after harvesting paddy. The importance of parameters that affect farmers' decisions in selection of wheat sowing technology (WST) in the combine harvested paddy fields is assessed in the present work by implementing an analytical hierarchy process (AHP) technique. AHP is the most comprehensive approach for making judgements with many criteria since it supports a hierarchical structure and quantitative and qualitative features. The suitability of four most commonly used wheat sowing technologies, namely, happy seeder (T1 ), super seeder (T2 ), smart seeder (T3 ) and roto seeder (T4 ), was assessed based on the importance given to six criteria, namely, ease of use (C1 ), machine capital cost (C2 ), fuel consumption (C3 ), machine field capacity (C4 ), crop yield (C5 ), and crop germination (C6 ). Based on farmers’ perceptions and using the analytical hierarchy process approach, criteria C5 was assigned a maximum criteria priority weights of 3.21 and 3.87 for selection of T1 and T2 , respectively; while criteria C6 was assigned a maximum criteria priority weights of 3.56 and 3.63 for selection of T3 and T4 , respectively. The results showed that farmers were less concerned with machine field capacity and more focused on crop output (yield) while selecting a wheat sowing technology. Besides crop yield, crop germination and ease of use were other important factors that farmers considered highly while prioritising and selecting a wheat sowing technology for a combine harvested paddy field.

Identifying key safety investments needed for arctic shipping via a fuzzy analytic hierarchy process (FAHP) approach

ABSTRACT The retreating ice coverage and reduced (ice) thickness scientifically recorded in the wider Arctic region, during the last few decades, are transforming it into a more accessible operating environment. Vessels engaged in maritime transport activities can now navigate the already established routes for more extended periods each year. With this background, Arctic shipping routes have attracted the interest of academics and maritime stakeholders because of the potential distance reduction compared to other existing (and often viewed as) conventional routes utilizing the Suez and Panama Canals today. However, the existing Arctic shipping environment requires specific future safety investments. This paper intends to provide input towards better-informed decision-making and identification of priority investments needed to improve the level of safety related to the Northern Sea Route (NSR) and Northwest Passage (NWP). A multi-attribute decision-making methodology, the Fuzzy Analytic Hierarchy Process, is applied to rank the various proposed safety investments. The results indicate that “infrastructure and facility” should come first, followed by “personnel,” “technology,” “measure,” and “management” investments. Ice monitoring and weather forecasting, strengthening Arctic seafaring expertise, and icebreakers stand out as the top three most important future investments required in the region.

Integrating AHP and GTMA for Enhanced Multi-Criteria Decision Making in Logistics Provider Selection

The selection of logistics providers is a critical task for organizations aiming to enhance their supply chain performance and maintain a competitive edge. This paper proposes an integrated approach that combines the Analytic Hierarchy Process (AHP) and Graph-Theoretic Matrix Approach (GTMA) for effective multi-criteria decision-making (MCDM) in the selection of logistics providers. AHP is widely used for evaluating criteria and alternatives based on pairwise comparisons, while GTMA enhances decision-making by incorporating complex interdependencies among criteria. The integrated AHPGTMA approach is demonstrated through a case study involving the selection of a third-party logistics provider (3PLP). The proposed method improves the decision-making process by simplifying complex relationships among criteria while ensuring an efficient and robust selection. This integrated model presents a more comprehensive and reliable framework for logistics provider selection, overcoming limitations observed in stand-alone AHP and ANP approaches. Future research may focus on the application of fuzzy logic to further enhance decision accuracy in uncertain environments.

Evaluation of groundwater quality potential zones using AHP and WIOA models in Shopian District, Jammu and Kashmir, India: A GIS

Groundwater is an important natural resource stored in aquifers beneath the earth's surface. The hilly district of Shopian in Jammu and Kashmir serves as a study area due to its present and future groundwater needs. This study aims to assess the groundwater potential zones (GWPZ) in Shopian District using the analytical hierarchy process (AHP) and weighted index overlay analysis (WIOA). The AHP approach attempted to assign weights to specific groundwater recharge characteristics. The various thematic maps, including rainfall, land cover and usage, slope, drainage density, geomorphology, soil, and geology, were integrated using overlay analysis to create a comprehensive GWPZ map. Geographic information system (GIS) and remote sensing (RS) tools were utilized to indicate the potential groundwater existence in the studied area. Four zones were created from the GWPZ: very poor, poor, good, and very good. The analysis showed that the very poor GWPZ is around 35.12 sq km, the poor zone is roughly 166.89 sq km, the excellent zone is approximately 340 sq km, and the very good zone is approximately 66.13 sq km. The present study reveals significant perspectives for organizing and effectively restocking groundwater locations within the district. It intends to safeguard the sustainability of groundwater resources for future generations by promoting their successful development and management.

Zero Produced Water Discharge Innovation in Production Fluid Management for Sustainability and Financial Efficiency

This paper will present the sustainability initiatives of PHI Tanjung Field obtained from the evaluation of existing oil and gas production activities. Through the Plan-Do-Check Action (PDCA) approach, based on the results of life cycle assessment and focus group discussions from managers and engineers in Tanjung Field, the identification of priority problems is related to the management of production fluid generated from outside the existing production facility process. Through a fishbone diagram approach to find out the root of the problem followed by Failure Mode Effect Analysis (FMEA) including Pareto diagrams and risk map analysis to get priority risk problems in the form of production fluid processing methods. Furthermore, through the Analytic Hierarchy Process (AHP) approach, the alternative solution taken is to modify the production fluid processing with CSSR (Contain, Sediment, Separate, Recovery) innovation. The results of this CSSR innovation are no more produced water is discharged into the environment so that the Tanjung Field Manager’s policy of moving towards zero produced water discharge is achieved. With this innovation, the processing efficiency of the production fluid in 2nd year (prediction) after innovation is 97.5%, up from 66.6% in initial year before innovation. By optimizing the use of produced water, the need for clean water for the injection program can be minimized. The reduction of clean water usage from Initial year to 2nd year (prediction) is 83.1%. The efficiency ratio of this innovation is 11.10 > 1 indicates that the program generates more savings and revenue than its cost, making it a worthwhile investment. In energy reduction, the effectiveness of this innovation from Initial year to 2nd year (prediction) is reducing energy by 94.96%. In emission reduction, the reduction of CO2 emission load from Initial year to 2nd year (prediction) is 95%. This innovation contributes to the 6th Sustainable Development Goal (SDGs) “Clean Water and Sanitation,” the 7th SDGs “Clean and Affordable Energy,” the 12th SDGs “Responsible Consumption and Production,” 13th SDGs “Handling Climate Change,” and the 14th SDGs “Ocean Ecosystems.”

Exploring Water Quality Assessment through AHP and Picture Fuzzy PROMETHEE - II: An In-Depth Investigation

Effective analysis of water quality is crucial for the well-being of ecosystems and human populations, notably in rivers like Thirumanimutharu. This study advances current methodologies by integrating the picture fuzzy PROMETHEE II approach with the analytic hierarchy process (AHP), offering a robust solution to the challenges posed by data ambiguity and imprecision. Born from the fusion of PROMETHEE II with picture fuzzy sets, this innovative method adeptly represents qualitative criteria and linguistic notions inherent in water quality assessment. A practical case study, utilising real water quality data, demonstrates the superior accuracy and durability of the combined picture fuzzy PROMETHEE II and AHP approach compared to traditional methods. These results significantly contribute to our understanding of water quality assessment, providing essential insights for environmental experts and decision-makers. The approach�s efficacy is particularly highlighted in the management and conservation of water resources in the Thirumanimutharu river, emphasising the need for advanced methodologies in environmental conservation and resource management. This research underscores the importance of adopting sophisticated techniques for more informed decision-making, ultimately contributing to the water resources and the preservation of ecological balance in the Thirumanimutharu river and similar water bodies.