Analytic Hierarchy Process Model Research Articles

Aviation Operators’ Total Loads Analysis by Multi-Criteria Decision-Making

The aviation operator's role and duties undergo a dramatic change from direct engagement to information management and surveillance in today's advanced aviation environment. In this modern and highly automated working environment, operators must handle various information, data, and transmission during operations, particularly while making decisions in specific situations. The total load system of operators (information, communication, mental, task, and workload) has been fundamentally reshaped in response to these dynamic changes. The highly automated system is linked to unbalanced operator loads, unanticipated losses in situation awareness, inappropriate decision-making quality, and higher stress levels. This research employs the Analytical Hierarchy Process (AHP) as a foundational framework, integrating the Fuzzy Analytical Hierarchy Process (FAHP) on the AHP model to address uncertainties and applying the Technique for Order of Preference by Similarity to the Ideal Solution (TOPSIS) for ranking the aviation operators' total loads. online Survey distributed among 63 experts across four aviation operator groups: less experienced pilots, expert pilots, less experienced Air Traffic Controllers (ATCOs), and experienced ATCOs. serves to evaluate the pivotal characteristics of the operators' total loads model. The results highlighted the communication load's effect on the aviation operators specifically the level of the language as well the workload specifically both practicing referring to the experience and skills.

IDENTIFICATION AND EVALUATION OF DISTRIBUTION RISK IN FOOD SUPPLY CHAIN USING AHP METHOD

The study aims to present a structured approach for identifying and assessing distribution risk within the food supply chain by employing the Analytic Hierarchy Process (AHP) method. Through a comprehensive literature review, various risk factors impacting the distribution network of food supply chains are identified, facilitating the development of a hierarchical framework. This framework integrates multiple criteria and sub-criteria to enable a systematic evaluation of distribution risks, considering aspects such as transportation delays, inventory management, quality control, and supplier reliability. The AHP method is then applied to assign relative weights to these criteria, allowing for a quantitative analysis of risk levels and prioritization of mitigation strategies. The findings reveal that the AHP model offers a valuable decision-making tool for stakeholders in the food industry to proactively manage and mitigate distribution risks, thereby enhancing operational efficiency and ensuring food safety and security. Keywords: identification, evaluation, distribution risk, food supply chain, Analytic Hierarchy Process (AHP), criteria, mitigation strategies, operational efficiency, food safety.

Study on decision-making for orthodontic treatment plans based on analytic hierarchy process

BackgroundOrthodontics is a common treatment for malocclusion and is essential for improving the oral health and aesthetics of patients. Currently, patients often rely on the clinical expertise and professional knowledge of doctors to select orthodontic programs. However, they lack their own objective and systematic evaluation methods to quantitatively compare different programs. Therefore, there is a need for a more comprehensive and quantitative approach to selecting orthodontic treatment plans, aiming to enhance their scientific validity and effectiveness.MethodsIn this study, a combination of the analytic hierarchy process (AHP) and semantic analysis was used to evaluate and compare different orthodontic treatment options. An AHP model and evaluation matrix were established through thorough research and semantic analysis of patient requirements. This model considered various treatment factors. Expert panels were invited to rate these factors using a 1–9 scale. The optimal solution was determined by ranking and comparing different orthodontic treatment plans using the geometric mean method to calculate the weights of each criterion.ResultsThe research indicates a higher preference for invisible correction compared to other orthodontic solutions, with a weight score that is 0.3923 higher. Factors such as comfort and difficulty of cleaning have been given significant attention.ConclusionThe Analytic Hierarchy Process (AHP) method can be utilized to effectively develop orthodontic treatment plans, making the treatment process more objective, scientific, and personalized. The design of this study offers strong decision support for orthodontic treatment, potentially improving orthodontic treatment outcomes in clinical practice and ultimately enhancing oral health and patients’ quality of life.

Selection of waste receiving companies for sustainable industrial symbiosis network: an application a case in Ankara for foundry industry waste

AbstractIn the past twenty years, besides the technological and innovative efforts for production processes, there have been activities for the recovery and quality improvement of waste based on the development of sustainable solutions. These activities bring us closer to zero waste by protecting natural resources and reducing the environmental impact of production facilities. One of the essential approaches in this process is the industrial symbiosis (IS) approach. Efforts to implement the industrial symbiosis approach in an industrial park constitute the motivation of the study. The study aims to identify alternative enterprises that can evaluate the wastes generated in the main production process of the foundry industry with industrial symbiosis and rank them to establish a symbiotic relationship. First, the Pythagorean Fuzzy Analytical Hierarchy Process (PF-AHP) model has been developed to evaluate organizational factors, waste-specific factors, and economic and environmental sustainability criteria for establishing an IS network among alternative businesses. Then, alternative businesses were ranked to establish a symbiosis network with the PF-TOPSIS method. The proposed method contributes to the solution of a real-life problem that may arise when there are multiple alternatives to cooperate in the field of industrial symbiosis. By contributing this framework to the literature, the robustness of the results has been demonstrated through sensitivity analysis and comparative analysis. According to the results obtained, it was seen that the importance levels of economic factors came to the fore. Furthermore, among the alternatives, enterprises with high waste exchange potential, such as cement, took first place in the ranking.

GIS-Based Analytical Hierarchy Process Modelling and Mapping of Erosion Vulnerability in the Coastal Areas of Rivers State, Nigeria

The problem of coastal erosion in rivers State Nigeria is a significant issue that has far-reaching consequences for the environment and local communities. Despite the efforts of previous research there remains a lack of comprehensive understanding of the factors contributing to erosion vulnerability and their relative importance, hindering effective decision-making and management practices aimed at mitigating the effects of coastal erosion in Rivers State. Therefore, this study aimed at a GIS-based analytical hierarchy process modeling and mapping of coastal erosion vulnerability in Rivers State, Nigeria. The objectives are to establish and classify the geophysical factors according to the levels of coastal erosion risk, calculate the reliability index of the classified geophysical factors, determine the coastal vulnerable areas across Rivers State using analytical hierarchical process and to produce a coastal vulnerability index map defining the extent of erosion vulnerability in Rivers State. The methodology comprises of the acquisition of primary and secondary data, image pre-processing, image classification, DEM processing, classification and standardization of factors, development of pairwise comparism, and weighted linear combination analysis. The study revealed three distinct coastal erosion vulnerability zones: high, moderate, and low vulnerability. The high vulnerability zone encompassed a total expanse of 545.29 square kilometers, constituting 6.38% of the study area. In contrast, the moderate and low vulnerability zones covered 1941.33 square kilometers and 6052.51 square kilometers, respectively, making up 22.73% and 70.89% of the total area. Bonny (139.28 sq km) was ranked as the most vulnerable due to its role as an oil and gas hub. Degema (111.28 sq km) ranked second and requires urgent erosion control. Okrika and Andoni (71.73 sq km and 62.20 sq km) were third and fourth respectively. It is recommended that an advocate for the systematic approach to coastal vulnerability zoning be introduced in the study. The categorization of areas into high, moderate, and low vulnerability zones provides a standardized framework for assessing coastal regions' susceptibility to erosion. This approach can be applied to other regions to facilitate consistent vulnerability assessments.

Flood susceptibility mapping contributes to disaster risk reduction: A case study in Sindh, Pakistan

Floods are a widespread and damaging natural phenomenon that causes harm to human lives, resources, property and has agricultural, eco-environmental, and economic impacts. Therefore, it is crucial to perform flood susceptibility mapping (FSM) to identify susceptible zones to mitigate and reduce damage. This study assessed the damage caused by the 2022 flash flood in Sindh and identified flood-susceptible zones based on the frequency ratio (FR) and analytical hierarchy process (AHP) models. Flood inventory maps were generated, containing 150 flood sampling points, which were manually selected from Landsat imagery. The flood sampling points were split into 70 % for training and 30 % for validating the results. Furthermore, fourteen flood conditioning factors were considered in the analysis for developing FSM. The final FSM is categorized into five zones, representing levels from very low to very high. The results identified that the areas under very high flood-susceptible zones in Ghotki (FR 4.42 % and AHP 5.66 %), Dadu (FR 21.40 % and AHP 21.29 %), and Sanghar (FR 6.81 % and AHP 6.78 %). Ultimately, FSM accuracy was evaluated using the receiver operating characteristics and area under the curve method, resulting in Ghotki (FR 82 %, AHP 83 %), Dadu (FR 91 %, AHP 90 %), and Sanghar (FR 96 %, AHP 95 %). This study enhances the scientific understanding of flash flood impacts across diverse regions and emphasizes the importance of accurate FSM for informed decision-making. The findings provide important informations and are supportive for policymakers, agricultural planners, and stakeholders engaged in flood risk management to mitigate the adverse consequences of flash floods.

Critical Watershed Prioritization through Multi-Criteria Decision-Making Techniques and Geographical Information System Integration for Watershed Management

The Precambrian hard rock topography of the Manbhum-Singhbhum plateau, which is well known for its semi-arid climates prone to drought, is often seen in Purulia district in West Bengal, India. Despite the district’s middling groundwater capacity, 17 out of 20 blocks have exorbitant fluoride pollution in the groundwater that negatively impacts the health of local residents. Approximately 13% of the whole area suffers from severe erosion. It is evident that the river Kangsabati and its tributaries are not well fed by rainwater and thereby there is always a dearth of ground water. The aim of this study was to identify and prioritize integral watersheds in the Purulia area using Multi-Criteria Decision Making (MCDM) and Geographic Information Systems (GIS). The evaluation was carried out in the Bandu sub-watershed, which contains five micro watersheds: 2A2B5m, 2A2B5k, 2A2B5h, 2A2B5b, and 2A2B5j. The analysis considered five major factors: lithological properties, land use and land cover, soil erosion, groundwater recharge, and hydrogeomorphology. The weights of these criteria were determined by the Analytical Hierarchy Process (AHP) model, which was then prioritized using the Techniques for Order of Preference by Similarity to the Ideal Solution (TOPSIS) technique. This study emphasized an integrated approach to assess watershed hazards and to establish rational conservation goals. The Central Ground Water Board (CGWB) of India report was referred during data analysis. As a result of this study, the 2A2B5k watershed emerged as the most critical due to its susceptibility across the analyzed parameters. This thorough plan demonstrated the usefulness of identifying watershed threads and prioritizing conservation efforts.

A Novel Modeling Approach to Quantify the Flood Resilience of Cities

In recent years, large-scale flood events have occurred more frequently, and the concept of resilience has become a prevalent approach to managing flood risk in many regions. This has led to an increased interest in how to effectively measure a city’s flood resilience levels. This study proposes a novel modeling approach to quantify urban flood resilience by developing D-number theory and analytical hierarchy process (AHP) models, which are applied to three cities in China using the VIse Kriterijumski Optimizacioni Racun (VIKOR) method. The findings reveal that Hefei City has the most effective level of flood resilience, Hangzhou City was ranked second, while Zhengzhou City has the least effective level of flood resilience. This study provides a new scientific basis on how to quantify flood resilience at the city scale and provides a useful reference for these three specific cities. The methods and approaches developed in this study have the potential to be applied to other cities and in the related aspects of disaster prevention, recovery, and reconstruction.

Quantitative Evaluation of Pre-Drilling Safety by Combining Analytic Hierarchy Process with Alternating Condition Expectation

In order to avoid potential personnel and financial losses, the evaluation of pre-drilling safety is of great importance in oil and gas exploration and development. This paper presents a method of evaluating pre-drilling safety through combining the Analytic Hierarchy Process (AHP) with the Alternating Condition Expectation (ACE) method. An indicator system with a 9-3-1 structure was established, incorporating various unrestricted variables to describe the technical factor. Additionally, nine membership functions and weights were determined in order to build the AHP model by connecting the independent variables in the basic layer to dependent variables in the middle layer. Four transformed functions were also formulated to construct the ACE model by linking the middle variables to the pre-drilling safety value in the final layer. A total of 28 sets of on-site drilling data from three oilfields were collected for the establishment and verification of the AHP-ACE model. Average absolute error (AAE) and average absolute relative error (AARE) of the model to predict the training data are 0.03 and 4.29%, respectively, whereas the AAE and AARE for verification samples are 0.03 and 4.51%, respectively. The sensitivity ranking of the three potential variables is as follows: human factor exhibits the highest degree of sensitivity, followed by natural factor and technical factor, in descending order. The AHP-ACE model for pre-drilling safety assessment faces limitations in universal applicability and scope, particularly in real-time drilling activities. However, its potential for improvement lies in integrating insights from past operations and expanding the dataset to enhance accuracy and broaden safety assessment coverage. This method is not limited by blocks, which is of great significance to ensure drilling safety.

Analytical Hierarchy Process for Risk Management in the Stabilized Flight Approach - Expert Judgment

Destabilised approaches have been the primary cause of fatal accidents during the approach and landing phase, as stated in  (Airbus, 2023). The stabilised approach concept is of great importance for the safe operation of an airline during the approach and landing phases (Acarbay & Kiyak, 2020). The elements highlighted in the approach phases are the runway's dry or contaminated condition and length. In the crew, we analyse their competence, recurrence, and fatigue. Another variable is the type of approach, whether it is precision, non-precision or visual. The external conditions of the aerodrome include obstacles, wind, and wildlife—the type of aircraft, whether light, medium or heavy.  Due to the large amount of qualitative information derived from the pilots' experience about risk management in the approach and landing phases, this paper proposes an Analytic Hierarchy Process model (AHP) for threat characterisation and risk analysis to achieve a stabilised approach. The results show that AHP proposed model establishes a new methodology for identifying potential in-flight risks to air operations based on expert criteria, improving the decisions to land at an alternate airport based on qualitative information from expert pilots in the risk management field.

Optimal design of renewable energy certificate multipliers using an LCOE-Integrated AHP model: A case study of South Korea

Finding and developing a reasonable design for renewable energy certificate (REC) systems is essential for societies to realize their policy goal of establishing optimal renewable energy portfolios and to minimize the controversy that surrounds REC multipliers. However, it is challenging to assess the adequacy of REC multipliers on a logical and quantitative basis. To fill this gap, we develop a levelized cost of electricity (LCOE)-integrated analytic hierarchy process (AHP) model as a quantitative method for identifying and analyzing appropriate REC multipliers. Our model prioritizes cost-effectiveness and social concerns as the two core factors of consideration in determining REC multipliers, and then quantitatively analyzes each using the LCOE and AHP methods. We also present results of analysis applying the proposed model for the Korean REC market. Our findings reflect the renewable energy market conditions and policy objectives in Korea, while revealing related needs such as the long-term policy objective of ensuring stability of power supply. The Korean government recently revised the REC multipliers adopting the results from our model, and in consideration of overall government policy, the diverse interests of stakeholders, and the need to ensure institutional consistency and market stability.

Research on training evaluation of new engineering talents in China local colleges under the background of regional economy

Under the regional economic background, local colleges have a crucial role in evaluating and researching the training of new engineering talents. With the continuous development of technology and the improvement of economic strength, training new engineering talents has become an important mission for local higher education institutions. This study aims to explore the evaluation methods and strategies for training new engineering talents in local colleges within the regional economic context. It proposes an evaluation system that selects and assesses indicators from five aspects: basic conditions, teaching process, practical proficiency, cultivation level of innovation ability, and cultivation effect. The results were obtained through a combination of the analytic hierarchy process and fuzzy comprehensive evaluation model and take two majors of A college as an example to evaluate and analyze the training effect of new engineering talents. Furthermore, this article presents valuable recommendations and countermeasures to enhance the training of new engineering talents in local colleges.

Mapping coastal groundwater potential zones using remote sensing based AHP model in Al Qunfudhah region along Red Sea, Saudi Arabia

Due to the increases in agriculture and industry sector as well as high population, lack of water is becoming a major problem in the Middle East especially in arid regions. Saudi Arabia needs more groundwater research and explorations because of its higher water use and no source of freshwater. Assessing groundwater zonation in semi-arid locations is essential due to the significant degree of variation in groundwater depth, aquifer features, topographical characteristics, and insufficient precipitation. Mapping prospective groundwater zones in Al Qunfudhah region of southwestern Saudi Arabia has utilized the capability of the multi-criteria decision approaches (MCDA), and the Geographic information system (GIS). We have used the analytical hierarchy process (AHP) as one of the MCDA that is applied to achieve the objective of the current study by integrating twelve controlling factors. These factors are represented by the thematic layers; slope, precipitation, soil type, land use/cover (LULC), drainage density (DD), normalized difference vegetation index (NDVI), curvature, topographic position index (TPI), Terrain Ruggedness Index (TRI), drainage density (DD), and Lineament Density (LD). These thematic layers are combined with GIS to delineate the zones of groundwater potentialities. All factors were classified and weighted according to their importance and its effect on groundwater zones. Their normalized weights were evaluated using a pairwise comparison matrix. The present study shows that the groundwater potential zones (GWPZs) map is represented by five groups ranging between a very high zone with an area of 23781.06 Km2 that represents 4.04 % of the studied area, and a very poor GWPZ with an area of 182944.4 Km2 that represents 31.09 % of the studied area. The AHP model suggests that lineament density, slope, and drainage density are more important for determining the groundwater potentiality than other physiographic factors. The study's findings will be helpful in developing practical strategies for the region's groundwater supply. This analysis shows how the methodology may be used to study a broad coastal groundwater basin. The current study will give the decision makers to select suitable sites with a high groundwater potential.

Analyzing Flood Damage and Mapping Flood Hazard Zones Using AHP Model: A Case Study of Pol-e-Alam, Logar Province, Afghanistan

This research aims to evaluate the impact of the most recent floods that occurred on August 20, 2022, in Logar province in southern Afghanistan. For this purpose, changes in land use and land cover (LULC) of the study area were created from the Sentinel-2 image with a spatial resolution of 10 meters. To achieve this, the study utilized Sentinel-2 images to analyze LULC changes before and after the flood event and employed a support vector machine for supervised classification. The study also applied the analytical hierarchy process (AHP) to evaluate the future risks of flooding in the study area, focusing on factors related to hydrological phenomena. Overall, the study demonstrates the effectiveness of geospatial technologies and remote sensing in assessing the impacts of floods and creating flood risk maps. This can significantly reduce the consequences of flooding and inform decision-making for disaster management and mitigation.

Integrated GIS and analytic hierarchy process for flood risk assessment in the Dades Wadi watershed (Central High Atlas, Morocco)

Flood risk assessment is crucial for delineating flood hazard zones and formulating effective mitigation strategies. Employing a multi-criteria decision support system, this study focused on assessing a Flood Risk Index (FHI) at the Dades Wadi watershed scale. Seven main flood-causing criteria were broadly selected, namely flow accumulation, distance from hydrographic network, drainage network density, land use, slope, rainfall, and permeability. The relative importance of each criterion prioritized as per their contribution toward flood risk, which were employed a blend of the Analytical Hierarchy Process (AHP) and Geographic Information System (GIS)/Remote Sensing (RS) techniques. The significance of each criterion was determined based on their contribution to flood hazard, and their relative importance was established through an AHP pair-wise comparison matrix. The efficacy of the AHP model was performed with a consistency ratio of 0.08, which indicated that each flood criterion weight is confirmed. Among the flood-causing criteria, the hydrologic flow accumulation factor was identified as the most influential (weight: 3.11), while permeability exhibited the least prominence (weight: 0.58). Approximately 40.36% of the total area, equivalent to around 1319, 89 km2, was concentrated within very high flood-risk zones situated near rivers. In contrast, an area of approximately 399,943 km2 (56.33%) exhibited a low to very low flood risk zone. The validation of the FHI map encompassed the application of the Receiver Operating Characteristic Curve (ROC) technique, revealing an Area Under the Curve (AUC) of 85%.

Geospatial modeling for groundwater potential zoning using a multi-parameter analytical hierarchy process supported by geophysical data

Groundwater plays a crucial role in Hungary sustaining ecosystems and meeting the growing demand for freshwater to fulfill domestic and agricultural needs. This study employs the analytical hierarchy process (AHP) methodology to delineate groundwater potential zones in the Debrecen area, Hungary. To ensure the robustness and reliability of the potential zoning, geophysical data are utilized for validation purposes. In the AHP modeling seven groundwater conditioning factors are integrated, including geology, topography, slope, land use/land cover, precipitation, drainage density, and lineament density. The integration of the normalized weights for each factor identified three groundwater potential zones (GWPZs) assigned as moderate, high, and very high potential. The result of the AHP model is further validated with geophysical data of gravity and wireline logging. Gravity data is subjected to spectral analysis and forward modeling to map the lineaments and detect the thickness of the sedimentary sequences. The forward modeling indicated that the thickness of these sequences varies between 1.25 and 2.7 km, with a deep local basin delimited by normal faults situated in the eastern part of the study area. Additionally, the analysis of the well-logging data using the Csókás method provided a continuous estimation of petrophysical and hydrogeological parameters along the main hydrostratigraphical units. Accordingly, a high and uniform distribution of hydraulic conductivity is observed in the eastern part of the study area due to the presence of coarse-grained incised valley deposits. The results of geophysical modeling showed a close agreement with that of AHP models. This interdisciplinary approach advanced the mapping of potential groundwater zones and provided valuable insights into the hydrogeological characteristics of the groundwater aquifers in the Debrecen area.

Research on Vehicle Frame Optimization Methods Based on the Combination of Size Optimization and Topology Optimization

The efficient development of electric vehicles is essential to drive society towards sustainable development. Designing a lightweight frame is a key strategy to improve the economy and environment, increase energy efficiency, and reduce carbon emissions. Taking an automatic loading and unloading mixer truck as the research object, a force analysis of its frame was conducted under six typical working conditions. A size optimization method based on a hybrid model of the Kriging model and the analytic hierarchy process (AHP) is proposed. An approximate model of the mass and maximum stress of the frame was established using the Kriging model, and the Kriging model was optimized by using the multi-objective genetic optimization algorithm and the AHP method. Meanwhile, topology optimization was introduced to improve the structural performance of the frame and reduce its weight. The optimization results show that the overall weight of the frame is reduced by 11.96% compared to the pre-optimization period, though it still meets the material performance specifications. By comparing the iterative curves of the single Kriging model with those of the AHP model, it can be seen that the initial optimization efficiency of the hybrid model is about twice as much as that of the AHP model, and the final optimization result is improved by about 3.6% compared with the Kriging model. This validates the hybrid model as an effective tool for the multi-objective optimization of electric vehicle frames, providing more efficient and accurate optimization results for frame design.

Flood Susceptibility Assessment of Chandpur Sadar Upazila using Analytical Hierarchy Process and Frequency Ratio Model

Flood susceptibility is a critical aspect of natural hazard assessment and disaster risk reduction. The objective of this study find out flood risk zone of chandpur sadar upazila using the Flood frequency ratio (FFR) and Analytical hierarchy process (AHP). The article explore the complex idea of flood susceptibility, focusing on analytical techniques used. The integration of twelve spatial data layers, such as Sediment Transport Index (STI), elevation, Topographic Wetness Index (TWI), slope, aspect, Land Use Land Cover (LULC), soil type, rainfall patterns, Normalize Difference Vegetation Index (NDVI), drainage density and distance from the river, is required for the assessment of flood vulnerability. A flood inventory map was buildup and using these methods, two vulnerability map was created, it was discovered that 60% & 48% of Chandpur's territory is categorized by very high to high risk zone. Flood has dangerous effect on livelihood. I was hoped that it will be a helpful study for researcher and people of this upazila will be benefited.

Adaptation Strategies of the Colombian Hotel Industry During the Pandemic

Different aspects related to business dynamics motivate the design and execution of strategies. In the case of the Colombian hospitality industry, the recent price regulation, the emergence of disruptive technologies, and events affecting public health demonstrate the need to outline appropriate tactics that lead to an adequate contextualized implementation. This study proposes an Analytic Hierarchy Process (AHP) model to evaluate the set of tactics and strategies most applicable to these current situation alternatives faced by hoteliers in the city of Medellin. The results of the evaluation indicate that intensive, generic business and defensive strategies are the most preferred. In addition, as expected, the results suggest that the pandemic has the greatest weight and should therefore be selected by hotel companies as the priority alternative on which to focus their strategies.

Identification and evaluation of the evolution stage of the agricultural machinery industry cluster in Shandong Province

AbstractAgricultural machinery industry clusters have great potential to solve key technological problems in China, and it is crucial to accurately identify the stage of cluster evolution. Based on the location entropy method, this paper finds that the location quotient coefficient is greater than 1.2 and the average annual growth rate is 1.11%, which indicates that the agricultural machinery industry in Shandong Province has a high degree of agglomeration, but the agglomeration speed is slow. Using the Groundings agglomeration—Economic network—Social network—Service system model, it is found that the agricultural machinery industry cluster in Shandong province is in the growth stage, in which the service system has the most significant influence on its development level. The weights of service system, social network, economic network, and basic resource aggregation derived from the Analytic Hierarchy Process model are 0.410, 0.321, 0.151, and 0.118, respectively, where agglomeration degree of the agricultural machinery industry, raw material production of agricultural machinery enterprises, exchange of tacit knowledge and intermediary service level are the four indicators with the greatest weights in the influences on sustainable development of the agricultural machinery industry. Because of the strong fuzzy nature between the indicators, this paper applies the Fuzzy Comprehensive Evaluation method to quantify the stage of evolution of Shandong Province's agricultural machinery industry cluster.