An intelligent approach to machine tool selection through fuzzy analytic network process

Machine tool selection plays important role regarding process of decision making in several companies involved in manufacturing. Machines which are not properly selected, may affect negatively the overall production system performance. The machine tool selection problem within available possibilities proved to be a critical issue among companies in competitive environment from long past. As several alternatives and criteria of selection are available, this problem is converted into MCDM (multiple criteria decision making) problem for machine tool selection. Hence maximum companies adopted several methods for successfully solve this time consuming as well as typical problem. In this paper, mostly used two MCDM methods are introduced viz-modified fuzzy TOPSIS & AHP (Analytical her Process) for presenting an analysis of performance for the problem of machine tool selection. As the global competition in the market is very high, companies are bound for focusing upon high productivity with minimum cost with the use of correct machine tool selection. Appropriate machine tool selection enables saving of labour, quality of product improvement & rate of production increment at the same time overall productivity increment. Machine tool evaluation & selection is a complicated problem for decision making as it involves several criteria with conflicts. In this work, we presented the logical method for evaluating computer numerical controlled (CNC) machine from the point of view of cost & system specifications with the use of method of fuzzy TOPSIS. We get highly promising results when selection problem with CNC machine was solved with respect to the past research.

A hybrid approach for fuzzy multi-attribute decision making in machine tool selection with consideration of the interactions of attributes

In this study, an intelligent approach is presented to help any simulation practitioner to evaluate simulation software alternatives and determine the best satisfying one based on his/her needs. On the other hand, this evaluation process is a typical multiple criteria decision making (MCDM) problem in the presence of evaluation criteria and a set of possible alternatives, and there are many methods in the literature, which have been used to successfully carry out this difficult and time-consuming process. In this paper, one of these methods, the analytic network process (ANP) method integrated with alpha-cut fuzzy logic is used because it can accommodate the variety of interactions, dependencies and feedback between higher and lower level elements, rather than analytic hierarchy process (AHP). In addition, an alpha-cut fuzzy extension of ANP uses uncertain human preferences as input information in the decision-making process. Instead of using the classical eigenvector prioritisation method in AHP, only employed in the prioritisation stage of ANP, an alpha-cut fuzzy logic method providing more accuracy on judgements is applied. The resulting alpha-cut fuzzy ANP enhances the potential of the conventional ANP for dealing with imprecise and uncertain human comparison judgements.

The uncertainty of data and weighting of variables are prima facie problems to model the green supply chain (GrSC) performance. The paper modelled GrSC performance of plastic film by fuzzy logic analysis-fuzzy analytic network process approach to overcome these hurdles. Fuzzy logic analysis is used to derive fuzzy score of variables using MATLAB. Further, fuzzy analytic network process is used to calculate global weights of variables. Thus, green score of supply chain performance for plastic film is computed as 28.83. Green supply chain performance analysis of plastic films is done for present status and computed as 48.62. The solutions developed by author's viz. adoption of best practices for blown film extrusion process and 'design for environment' tool for segregating MSW at source are analysed. It is found that, if the tools adopted simultaneously, the GrSC performance score resulted in 27.38. This is well below green score making the plastic film industry environment friendly. Approach is suitable for modelling small scale systems GrSC performance.

Analytic Network Process and Fuzzy Analytic Network Process

Currently, the analytic network process (ANP) method is widely employed to consider the multiple criteria analysis problems with dependence and feedback effects. However, in order to extend the ANP to resolve the problem of uncertainty or human subjective judgment, the concepts of fuzzy numbers should be incorporated into the ANP to represent the subjective uncertain pairwise judgments. In this paper, therefore, we propose a novel fuzzy analytic network process (FANP) model by solving a mathematical programming problem. Unlike other FANPs, the proposed method does not require the reciprocity assumption of the weight ratios between criteria, and it can derive local and global weights simultaneously in a single model. Two numerical examples of international investment problems are used to demonstrate the proposed method.

A fuzzy analytic network process (ANP) model for measurement of the sectoral competititon level (SCL)

Shopping center plays an important role in distribution system and marketing. These canters provide an appropriate atmosphere for customers; so that, the customers achieve the best service within a short time. However, there is an intense competition among shopping centers to attract more customers for increasing the profit. Therefore, a powerful model assists authorities in identifying the critical competitive aspects and directing their efforts toward performance improvement. However, a number of strategies have been developed to identify the most relevant components. The Delphi technique under intuitionistic fuzzy environment, called intuitionistic fuzzy Delphi method (IFDM) study, is a group-based technique that can simply formulate the uncertainty imposed by decision making circle. On the other hand, multi criteria decision making (MCDM) method such as analytical network process (ANP) is a mathematical tool for taking into account mutual relationships in order to rank a number of criteria. Nonetheless, the ANP is unable to account for the uncertainty involved in the decision-making process. Similarly, the intuitionistic fuzzy set (IFS) can express ambiguity and vagueness by utilizing the given scale. Because the IFS is robust in dealing with complexity and ambiguity, the IFS-GANP (an integrated model of the IFS and ANP methods under group decision) can result in a more specific description of the situation. As a result, the IFS-GANP approach outperforms both conventional ANP and fuzzy ANP. To demonstrate the model’s feasibility, a case study rating the essential aspects impacting the attractiveness of retail centers is shown. The result demonstrates factor C31 (Location) with value of 0.202 plays the greatest role in attracting customers.

Network screening and countermeasure selection are two crucial steps in the highway improvement process. In network screening, potential improvement locations are ranked and prioritized based on a specific method with a set of criteria. The most common practice by transportation agencies has been to use a simple scoring method, which, in general, weighs and scores each criterion and then ranks the locations based on their relative overall scoring. The method does not deal well with criteria that are qualitative in nature, nor does it account for the impacts of correlation among the criteria. The introduction of Analytic Hierarchy Process (AHP) provides agencies with a method to include both quantitative and qualitative criteria. However, it does not address the issue on correlation. This dissertation explores the use of both Analytic Network Process (ANP) and Fuzzy Analytic Network Process (FANP) for their potential capabilities to address both issues. Using urban four-lane divided highways in Florida for bicycle safety improvements, both ANP and FANP were shown to provide more reasonable rankings than AHP, with FANP providing the best results among the methods. After the locations are ranked and prioritized for improvements, the next step is to evaluate the potential countermeasures for improvements at the selected top-ranked locations. In this step, the standard practice has been to use Crash Modification Factors (CMFs) to quantify the potential impacts from implementing specific countermeasures. In this research, CMFs for bicycle crashes on urban facilities in Florida were developed using the Generalized Linear Model approach with a Zero-Inflated Negative Binomial (ZINB) distribution. The CMFs were tested for their spatial and temporal transferability and the results show only limited transferability both spatially and temporally. The CMFs show that, in general, wider lanes, lower speed limits, and presence of vegetation in the median reduce bicycle crashes, while presence of sidewalk and sidewalk barrier increase bicycle crashes. The research further considered bicycle exposure using the bicycle activity data from the Strava smartphone application. It was found that increased bicycle activity reduces bicycle crash probabilities on segments but increases bicycle crash probabilities at signalized intersections. Also, presence of bus stops and use of permissive signal phasing at intersections were found to increase bicycle crash probabilities.

The use of logistics outsourcing or third-party logistics (3PL) is becoming a global trend. For suiting the needs of outsourcing companies, here raises a critical issue of how companies can evaluate and select a favorable logistics service provider. However, choosing a proper logistics service provider is a kind of multicriteria decision-making (MCDM) problem, which requires considering a large number of complex factors. The analytic network process (ANP) is a relative new MCDM theory of measurement used to deal with complex decision issues with dependence and feedback However, the approach is incapable of capturing the vagueness and fuzziness during value judgment elicitation. In view of this, a method to select a proper 3PL provider is proposed by applying an fuzzy ANP (FANP). The merits of the FANP lie in, not only could it handle the complexity of the problem structure, but also it may soundly deal with the judgments derived from intrinsically imprecise information. Finally, a real case application is given to validate the feasibility of the proposed approach.

Previous researches outlined the advantages of the Analytical Hierarchy Process (AHP) and Analytic Network Process (ANP) methods in solving Multi-Attribute Decision Making (MADM) problems. The advancement of the above methods was continually developed as an effort to cover up various weaknesses. Mainly related to the consistency and linguistic variables in translating the expert opinions. Thus, it initialized the emergence of Fuzzy AHP (F-AHP) and Fuzzy ANP (F-ANP). Due to the restricted operation of these algorithms in smartphone selection, this research attempted to investigate the effectiveness of both methods in providing the analysis of criteria weight, the final recommendation weight, the product recommendation weight, and the execution time in DSS-SmartPhoneRec application development. A survey of one hundred respondents of University students identified the dominant criteria in selecting the smartphone, namely price, Random Access Memory (RAM), processor, internal memory, and camera. Hence, five alternative products were then chosen as the appropriate smartphones’ recommendations based on the respondent’s preferences. As an automatic tool, a DSS-SmartPhoneRec application was built to analyze and compare between F-AHP and F-ANP methods in resolving the smartphone selection cases. It revealed that the level of consistency of criteria weight, the final weight of recommendation, and the weight that the product-based F-ANP was 40% greater than F-AHP. In terms of execution time, F-AHP had a shorter time than F-ANP. Meanwhile, the comparison of products recommendation from DSS-SmartPhoneRec and a manual test showed that F-ANP was 16% more in line with the respondents’ predilection. In a nutshell, the DSS-SmartPhoneRec administered the devote smartphone recommendations based on the user’s expectation. The comparison analysis furnished a learning outcome for the users in determining the appropriate MADM method tailored to the type of cases.

This paper explores the probabilistic fuzzy analytic network process (PROFUZANP) approach in identifying the content of manufacturing strategy infrastructural decisions that attempt to integrate a sustainability and classical manufacturing strategy framework, in the presence of firm size as a relevant component in decision-making. Linguistic variables with equivalent triangular fuzzy numbers (TFNs) are used to elucidate the judgment of elements in pairwise comparison in the framework of the analytic network process (ANP). The ANP effectively handles the complexity of decision-making brought about by the subjectivity and relationships among components of the decision model. Integration of expert judgments conducted by introducing a normal probability distribution in each pairwise comparison with mean equal to the geometric mean of the judgment and standard deviation equal to a predefined perturbation of judgment around the mean. Pre-selected experts in manufacturing strategy and sustainability were asked to elicit judgment in pairwise comparison. Results show that the content of the infrastructural decisions of manufacturing strategy remains constant regardless of the types of firm size. However, the priority of each decision to the goal, which can be translated as the priority of implementation of each policy, varies between large firms and SMEs. The main contribution of this paper is a novel approach that holistically captures the judgmental uncertainty of individual decision-makers and the uncertainty of group decision-making.

Wenchuan earthquake disaster reconstruction planning is a typical government investment project, the performance evaluation of which is conducive to improve the management ability of government of managing disaster reconstruction projects and enriches the finance expenditure decision-making reliance of disaster reconstruction projects. There may be dependence and feedback among factors of disaster reconstruction performance evaluation. In this study, analytic network process (ANP) was adopted to model a multi-criteria disaster reconstruction performance evaluation indices system with dependence and feedback. Due to complexity in evaluating disaster reconstruction performance, it is difficult for decision-makers to provide exact numerical values for the factors. Therefore, a fuzzy ANP method was taken to calculate the weights of each factor of the model, which can solve problems in an uncertain condition effectively.

Forest fires have a significant impact on human life, property safety, and ecological environment. Deve-loping high-quality forest fire risk maps is beneficial for preventing forest fires, guiding resource allocation for firefighting, assisting in fire suppression efforts, and supporting decision-making. With a multi-criteria decision analysis (MCDA) method based on geographic information systems (GIS) and literature review, we assessed the main factors influencing the occurrences of forest fires in Youxi County, Fujian Province. We analyzed the importance of each fire risk factor using the analytic network process (ANP) and assigned weights, and evaluated the sub-standard weights using fuzzy logic assessment. Using ArcGIS aggregation functions, we generated a forest fire risk map and validated it with satellite fire points. The results showed that the areas classified as level 4 or higher fire risk accounted for a considerable proportion in Youxi County, and that the central and northern regions were at higher risk. The overall fire risk situation in the county was severe. The fuzzy ANP model demonstrated a high accuracy of 85.8%. The introduction of this novel MCDA method could effectively improve the accuracy of forest fire risk mapping at a small scale, providing a basis for early fire warning and the planning and allocation of firefighting resources.

Long term supplier selection using a combined fuzzy MCDM approach: A case study for a telecommunication company