Fuzzy Axiomatic Design Research Articles

Extending a pessimistic–optimistic fuzzy information axiom based approach considering acceptable risk: Application in the selection of maintenance strategy

Maintenance is considered as an important factor in the improvement of machine performance. Indeed, maintenance plays an important role in maintaining reliability, availability, quality of products, reducing risk, improving efficiency, and safety. In maintenance problems, the desired real data cannot easily be found, thus decision making by applying expert knowledge is the only way. However, due to the existence of uncertainties in these assessments, the accuracy of evaluations may be questioned. The aim of this study was to present an appropriate mathematical model for decision making in the assessment and selection of proper maintenance strategy in risky situations. For this purpose, a model based on fuzzy axiomatic design (FAD) is presented, wherein each evaluation has both optimistic and pessimistic fuzzy scores, as the fuzzy evaluations themselves have risks. In order to improve the accuracy of the presented method, a new concept called “acceptable risk” has been suggested. A real case study, to measure the effectiveness of the proposed model, is conducted in a rolling mill company and the obtained results are compared with other FAD concepts.

An Evidential Axiomatic Design Approach for Decision Making Using the Evaluation of Belief Structure Satisfaction to Uncertain Target Values

Axiomatic design (AD) provides a general theory for system and product development. In recent years, the principles of AD have been successfully applied to the decision-making field, and derived a fuzzy AD approach for fuzzy decision-making environment. In this work, the interest is paid on the theoretical developments and applications of AD in the uncertain environment expressed by Dempster–Shafer evidence theory. Based on the concept of belief structure satisfaction to uncertain target values, an evidential AD approach is proposed for decision making by combining the independence axiom and information axiom of AD with the framework of Dempster–Shafer theory. An illustrative example has demonstrated the effectiveness of the proposed approach. This work, on the one hand, has successfully generalized the principles of AD to the Dempster–Shafer uncertain environment; on the other hand, it has presented a successful application of the concept of belief structure satisfaction.

Ranking maintenance strategies for sustainable maintenance plan in manufacturing systems using fuzzy axiomatic design principle and fuzzy-TOPSIS

PurposeMaintenance plans are programmes, which follow maintenance appraisals, contain information of what to do and the time approximates for accomplishments. They also deal with how to carry out maintenance jobs. In contemporary period, curiosity has proliferated about how sustainability affects manufacturing plans. The purpose of this paper is to offer a comprehensive notion of maintenance sustainability in maintenance planning. The literature has downplayed maintenance sustainability but may support in understanding how to crack the present company-community conflicts about the negative influence of manufacturing on the environment.Design/methodology/approachThis study develops the idea of selecting the proper maintenance strategy based on integrated fuzzy axiomatic design (FAD) principle and fuzzy-TOPSIS. This work suggests that the maintenance function is an uncertain, activity-oriented system. To fully appreciate the proposed framework, the work employs data from a cement manufacturing plant to test the structure. This study offers 20 influential factors on which it build the fundamental structure of maintenance system sustainability for manufacturing concerns. A novel literature contribution that departs from existing conceptions is the classical determination of weights of each sustainability factor, employing fuzzy entropy weighting approach. Furthermore, work innovatively determines the ranking of some important tenets of sustainability in maintenance and optimises the maintenance consumables employing the FAD principle.FindingsInterestingly, the output of the investigation revealed differences as the work adopts fuzzy-TOPSIS in comparison with FAD principle.Originality/valueCase examination of a real-life manufacturing venture validated the claims, showing maintenance workforce training as a top-echelon strategy for maintenance system sustainability.

Application of fuzzy axiomatic design principles for cotton fibre selection

Selection of cotton fibres as the raw material in textile spinning industries can often be formulated as a multi-criteria decision-making problem. Sometimes, the nature of this selection problem becomes complicated and unstructured requiring the deployment of advanced mathematical tools and techniques to derive at the most acceptable solution. The traditional computational methods are inapt to deal with fuzzy information, if present in a decision-making problem. Thus, in this paper, the application of fuzzy axiomatic design (FAD) principles is presented in order to identify the most suitable cotton fibre for ring spun yarn from a set of competing alternatives while fulfilling the requirements of the spinning industries. It can quantitatively transform the impreciseness present in the cotton fibre selection problem while yielding satisfactory ranking order of the considered alternatives. To ease out this cotton fibre selection process, a software prototype is also developed which can be applicable to any type of decision-making problem with fuzzy information having any number of alternatives and criteria. It is observed that the ranking pattern of the cotton fibre alternatives derived from FAD methodology is almost similar to that obtained by the past researchers.

RFID service provider selection: An integrated fuzzy MCDM approach

The Radio Frequency Identification (RFID) technology supports companies to optimize business processes and reduce operational costs by knowing an item’s condition and location in the inventory. RFID applications expand on the basis of speed, security and correct information flow; however, selecting the most suitable RFID service provider presents a challenge. This article offers an integrated multi-criteria evaluation framework for selecting the most suitable RFID service provider by applying Fuzzy Axiomatic Design (Fuzzy AD) and Fuzzy Analytic Hierarchy Process (Fuzzy AHP) techniques with Group Decision Making (GDM) approach. A case study is conducted and the results are discussed through a sensitivity analysis and a comparative evaluation with fuzzy TOPSIS. It is observed that an alternative RFID service provider that does not meet the defined Functional Requirements (FRs) is directly eliminated by Fuzzy AD, whereas fuzzy TOPSIS ranks it as an eligible one. The sensitivity analysis demonstrates that if FRs are low enough, the outcome of Fuzzy AD and fuzzy TOPSIS do converge, underlining the goal-oriented advantage of Fuzzy AD. The paper contributes to literature by presenting a novel approach for incorporating subjective and often conflicting linguistic evaluations of a decision committee into a solid decision support model approach for selecting the most suitable RFID service provider.

Multiattribute Decision Making Using Multiperiod Probabilistic Weighted Fuzzy Axiomatic Design

Axiomatic Design is a methodology that provides a framework to systematically analyze the transformation of customer needs into functional requirements and design parameters. Decision-makers use Weighted Fuzzy Axiomatic Design (wFAD) in cases where there is imperfect information, and decision criteria have different priorities. In this paper, the wFAD approach is extended to situations which include uncertainty in future events and decision payoffs. In particular, we consider multiple future scenarios with different probabilities and time-dependent decision payoffs for each system range (SR). For such decision problems, we propose the Multiperiod Probabilistic Weighted Fuzzy Axiomatic Design (MPP-wFAD) methodology. The methodology utilizes probabilistic scenario analysis and SR forecast data to assist decision makers in attaining better decisions with improved expected payoffs. As a case study, we apply MPP-wFAD to tackle a multiattribute industry selection problem in Turkey and show the impact and usability of the method.

Failure Modes and Effects Analysis under Fuzzy Environment Using Fuzzy Axiomatic Design Approach

Failure Modes and Effects Analysis (FMEA) is being widely used to detect and eliminate known and/or potential failures, problems, errors and so on from system design, process, and/or service, before they reach the customer. It can be done by calculating the risk priority number which is the product of three factors: occurrence, severity and detectability. A lot of efforts have been made to overcome the shortcomings of the crisp RPN calculation and extend it to fuzzy environment. In this study, the presented fuzzy approach allows experts to describe the variables of risk priority number using linguistic terms by applying the method of fuzzy axiomatic design (FAD). At the final part of this paper a hypothetical case study demonstrated the applicability of the FMEA model under fuzzy environment.

Solution of Material Selection Problem Using Fuzzy Axiomatic Design and DEMATEL Methods

Solution of Material Selection Problem Using Fuzzy Axiomatic Design and DEMATEL Methods

A weighted rough set based fuzzy axiomatic design approach for the selection of AM processes

Additive manufacturing (AM) or 3D printing, as an enabling technology for mass customization or personalization, has been developed rapidly in recent years. Various design tools, materials, machines and service bureaus can be found in the market. Clearly, the choices are abundant, but users can be easily confused as to which AM process they should use. This paper first reviews the existing multi-attribute decision-making methods for AM process selection and assesses their suitability with regard to two aspects, preference rating flexibility and performance evaluation objectivity. We propose that an approach that is capable of handling incomplete attribute information and objective assessment within inherent data has advantages over other approaches. Based on this proposition, this paper proposes a weighted preference graph method for personalized preference evaluation and a rough set based fuzzy axiomatic design approach for performance evaluation and the selection of appropriate AM processes. An example based on the previous research work of AM machine selection is given to validate its robustness for the priori articulation of AM process selection decision support.

Technique selection and evaluation of ballast water management methods under an intuitionistic fuzzy environment: An information axiom approach

A recent survey showed the reluctance of ship-owners to install ballast water treatment systems onboard their ships. This raised a question on the acceptability of shipboard management of ballast water and the need to investigate the potential of non-shipboard alternatives to managing the menace of invasive species transfer via ships’ ballast water. The aim of this article is to investigate the viability of both shipboard and onshore-based concepts of ballast water management with respect to the evaluation criteria stipulated in the Ballast Water Management Convention of the International Maritime Organization. To achieve that, an appropriate decision-making technique was selected using a robust procedure; this is critical in the evaluation and ultimate selection of an appropriate ballast water management method. A multi-criteria decision-making technique known as intuitionistic fuzzy multi-attribute axiomatic design which is a hybridized extension of fuzzy axiomatic design was employed for the selection process. The eventual selected technique was used to evaluate the ballast water management options based on the linguistic data collected from an interview with ballast water management experts. The novel applications of intuitionistic fuzzy multi-attribute axiomatic design in this article for technique selection and subsequently for ballast water management methods’ evaluation exemplify not only the versatility of the technique as a decision-making tool but also showed a strong paradigm shift in experts’ opinions about the future of ballast water management beyond just the traditional shipboard system.

Interval target-based VIKOR method supported on interval distance and preference degree for machine selection

By considering target values for attributes in addition to beneficial and non-beneficial attributes, a traditional MADM technique is converted to a comprehensive form. In many machine selection problems, some attributes have given target values. The target value regarding a machine attribute can be reported as a range of data. Some target-based decision-making methods have recently been developed; however, a research gap exists in the area. For example, fuzzy axiomatic design approach presents a target-based decision-making supported on common area of membership functions of alternative ratings and target values of attributes. However, it has detects on finding a complete ranking because of probable infinite values of assessment index. Two target-based VIKOR models with interval data exist in the literature; however, the target values of attributes or ratings of alternatives on attributes are crisp numbers in the models and their formulations may have some limitations. The present paper tries to fill the gap by developing the VIKOR method with both interval target values of attributes and interval ratings of alternatives on attributes. Moreover, we attempt to utilize the power of interval computations to minimize degeneration of uncertain information. In this regard, we employ interval arithmetic and introduce a new normalization technique based on interval distance of interval numbers. We use a preference matrix to determine extremum and rank interval numbers. Two machine selection problems concerning punching equipment and continuous fluid bed tea dryer are solved employing the proposed method. Preference-degree-based ranking lists are formed by calculating the relative degrees of preference for the arranged assessment values of the candidate machines. The resultant rankings for the problems are compared with the results of fuzzy axiomatic design approach and the interval target-based MULTIMOORA method and its subordinate parts.

Risk-based material selection process supported on information theory: A case study on industrial gas turbine

Gas turbine blades are produced using high-temperature high-strength materials because they are often exposed to severe environments. Material selection for such cases should be performed with sensitivity and using a systematic method. Moreover, various risks may exist about the values of materials properties. For example, the difference between the designed and unexpected conditions may pose some risks to materials properties. Although considering risks for gas turbine blade material selection problem or similar high-tech practical cases is important, a research gap exists in such fields. This paper presents a risk-based material selection algorithm using the principles of Suh and Shannon entropies supported on information theory. In this regard, we develop the risk-based fuzzy axiomatic design approach with the integrated Shannon significance coefficients of attributes. A real-world example about material selection of industrial gas turbine blade is examined using four techniques including the fuzzy axiomatic design, weighted fuzzy axiomatic design, risk-based fuzzy axiomatic design, and weighted risk-based fuzzy axiomatic design approaches. In the example, risk factors are determined to consider the effect of temperature variation on materials properties. Finally, the resultant rankings are compared by calculating Spearman rank correlation coefficients. The comparisons show that considering risk factors in the problem affects the resultant ranking. We validate the results of the proposed methods by the unweighted and weighted fuzzy MULTIMOORA approaches.

Personnel Selection Using Fuzzy Axiomatic Design Principles

Overall competency of the working personnel is often observed to ultimately affect the productivity of an organization. The globalised competitive atmosphere coupled with technological improvements demands for efficient and specialized manpower for the industrial operations. A set of typical technological skills and attitudes is thus demanded for every job profile. Most often, these skills and attitudes are expressed imprecisely and hence, necessitating the support of fuzzy sets for their effective understanding and further processing. In this paper, a method based on fuzzy axiomatic design principles is applied for solving the personnel selection problems. Selecting a middle management staff of a service department for a large scale organization is demonstrated here as a real life example. Five shortlisted candidates are assessed with respect to a set of 18 evaluation criteria, and the selection committee with experts from the related fields also realizes the outcome of the adopted approach to be quite appropriate, befitting and in agreement with their expectations.

Application of a new combined intuitionistic fuzzy MCDM approach based on axiomatic design methodology for the supplier selection problem

Evaluating and selecting a suitable supplier is a complex problem which involves a number of different criteria. In literature, there are various multi-criteria decision making (MCDM) methods available with their own characteristic features. The focus of this study is intuitionistic fuzzy (IF) MCDM methods which have attracted much attention from academics and practitioners in recent years. IF sets are widely used to tackle imprecise and uncertain decision information in decision making due to their capability of accommodating the hesitation in human decision processes. This study proposes a new integrated methodology that is used for the first time in the literature. This approach consists of intuitionistic fuzzy analytic hierarchy process (IFAHP), an MCDM technique, for determining the weights of supplier evaluation criteria, and the concept of intuitionistic fuzzy axiomatic design (IFAD) principles for ranking competing supplier alternatives with respect to their overall performance. Decision makers’ assessments and opinions are extended to the IF environment in this approach and furthermore, the group decision making (GDM) approach is utilized in order to overcome uncertainties and vagueness, minimize the partiality of decision process and to avoid bias. This study contributes to supplier selection and IF sets literature by providing a combined framework based on IFAHP and IFAD methodology for the first time. To assess the validity of the proposed integrated IF MCDM approach, a case study from Turkey is provided. This study can be useful to researchers in better understanding the supplier selection problem theoretically, as well as to organizations in designing better satisfying supplier evaluation systems.

Matching demanders and suppliers in knowledge service: A method based on fuzzy axiomatic design

The advancement of knowledge service has enabled the demanders and suppliers to find satisfied cooperation results. An optimal match between demanders and suppliers can facilitate continuous improvement and efficiency in knowledge services. While selecting suitable matching knowledge demander and supplier pairs is of significance for effective knowledge services, an area that has been generally neglected in previous studies. This paper reports on a method for effectively matching suitable knowledge service demanders and suppliers in which the expectation levels of attributes given by demanders and suppliers are considered. Linguistic information is used to describe the demanders and suppliers’ expectation levels and their actual levels. A new matching degree calculation method is proposed which takes account of the fuzzy linguistic information. First, the matching relationship between the demanders and suppliers is defined. Then, from the principle of axiomatic design (AD), a method based on fuzzy axiomatic design (FAD) is developed to identify the matching degree between the knowledge demanders and suppliers. Further, a multi-objective optimization model is formulated to maximize the overall matching degree of the pairs and to select the optimal matching pairs. Finally, an example illustrates the potential applications of the proposed method. The obtained computational process and results clearly demonstrate how optimal matching pairs can be identified for knowledge services’ demanders and suppliers.

A sequence dependent single machine scheduling problem with fuzzy axiomatic design for the penalty costs

In this paper, a scheduling problem on a single machine producing dairy products subject to variable due dates, earliness and tardiness penalty costs and sequence dependent setup times was studied. The main purpose was to meet demands of customers just in time whilst total penalty costs of earliness and tardiness were minimized. In addition, applicability of the schedules was appraised using Fuzzy Axiomatic Design (FAD) to determine earliness and tardiness penalty costs. A hierarchical approach consisting of meta-heuristic algorithms such as a tabu search and a genetic algorithm was proposed to generate proper schedules. In the first stage, an initial solution was found by the tabu search algorithm. The solution was improved using the genetic algorithm to find an optimum or a near optimum solution in the second stage. The proposed approach was employed on a cheese production process in the food industry. An instance of the algorithm was demonstrated to illustrate the applicability of the proposed approach and the results obtained were highly favourable.

SMALL HYDRO-POWER PLANT PROJECT SELECTION USING FUZZY AXIOMATIC DESIGN PRINCIPLES

There has been a rapid growth in construction activities during the last few decades owing to overall development in all facets of humanity. Due to technological advancements and ever increasing civilization, there is a persistent need of energy. Along with the conventional energy sources, the renewable energy sources have also significantly contributed to the rising energy needs. As a renewable source of energy, numerous small hydro-power plants (SHPPs) have been built up across the world in the recent past. Usually these SHPPs are being built and operated by the private developers complying with the government regulations. In order to assist a developer in selecting the most profitable and feasible SHPP for construction and subsequent operation, a method based on fuzzy axiomatic design principles is employed in this paper. The techno-commercial and socioeconomic criteria as considered for analyzing the feasibility of the candidate SHPPs are expressed qualitatively using trapezoidal fuzzy numbers. The performance of each SHPP is evaluated in terms of its total information content and the one with the least information content is selected to be the best venture for the required construction activity. The adopted methodology is found to have immense potential to the developers while selecting the most feasible project for construction.

Application of fuzzy axiomatic design principles for selection of non-traditional machining processes

Since the last few decades, there have been tremendous technological advancements in communication, aeronautics, automobiles, textile engineering, nuclear energy, medical sciences and die-making industries. These have necessitated the use of some totally new and hitherto unknown high-strength temperature-resistant, tough and difficult-to-machine materials and, consequently, some newer unconventional processes for their efficient machining. It has been well established that non-traditional machining processes (NTMPs) far surpass their traditional counterparts in machining such advanced materials with respect to tolerance, surface finish, accuracy, complexity and miniatureness of the machined product/part. These NTMPs are also found to be more effective and economical. Choosing the most appropriate NTMP for generation of a desired shape feature on a given work material involves consideration of numerous conflicting qualitative and quantitative criteria. This paper proposes the application of fuzzy axiomatic design principles for selection of the most suitable NTMPs for generating cavities on ceramics and micro-holes on hardened tool steel and titanium materials, based on their practical/industrial importance. For micro-drilling operation on hardened tool steel, electrical discharge machining is found to be the best process followed by abrasive jet machining and ultrasonic machining. On the other hand, for generation of micro-holes on titanium, electrochemical machining is the most suitable process. Abrasive jet machining emerges out as the most efficient process for generating blind cavities on ceramics. These results are well in accordance with the expected machining practices and perfectly match with the decisions of the machining professionals.

An integrated fuzzy approach for information technology planning in collaborative product development

Collaborative product development (CPD) processes are generally based on technological infrastructures. Various information technologies (IT) are proposed every day to facilitate collaboration, integration, co-design and co-development processes. In this highly uncertain environment, a systematic methodology is essential to plan the IT infrastructure needed to start and maintain a collaborative process. This study offers an integrated IT planning methodology combining fuzzy quality function deployment, fuzzy axiomatic design and fuzzy rule-based systems. The methodology is tested in a CPD case and the outcome presents an improvement path for IT for each of the collaborative parties.

A new multi criteria decision making approach for medical imaging systems considering risk factors

Effective and good quality imaging is important for medical decision-making and can reduce unnecessary costs and procedures. Therefore, decision making regarding any technology can present serious problems for healthcare centers with multi criteria decision making problems (MCDM). This paper is the first to develop the fuzzy axiomatic design with risk factors (RFAD) approach and to use it in multi attribute comparisons of medical imaging systems in a university hospital. Although most MCDM approaches in the literature treat risk factors as separate criteria, in real life every alternative has its own risks related to each criterion. The proposed approach integrates the risk factors in each criterion and calculates the information content to compare alternatives. This paper applies three different approaches to MCDM problems related to the selection of medical imaging systems for a university hospital.