A decision maker usually holds various viewpoints regarding the priorities of criteria, which complicates the decision making process. To overcome this concern, in this study, a diversified AHP-tree ...approach was proposed. In the proposed diversified AHP-tree approach, the judgement matrix of a decision maker is decomposed into several subjudgement matrices, which are more consistent than the original judgement matrix and represent diverse viewpoints on the relative priorities of criteria. Thus, a nonlinear programming model was established and optimized, for which a genetic algorithm is designed. To assess the effectiveness of the proposed diversified AHP-tree approach, it was applied to a supplier selection problem. The experimental results showed that the application of the diversified AHP-tree approach enabled the selection of multiple diversified suppliers from a single judgement matrix. Furthermore, all suppliers selected using the diversified AHP-tree approach were somewhat ideal.
Fuzzy analytic hierarchy process (FAHP) has been extensively applied to multi-criteria decision making (MCDM). However, the computational burden resulting from the calculation of fuzzy eigenvalue and ...eigenvector is heavy. As a result, a FAHP problem is usually solved using approximation techniques such as fuzzy geometric mean (FGM) and fuzzy extent analysis (FEA) instead of exact methods. Therefore, the FAHP results are subject to considerable inaccuracy. To solve this problem, in this study, a FAHP method based on the combination of
α
-cut operations (ACO), center-of-gravity (COG) defuzzification and defuzzification convergence mechanism (DCM) is proposed. First, ACO is applied to derive the near-exact fuzzy maximal eigenvalue and fuzzy weights. Subsequently, the
α
cuts of the fuzzy maximal eigenvalue and fuzzy weights are interpolated to generate samples that are uniformly distributed along the
x
-axis so that COG can be correctly applied to defuzzify the fuzzy maximal eigenvalue and fuzzy weights. To accelerate the computation process, DCM is applied to terminate the enumeration process if the defuzzified values of fuzzy weights have converged. The ACO–COG–DCM method has been applied to a real case to illustrate its applicability. In addition, a simulation study was also conducted to perform a parametric analysis. According to the experimental results, the proposed ACO–COG–DCM method improved the accuracy of estimating fuzzy weights by up to 56%. Furthermore, the experimental results also showed that the inaccuracy of estimating fuzzy weights was mostly owing to the deficiency of the FAHP method rather than the inconsistency of fuzzy pairwise comparison results.
In the aircraft industry, three-dimensional (3D) printing can confer several benefits, such as shortened cycle times, reduced production costs, and lighter part weights. However, some concerns must ...be addressed for 3D-printing applications to be viable. This paper investigated these concerns by reviewing the current 3D printing practices in the aircraft industry. The literature review identified five factors critical to the applicability of advanced 3D printing technologies to the aircraft industry, and a fuzzy systematic approach was applied to assess the applicability and relative importance of the identified factors, combining fuzzy geometric mean and fuzzy analytical hierarchy process. The findings provide valuable input for countries or regions considering expanding 3D printing applications to their aircraft industries.
The COVID-19 pandemic has severely impacted factories all over the world, which have been closed to avoid the spread of COVID-19. As a result, ensuring the long-term operation of a factory amid the ...COVID-19 pandemic becomes a critical but challenging task. To fulfill this task, the applications of smart and automation technologies have been regarded as an effective means. However, such applications are time-consuming and budget-intensive with varying effects and are not necessarily acceptable to workers. In order to make full use of limited resources and time, it is necessary to establish a systematic procedure for comparing various applications of smart and automation technologies. For this reason, an evolving fuzzy assessment approach is proposed. A case study has been conducted to demonstrate the effectiveness of the evolving fuzzy assessment approach in ensuring the long-term operation of a factory amid the COVID-19 pandemic.
Purpose
This study aims to investigate issues of quality and quality control (QC) in three-dimensional (3D) printing by reviewing past work and current practices. Possible future developments are ...also discussed.
Design/methodology/approach
After a discussion of the major quality dimensions of 3D-printed objects, the applications of some QC techniques at various stages of the product life cycle (including product design, process planning, incoming QC, in-process QC and outgoing QC) are introduced.
Findings
The application of QC techniques to 3D printing is not uncommon. Some techniques (e.g. cause-and-effect analysis) have been applied extensively; others, such as design of experiments, have not been used accurately and completely and therefore cannot optimize quality. Taguchi’s method and control charts can enhance the quality of 3D-printed objects; however, these techniques require repetitive experimentation, which may not fit the work flow of 3D printing.
Originality/value
Because quality issues may discourage customers from buying 3D-printed products, enhancing 3D printing quality is imperative. In addition, 3D printing can be used to manufacture diverse products with a reduced investment in machines, tools, assembly and materials. Production economics issues can be addressed by successfully implementing QC.
Current group decision-making fuzzy analytic hierarchy processes (FAHPs) have two major problems. First, inconsistent fuzzy pairwise comparison results, rather than compromised fuzzy weights, are ...aggregated. Second, a consensus among decision makers (DMs) cannot be guaranteed. To address these problems, in this study, the guaranteed-consensus posterior-aggregation FAHP (GCPA-FAHP) method was proposed. In the proposed methodology, the membership functions of the linguistic terms for performing fuzzy pairwise comparisons were designed to guarantee a consensus among the DMs and can be modified afterward to enhance the estimation precision. In addition, fuzzy intersection and center of gravity were used to aggregate and defuzzify the estimated fuzzy weights. The GCPA-FAHP method was applied to a real case to evaluate its effectiveness. The experimental results revealed that the GCPA-FAHP method guaranteed consensus among the DMs and improved the precision of estimating fuzzy weights.
This study proposes a hybrid big data analytics and Industry 4.0 (BD-I4) approach to enhancing the effectiveness of cycle time range projections for factory jobs. As a joint application of big data ...analytics and Industry 4.0, the BD-I4 approach is distinct from existing methods in this field. In this approach, each expert first constructs a fuzzy deep neural network to project the cycle time range of a job, an application of big data analytics (i.e., deep learning). Subsequently, the fuzzy weighted intersection operator is applied to aggregate the projected cycle times such that unequal authority levels can be considered, an application of Industry 4.0 (i.e., artificial intelligence). Applying the BD-I4 approach to a real case that the proposed methodology improved the projection precision by up to 72%, suggesting that instead of relying on a single expert, collaboration among multiple experts may be more effective and efficient.
Advances in computer and communication technologies have engendered opportunities for developing an improved ubiquitous health care environment. One of the crucial applications is a ubiquitous clinic ...recommendation system, which entails recommending a suitable clinic to a mobile patient based on his/her location, hospital department, and preferences. However, patients may not be willing or able to express their preferences. To overcome this problem, some ubiquitous clinic recommendation systems mine the historical data of patients to learn their preferences, and they apply an algorithm to adjust the recommendation algorithm after receiving more patient data. Such an adjustment mechanism may operate for several periods; however, this raises a question regarding the sustainability (i.e., long-term effectiveness) of such an adjustment mechanism. To address this question, this study modeled the improvement in the successful recommendation rate of a ubiquitous clinic recommendation system that adopts an adjustment mechanism as a learning process. Both the asymptotic value and learning speed of the learning process provide valuable information regarding the long-term effectiveness of the adjustment mechanism. The proposed methodology was applied in a regional study to a ubiquitous clinic recommendation system that adjusts the recommendation mechanism by solving an integer nonlinear programming problem on a rolling basis. The experimental results revealed that the proposed method exhibited a considerably higher level of accuracy in forecasting the successful recommendation rate compared with several existing methods. Although the adjustment mechanism exhibits long-term effectiveness, the learning speed requires improvement.
The application of three-dimensional (3D) printing can enhance not only the competitiveness but also the sustainability of an aircraft manufacturing or maintenance, repair, and overhaul (MRO) ...company. This study sought to identify the critical factors for such applications. Herein, first, the long-term opportunities and challenges facing an aircraft manufacturing or MRO company planning to apply 3D printing technologies are discussed. The critical factors for enhancing their sustainability are identified from the discussion results. The priorities of critical factors are usually ranked using the fuzzy analytic hierarchy process (FAHP). However, existing FAHP methods cannot rank priorities reasonably when experts (or decision-makers) fail to reach an overall consensus. To address this problem, a novel partial consensus (PC)-FAHP approach is proposed that seeks to obtain a partial consensus among experts. After assessing the effectiveness of the proposed methodology with a case study involving three experts, the most critical factors were identified to be the long-term cost-effectiveness, number or types of aircraft parts that are or will be 3D printable, and advances in research and development that have been made already or are expected in the near future. In addition, the ranking result obtained using the PC-FAHP approach was different from that obtained using existing FAHP methods.
A challenge facing all ubiquitous clinic recommendation systems is that patients often have difficulty articulating their requirements. To overcome this problem, a ubiquitous clinic recommendation ...mechanism was designed in this study by mining the clinic preferences of patients. Their preferences were defined using the weights in the ubiquitous clinic recommendation mechanism. An integer nonlinear programming problem was solved to tune the values of the weights on a rolling basis. In addition, since it may take a long time to adjust the values of weights to their asymptotic values, the back propagation network (BPN)-response surface method (RSM) method is applied to estimate the asymptotic values of weights. The proposed methodology was tested in a regional study. Experimental results indicated that the ubiquitous clinic recommendation system outperformed several existing methods in improving the successful recommendation rate.
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