Evaluation and Selection of the Quality Methods for Manufacturing Process Reliability Improvement—Intuitionistic Fuzzy Sets and Genetic Algorithm Approach
Round 1
Reviewer 1 Report
The paper proposes a decision making model to evaluate and select quality methods to improved reliability of manufacturing. The approach is challenging. However I see some drawbacks:
(1) Regarding fuzzy nomenclature, you use some acronyms without defining it.
(2) The phrase "The use of the intuitionistic fuzzy set allows natural language words to be significantly quantitatively described, as has been done in this paper" (lines 146-148) can be applied to many different generalizations of fuzzy sets. I'm not sure what you mean here...
(3) The definitions in section 3.1 are not properly formatted. In addition some of them are not clear at all. For example in definition 3 you use 2 TIFNs , but were are they properly defined?
(4) In definition 4, you mention C-OWA operators. It is a strange way of define a defuzzification.
(5) In section 3.3 you introduce the quantifiers. The question is, which is the bases to define the quantifiers in this way?
(6) Regarding the genetic algorithm, I think you should define in detail the initial codification as well as the parameter settings.
(7) With regard to the case study. First of all, when you use a genetic algorithm you should compare its behavior with regard to some benchmark methods. As you mention that there is no benchmarking, you could have been shown the behavior of it depending on the parameters. But from my point of view, it makes no sense to present all the computations, neither the iterations. Figure 1 does not provide any informations, one has to imagine what you are presenting there.
Apart from these major things, you should carefully revise English (there is some word not in English) and revise the literature about fuzzy sets and their generalizations.
To sum up, even if the proposal potentially solve a problem, you don't show the benefits.
Author Response
Authors wish to express their gratitude to the reviewers for the useful comments and suggestions.
The changes incorporated in the manuscript have been denoted in blue.
Author Response File: 
Author Response.docx
Reviewer 2 Report
The manuscript entitled “Intuitionistic fuzzy sets and genetic algorithm approach for 2 evaluation and selection of the quality methods for manufacturing process reliability improvement” is interesting from the theoretical and practical perspective.
In order to be accepted, the manuscript has to be improved as following:
- The title should be changed as it depicts methodology instead of contribution. I suggest: “Evaluation and selection of the quality methods for manufacturing process reliability improvement - Intuitionistic fuzzy sets and genetic algorithm approach”
- In the introduction section, the authors said: “According to the Lean concept [2], there are seven types of waste found in any process: Transportation, Inventory, Motion, Waiting, Overprocessing, Overproduction and Defect. Later, Liker [3] introduced waste related to underutilization of labour creativity, and it is denoted as Unused employee creativity.” It can be analysed as presented but authors should explain generating waste and malfunction of the system may be treated form the perspective of other concepts, too.
- In the section 2, authors stated: “In the literature, there are a large number of papers in which the relative importance of RFs and its values are modelled by: (i) type 1 fuzzy sets [26, 27], (ii) the interval type 2 fuzzy numbers [10, 28], and (iii) Intuitionistic fuzzy sets [29, 30, 31]. The basic characteristic of type 1 fuzzy sets is a single membership function which describes the belonging of the element fuzzy sets [32]. The interval type 2 fuzzy sets is described by upper and lower membership function [33] which better describes uncertainties but requires a large amount of computation.” As the focus of the paper is set to intuitionistic fuzzy sets, there is no need to explain type 1 fuzzy sets and the interval type 2 fuzzy numbers. These references and explanations should be removed.
- The notation used is good which enables readers to go smoothly through the whole manuscript.
- After the part: “GA (Step 12 of the proposed Algorithm) was applied to find a near-optimal solution. The stop criterion is defined to have a number of iterations equal to 1000.” The authors have presented the results of the testing in the scope of the o. iteration and 1. iteration. This results should be removed from the manuscript.
- The conclusions are presented in clear manner.
After the minor revision, the manuscript could be considered for publishing.
Author Response
Authors wish to express their gratitude to the reviewers for the useful comments and suggestions.
The changes incorporated in the manuscript have been denoted in blue.
Author Response File: Author Response.docx
Round 2
Reviewer 1 Report
The authors have followed my suggestions si I recommend the publication in its present form
