(Worse) Introduction of the MRSN ratio is possible by integration of the quality loss for all responses.

(Better) Integrating the quality loss for all responses can introduce the MRSN ratio.

(Worse) Optimization of multi-response problems in the Taguchi method is achieved in this work by the procedure proposed herein.

(Better) This work proposes a procedure to optimize multi-response problems in the Taguchi method.

To increase word variety in a sentence, presents and occasionally describes can be used instead of always saying proposes when the Chinese meaning is 提出 .

(Worse) Dissemination of imprecise information can not be effectively done by conventional MADM methods.

(Better) The classical MADM methods can not effectively disseminate imprecise information.

Depending on the sentence‘s context,precise/imprecise and accurate/ inaccurate can be used as alternatives to correct/incorrect when the Chinese meaning is 正確 / 不正確

(Worse) Constraints on fuzzy MAD M approaches are imposed by cumbersome computation.

(Better) Cumbersome computation constrains fuzzy MADM approaches.

To increase word variety in a sentence, cumbersome and complex can be used as alternatives to complicated when the Chinese meaning is 複雜 .

(Worse) Conversion of fuzzy data into crisp scores is achieved in the first phase.

(Better) The first phase converts fuzzy data into crisp scores.

(Worse) The fact that the attributes must be numerical and comparable is stipulated by TOPSIS.

(Better) TOPSIS stipulates that the attributes must be numerical and comparable.

(Worse) The relative closeness computed in TOPSIS can be used as a performance assessment of multi-response problems in the Taguchi method.

(Better) The relative closeness computed in TOPSIS can assess the performance of multi-response problems in the Taguchi method.

(Worse) Measurement of each response must be carefully made by the standard.

(Better) The standard must carefully measure each response.

(Worse) Systematic optimization of the scheme is the focus of this section.

(Better) This section focuses on systematically optimizing the scheme

(Worse) Determination from the experience of an engineer shows how pressure is affected by time.

(Better) An engineer's experience determines how time affects pressure.

(Worse) Further analysis of the facility is necessary for the practitioner to make an adjustment of the parameter settings.

(Better) The practitioner must further analyze the facility to adjust the parameter settings.

(Worse) Minimization of A and B levels can be achieved by setting factors A and B at A2 .

(Better) Setting factors A and B at A2 can minimize A and B levels.