**3. Case Design**

The objective of this study is to build an evaluation index for the design of a pillbox for patients with chronic diseases. The first step is to classify and determine the items to be scored for product design. In order to identify the relevance of the preliminary evaluation indices, semi-structured interviews were conducted. The researchers surveyed professionals in related fields for their opinions, aiming at collecting an organized evaluation indicator based on their capacity to make professional judgments, assessing the importance of each question, and applying corrections or supplements to these evaluation indices. In addition to the drafted evaluation indices, the interview contents and questions were prepared so that the interviewees were asked questions such as "Any other factors to be included as the evaluation indices?" and "What are the criteria for a pillbox for patients with chronic diseases?". The interview procedure included preparing for the interview, drafting interview contents and an outline, determining the interviewees, questioning and making records, ending the interview, and collecting and analyzing the data. After interviewing the experts, the appraisal process for a pillbox for patients with chronic diseases could be determined. In addition, assessing the professional literacy of the interviewees, the conditions of the pillbox are among the critical factors during the evaluation process. Therefore, the evaluation indices can be determined, and include the first level, i.e., the goal level, which is the eventual goal of appraising product designs. The second level is the objective level, which includes five constituent elements: functionality, structure, aesthetics, creativeness, and economy. The third level covers 19 evaluation criteria. In order to carry out systematic evaluation and analysis, the evaluation factors and constituent elements were chosen to build the hierarchical structure, as shown in Figure 1. Since numerous factors could affect the selection of interviewees, quantification of the degree of influence of each factor had to be carried out. After that, the degrees of influence of various factors were combined and calculated by utilizing a systematic approach in order to obtain quantization results. The definitions of the assessment items are as follows.

**Figure 1.** Hierarchical framework of evaluation indices of a pillbox for patients with chronic diseases.

First, the functionality part indicates the functionality of the pillbox for patients with chronic diseases. It covers two criteria, a product's "convenience" and its "unified pattern and function." Structure comprises "simplicity, "practicability,", "lightweight and portable," and "easy to store." Aesthetics comprises "product texture," "color," "shape variation," and "streamlined." Creativeness comprises "innovation," "uniqueness," "avant-garde," and "personal style." Economy comprises "product material," "assembly approach," "cost estimation," "spatial arrangement," and "simplicity."

In addition, the interviewees were mainly experts who could provide answers to the questions. Through the investigation and questionnaire, the resulting data were processed by the quantization approach. A total of 24 experts participated in this study, including 14 who run a business in an industry related to the pillbox and 10 workers in this industry. The information on their backgrounds is shown in Table 1. The participants were asked to consider the evaluation factors of the design of a pillbox for patients with chronic diseases. Answers, including the implementation of the AHP method and the fuzzy comprehensive evaluation, were checked. The goal was to obtain objective results from the questionnaire survey. After the relative weight of each factor was obtained by the AHP method and the consistency examination was carried out, Model 4 of the fuzzy synthetic method was used to apply the evaluation indices to obtain the final evaluation results.

Fuzzy multicriteria decision-making was used in this study to determine the evaluation indices of a pillbox design for patients with chronic diseases. Based on the above-mentioned analysis and construction of the evaluation factors for the pillbox, a total of 5 constituent elements and 19 evaluation criteria were obtained. They were classified into upper-level and lower-level factors as follows:

Upper-level factors: *U* = {Functionality ( *U*1), Structure ( *U*2), Aesthetics ( *U*3), Creativity ( *U*4), Economy ( *U*5)}

Lower-level factors: *U*1 = {Convenience (*u*11), Unified pattern and function (*u*12)}

*U*2 = {Simplicity (*u*21), Practicability (*u*22), Lightweight and portable (*u*23), Easy to store (*u*24)}

*U*3 = {Product texture (*u*31), Color (*u*32), Shape variation (*u*33), Streamlined (*u*34)}

*U*4 = {Innovation (*u*41), Uniqueness (*u*42), Avant-garde (*u*43), Personal style (*u*44)}

*U*5 = {Product material (*u*51), Assembly approach (*u*52), Cost estimation (*u*53), Spatial arrangemen<sup>t</sup> (*u*54), Simplicity (*u*54)}

In order to reflect the importance of each factor, the AHP was implemented to obtain the relative weights determined by the experts in this study. The questionnaire contents included a letter of instruction, instructions for filling out the questionnaire and examples, the standards of the intensity of importance, the hierarchical framework of indices, explanations, and questions. The importance of two factors in each subsystem was compared. The evaluation scale basically can be divided into five levels: equally important, slightly important, considerably important, very important, and absolutely important. They were assigned weights of 1, 3, 5, 7, and 9. An additional four levels between these five levels were assigned weights of 2, 4, 6, and 8. Left-aligned scales indicated that the factors on the left were more important than the factors on the right. On the other hand, right-aligned scales indicated that the factors on the right were more important than the factors on the left. The experts were asked to tick adequate assessment items, and the results are shown in Tables 3 and 4.






**Table 4.** *Cont.*

In addition, it is known from the AHP method that when *C*.*R*. ≤ 0.1, it can be determined that the judgment matrix has satisfactory consistency. It also demonstrated that the weight distribution is reasonable, and the results are shown in Tables 3 and 4.

Based on the results in Tables 2 and 3 and from Equation (2), the weight set of each factor can be obtained as follows:


Moreover, the set of evaluation results obtained from the participants' judgment of the evaluation target can be classified into five levels: V = {completely agree, agree, neither agree nor disagree, disagree, completely disagree}. Based on the factor set and evaluation set, the questionnaire for comprehensive evaluation of the designs allowed experts to fill in their answers to evaluate each factor. After the researchers collected the questionnaires for further statistical analysis, the membership grade of the evaluation of each factor was determined in order to obtain their fuzzy evaluation matrices. The fuzzy set is summarized as follows:


*Appl. Sci.* **2019**, *9*, 4909

The fuzzy evaluation matrix can be obtained from the above-mentioned procedures. The comprehensive evaluation and operation were carried out by implementing Model 4 of the fuzzy synthetic method. This synthetic method only requires carrying out normalization of *wi*. Therefore, there is no need to normalize the results obtained from the fuzzy comprehensive evaluation. The operations are as follows for the low-level evaluation:

$$\begin{aligned} \text{Functionality factor: } \overline{B}\_{1} &= \overline{W}\_{1} \bullet \overline{R}\_{1} = \begin{bmatrix} 0.263 & 0.397 & 0.300 & 0.044 & 0.00 \end{bmatrix}. \\ \text{Strature factor: } \overline{B}\_{2} &= \overline{W}\_{2} \bullet \overline{R}\_{2} = \begin{bmatrix} 0.341 & 0.311 & 0.307 & 0.041 & 0.00 \end{bmatrix}. \\ \text{Assets factor: } \overline{B}\_{3} &= \overline{W}\_{3} \bullet \overline{R}\_{3} = \begin{bmatrix} 0.266 & 0.307 & 0.321 & 0.110 & 0.00 \end{bmatrix}. \\ \text{Creatity factor: } \overline{B}\_{4} &= \overline{W}\_{4} \bullet \overline{R}\_{4} = \begin{bmatrix} 0.248 & 0.419 & 0.227 & 0.045 & 0.107 \end{bmatrix}. \\ \text{Econemy factor: } \overline{B}\_{5} &= \overline{W}\_{5} \bullet \overline{R}\_{5} = \begin{bmatrix} 0.293 & 0.369 & 0.239 & 0.099 & 0.00 \end{bmatrix}. \end{aligned}$$

It is known from Table 2 that the weights of the high-level factors can be determined, and the high-level judgment matrix is as follows:

$$
\widetilde{R}^\* = \begin{bmatrix}
\underline{B}\_1 \\
\underline{B}\_2 \\
\overline{B}\_3 \\
\overline{B}\_4 \\
\overline{B}\_5
\end{bmatrix} = \begin{bmatrix}
0.263 & 0.397 & 0.300 & 0.044 & 0.00 \\
0.341 & 0.311 & 0.307 & 0.041 & 0.00 \\
0.266 & 0.307 & 0.321 & 0.110 & 0.00 \\
0.248 & 0.419 & 0.227 & 0.107 & 0.00 \\
0.293 & 0.369 & 0.239 & 0.099 & 0.00
\end{bmatrix}.
$$

Therefore, the result of the high-level fuzzy comprehensive evaluation is

 

$$
\overline{\mathcal{C}} = \overline{\mathcal{W}} \bullet \overline{\mathcal{R}}^\* = \begin{bmatrix} \ 0.288 & 0.346 & 0.289 & 0.080 & 0.00 \ \end{bmatrix}.
$$

As for the processing of evaluation indices, typical methods in common use are maximum degree of membership and weighted averaging. Weighted averaging can turn vague values into definite values. This is the so-called defuzzification effect. The purpose of defuzzification is to transform the final data or results with vague properties into definite values and data. If vague values are used in the operations, the result is also a vague value. Defuzzification of vague values must be done so that they can turn into definite values with their own representativeness for the benefit of follow-up comparison and ranking operations. Therefore, by calculating with the weighted-average method in this study, the concept of a hierarchy of values is applied to the results (Kuo and Chen, 2006). Assigning V = {completely agree, agree, neither agree nor disagree, disagree, completely disagree} = {1, 0.75, 0.50, 0.25, 0}, the researchers calculated defuzzified values of evaluation results D, shown in Tables 5 and 6.

**Table 5.** Degrees of conformity of various factors determined by interviewees.


**Table 6.** Degrees of conformity of index framework for evaluation by interviewees.


In this study, the evaluation of pillbox designs for patients with chronic diseases was carried out by the fuzzy theory. The research results are shown in Tables 5 and 6. The degrees of conformity of various factors determined by the interviewees are shown in Table 5. The degrees of conformity of the index framework for evaluation by the interviewees are shown in Table 6. If the principle of maximum membership serves for the processing of evaluation indices, for the Structure factor, the evaluation items include "simplicity" (*u*21), "practicability" (*u*22), "lightweight and portable" (*u*23), and "easy to store" (*u*24). The evaluation result indicates that using the factors as constituent elements of the pillbox design is at the level

If the values obtained after defuzzification serve as evaluation indices for processing, it is known from the comprehensive evaluation that the result of the Functionality factor is 0.716, which indicates a level of "Completely agree" for the pillbox design, followed by Structure at 0.713, Aesthetics at 0.686, Creativity at 0.694, and Economy at 0.691. Since the design of a pillbox for patients with chronic diseases should follow regulated dimensions and patterns, according to the AHP, the factor weights are as shown in Tables 3 and 4. The weight of the Structure factor is 0.319, which corresponds to the ranking from the fuzzy comprehensive evaluation. However, the pairwise comparison matrix in the AHP has the problems of subjectivity, inaccuracy, and vagueness. In order to resolve this problem, the AHP approach must be extended to the vague environment in order to compensate for the deficiency of the vagueness problems that the AHP cannot resolve. After that, the fuzzy comprehensive evaluation is implemented to select the evaluation items in order to obtain their fuzzy values. Therefore, the result can be viewed as a dual verification, which indicates a certain degree of commonality between two factors in order to enhance the accuracy of the research. Moreover, the resulting values in Table 5 indicate that the overall index of the evaluation of the pillbox design is 0.723, which is between the levels "Completely agree" and "Agree." This indicates that the framework of the evaluation indices is acceptable. The result serves as a good reference for the process of designing a pillbox for patients with chronic diseases, as shown in Figure 2.

**Figure 2.** Weight set of the lower factors of the trolley selection indicator.

#### *3.1. Design Case Comparison*

Finally, three pillbox designs with di fferent forms and styles are shown in Table 7. Case 1 presents a timed pillbox design as the main body and its contents show a simple and convenient design. This design provides a simple and convenient way of reminding users of the time and function of taking a pill. Case 2 presents a concept of a pillbox composed of a button-type storage compartment. This design is simple and easy to use. Case 3 features a rotating pillbox. The main idea is to implement a rotating shape in an attempt to increase the storage space. Each of these three designs has a di fferent style.

For the evaluation of the overall schemes, it is known from Figure 3 that the defuzzified values of Case 3 is 0.74, which is at the "Satisfied" level, followed by Case 1, which has a defuzzified value of 0.62, at the "Neither satisfied nor dissatisfied" level. Therefore, Case 1 is one the most favored by subjects who made the decision. This scheme is not only full of functionality and economical, but it also performs well considering the coordination between humans, machines, and the environment. The advantage of this scheme lies in its creativity and aesthetics. Follow-up studies are advised to highlight the consideration of aesthetics. The results also indicate that Case 2 is inferior in terms of aesthetics. On the other hand, the economic aspect of Case 1 should be further enhanced as well.


**Table 7.** Three types of new pillbox designs with di fferent shapes for patients with chronic diseases.

The pillbox design of Case 3 provides the function of a favorable performance design with portable pill cells. Since patients are not professional medical personnel (Figure 4), they might take the wrong medicine by mistake or by misunderstanding the information. In order to create an intelligent pillbox that can recognize prescriptions and scheduling, a new type of portable cell is created. It is similar to the design of hospital medicine bags that can prevent cross-contamination of di fferent medicines. Each cell is loaded with only one type of medicine and there is a barcode for the medicine information on the top. The information includes patient name, medicine name, and dose, as well as medication instructions. Based on doctors' prescriptions, pharmacists load the medicines into the portable cells and seal them for patients.

**Figure 3.** Subjects' satisfaction degree and defuzzification values for the three design cases. satisfaction degree value, the highest score of each program.

**Figure 4.** Pillbox control module mock-up.

In addition, the design of the pillbox control module is to house the portable medicine cells. The top cover is opened to display the barcodes of the cells so that patients can scan for prescriptions. Moreover, in order to effectively avoid medication errors, the pillbox control module is equipped with a mechanical device that includes an electronic lock, sensors, and LEDs for controlling and managing the cells. The functions of the control module include detecting whether the portable medicine cell is loaded and the top cover is sealed, locking the pillbox, and indicating medicine locations by LEDs, etc.
