The application of Fuzzy Delphi Method and Fuzzy

Expert Systems with Applications 37 (2010) 419–425

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Expert Systems with Applications journal homepage: www.elsevier.com/locate/eswa

The application of Fuzzy Delphi Method and Fuzzy AHP in lubricant regenerative technology selection Yu-Lung Hsu a,*, Cheng-Haw Lee a, V.B. Kreng b a b

Department of Resources Engineering, National Cheng Kung University, No. 1, University Road, Tainan 701, Taiwan Department of Industrial and Information Management, National Cheng Kung University, No. 1, University Road, Tainan 701, Taiwan

a r t i c l e

i n f o

Keywords: Lubricant regenerative technology Fuzzy Delphi Method Fuzzy Analytic Hierarchy Process

a b s t r a c t Due to the funding scale and complexity of lubricant regenerative technology, the selection of recycling technology and policy for waste lubricant oil can be viewed as a multiple-attribute decision process that is normally made by a review committee with experts from academia, industry, and the government. This study aims to provide a systematic approach towards the technology selection, in which two phase procedures are proposed. The first stage utilizes Fuzzy Delphi Method to obtain the critical factors of the regenerative technologies by interviewing the foregoing experts. In the second stage, Fuzzy Analytic Hierarchy Process is applied to find the importance degree of each criterion as the measurable indices of the regenerative technologies. This study considers eight kinds of regenerative technologies which have already been widely used, and establishes a ranking model that provides decision makers to assessing the prior order of regenerative technologies. The empirical study indicates that the ‘‘Proper scale” is the most important evaluation criterion considered in overall experts. The demonstration of how the prior order of regenerative technologies changes under various domains of experts is addressed as well. Ó 2009 Published by Elsevier Ltd.

1. Introduction The efficient recycling of waste lubricant could help reduce both the environmental pollution and gas emission from greenhouses, thus, creating a huge efficiency either from environmentallyfriendly or economic levels. Waste lubricant recycling and regeneration not only save the cost of lubricant, but also contribute to environmental protection. The proper management of dispose and recycling of the waste oil becomes critical to the management of environment (Cheng, Lin, Chang, & Huang, 2006/1). Regenerating waste oil into chemical feedstock or fuel oil is one of the preferred recycle methods. At present, there are eight kinds of common lubricant recycling technologies as follows: (1) acid/clay process; (2) distillation process; (3) solvent de-asphalting process; (4) TFE + hydro-finishing; (5) TFE + clay finishing; (6) TFE + solvent finishing; (7) solvent extraction hydro-finishing and (8) TDA + clay finishing and TDA + hydro-finishing. These technologies are different in economic benefit, technology maturity and environmental impact, and new technologies have been developed and applied continuously. The government shall be responsible for technology assessment, and combine the views of academia, industrial circles and government * Corresponding author. E-mail addresses: [email protected] (Y.-L. Hsu), [email protected] (V.B. Kreng). 0957-4174/$ - see front matter Ó 2009 Published by Elsevier Ltd. doi:10.1016/j.eswa.2009.05.068

sectors to set up a measuring index for selection of lubricant recycling technology. The traditional Delphi Method, developed by Dalkey and Helmer (1963), has been widely used to obtain a consistent flow of answers through the results of questionnaires (Hwang & Lin, 1987; Reza & Vassilis, 1988). Delphi is an expert opinion survey method with three features: anonymous response, iteration and controlled feedback and finally statistical group response. However, some weaknesses have been exposed, it needs repetitive surveys to allow forecasting values to converge which requires much more time and cost (Hwang & Lin, 1987; Ishikawa et al., 1993). Furthermore, in many real situations, experts’ judgments can not be properly reflected in quantitative terms. Some ambiguity will result due to the differences in the meanings and interpretations of the expert’s opinions. Since people use linguistic terms, such as ‘good’ or ‘very good’ to reflect their preferences, the concept of combining fuzzy set theory and Delphi was proposed by Murray, Pipino, and Gigch (1985), and named the Fuzzy Delphi Method (FDM). Lubricant regenerative technology selection is a multiple criteria decision-making problem. Among these, the Fuzzy Analytic Hierarchy Process (FAHP) is one of the most popular (Kahraman, Cebeci, & Ruan, 2004; Teng & Tzeng, 1996; Zhau & Goving, 1991). People often use knowledge that is imprecise rather than precise. The fuzzy set theory approaches could resemble human reasoning in use of approximate information and uncertainty to generate decisions. It was specifically designed to mathematically

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represent uncertainty and vagueness and provide formalized tools for dealing with the imprecision intrinsic to many problems (Kahraman et al., 2004; Williams, 2003; Zadeh, 1965). Consequently, to make this study more sensible and gain a more representative description of the decision-making process, this study would apply the FAHP to investigate which evaluation criterion is the most important in overall technical committees. This study contains two stages: the first stage is to establish the key factors for evaluation of the waste lubricant recycling technologies, and use FDM by consulting experts of academia, industries and government sectors to select a technological selection criterion, in order to find out the important factors to be considered while selecting a technology; the second stage is based on FAHP, and consults experts of various fields to find out the importance of various criteria, in order to obtain the measuring index for selecting lubricant recycling technology.

2. Methodology 2.1. Fuzzy Delphi Method Fuzzy Delphi Method was proposed by Ishikawa et al. (1993), and it was derived from the traditional Delphi technique and fuzzy set theory. Noorderhaben (1995) indicated that applying the Fuzzy Delphi Method to group decision can solve the fuzziness of common understanding of expert opinions. As for the selection of fuzzy membership functions, previous researches were usually based on triangular fuzzy number, trapezoidal fuzzy number and Gaussian fuzzy number. This study applied the triangular membership functions and the fuzzy theory to solving the group decision. This study used FDM for the screening of alternate factors of the first stage. The fuzziness of common understanding of experts could be solved by using the fuzzy theory, and evaluated on a more flexible scale. The efficiency and quality of questionnaires could be improved. Thus, more objective evaluation factors could be screened through the statistical results. The FDM steps are as follows: 1. Collect opinions of decision group: Find the evaluation score of each alternate factor’s significance given by each expert by using linguistic variables in questionnaires. 2. Set up triangular fuzzy numbers: Calculate the evaluation value of triangular fuzzy number of each alternate factor given by experts, find out the significance triangular fuzzy number of the alternate factor. This study used the geometric mean model of mean general model proposed by Klir and Yuan (1995) for FDM to find out the common understanding of group decision. The computing formula is illustrated as follows: Assuming the evaluation value of the significance of No. j fij ¼ ðaij ; bij ; cij Þ; element given by No. i expert of n experts is w fj of i ¼ 1; 2; . . . ; n; j ¼ 1; 2; . . . ; m. Then the fuzzy weighting w fj ¼ ðaj ; bj ; cj Þ; j ¼ 1; 2; . . . ; m.Among which No. j element is w

aj ¼ Minfaij g; i

bj ¼

n 1X bij ; n i¼1

Schematic diagram of Fuzzy Delphi Method threshold is shown in Fig. 1. 2.2. Fuzzy Analytic Hierarchy Process Laarhoven and Pedrycz (1983) proposed the Fuzzy Analytic Hierarchy Process in 1983, which was an application of the combination of Analytic Hierarchy Process (AHP) and Fuzzy Theory. The linguistic scale of traditional AHP method could express the fuzzy uncertainty when a decision maker is making a decision. Therefore, FAHP converts the opinions of experts from previous definite values to fuzzy numbers and membership functions, presents triangular fuzzy numbers in paired comparison of matrices to develop FAHP, thus the opinions of experts approach human thinking model, so as to achieve more reasonable evaluation criteria. As for the experts’ opinions, this study adopted the Similarity Aggregation Method (SAM) proposed by Hsu and Chen (1996) to integrate experts’ weight values for various evaluation criteria, the fuzzy weight fraction of criterion of each hierarchy is obtained through the calculating mode of FAHP, and then the sequence of significance of each criterion is determined based on the hierarchy series connection and defuzzification mode. Laarhoven and Pedrycz (1983) proposed the FAHP, which is to show that many concepts in the real world have fuzziness. Therefore, the opinions of decision makers are converted from previous definite values to fuzzy numbers and membership numbers in FAHP, so as to present in FAHP matrix. The steps of this study based on FAHP method are as follows: 1. Determine problems: Determine the current decision problems to be solved, so as to ensure future analyses correct, this study discussed the ‘‘evaluation criteria for verification of credit card”. 2. Set up hierarchy architecture: Determine the evaluation criteria having indexes to be the criteria layer of FAHP, for the selection of evaluation criteria, relevant criteria and feasible schemes can be found out through reading literatures and collective discussions. This study screened the important factors conforming to target problems through FDM investigating experts’ opinions, to set up the hierarchy architecture. 3. Set up fuzzy paired comparison matrices: Compare the relative importance between factors given by decision makers in pairs, set up paired comparison matrices, after the definite values are converted to fuzzy numbers according to the definitions in Table 1 and Fig. 2, integrate the fuzzy evaluation values of experts based on the SAM concept proposed by Hsu and Chen (1996). 4. Calculate fuzzy weight value: Obtain the characteristic vector value of fuzzy matrix, namely the weight value of element. This

cj ¼ Maxfcij g i

3. Defuzzification: Use simple center of gravity method to defuzzify fj of each alternate element to definite value the fuzzy weight w Sj , the followings are obtained:

Sj ¼

aj þ bj þ cj ; 3

j ¼ 1; 2; . . . ; m

4. Screen evaluation indexes: Finally proper factors can be screened out from numerous factors by setting the threshold a. The principle of screening is as follows: If Sj P a, then No. j factor is the evaluation index. If Sj < a, then delete No. j factor.

Fig. 1. Schematic diagram of Fuzzy Delphi Method threshold.

Y.-L. Hsu et al. / Expert Systems with Applications 37 (2010) 419–425 Table 1 The definition of every fuzzy number. Fuzzy number

Definition

~ ¼ ð1; 1; 1Þ 1 ~ ¼ ð1; 2; 3Þ 2 ~ ¼ ð2; 3; 4Þ 3 ~ ¼ ð3; 4; 5Þ 4 ~ ¼ ð4; 5; 6Þ 5 ~ ¼ ð5; 6; 7Þ 6 ~ ¼ ð6; 7; 8Þ 7 ~ ¼ ð7; 8; 9Þ 8 ~ ¼ ð8; 9; 9Þ 9

Equally important Judgment values between equally and moderately Moderately more important Judgment values between moderately and strongly Strongly more important Judgment values between strongly and very strongly Very strongly more important Judgment values between very strongly and extremely Extremely more important

Fig. 2. Scale of fuzzy numbers.

study calculated these three positive and negative value matrices respectively by using the ‘‘Column Vector Geometric Mean Method” proposed by Buckley.

Z i ¼ ðai1  ai2      ain Þ1=n

8i

W i ¼ Z i ;ðZ 1  Z 2      Z n Þ Among which aij : Column i row j of matrix, i; j ¼ 1; 2; . . . ; n; Z i : column vector mean value of fuzzy number, i ¼ 1; 2; . . . ; n; W i : weight of No. i factor. : multiply fuzzy numbers, e.g. assuming two triangular fuzzy e ¼ ða1 ; b1 ; c1 Þ; B e ¼ ða2 ; b2 ; c2 Þ, numbers A

eB e ¼ ða1 ; b1 ; c1 Þ  ða2 ; b2 ; c2 Þ ¼ ða1  a2 ; b1  b2 ; c1  c2 Þ: A ;: divide fuzzy numbers, e.g.: assuming two triangular fuzzy e ¼ ða1 ; b1 ; c1 Þ; B e ¼ ða2 ; b2 ; c2 Þ, numbers A

e B e ¼ ða1 ; b1 ; c1 Þ;ða2 ; b2 ; c2 Þ ¼ ða1 =a2 ; b1 =b2 ; c1 =c2 Þ: A; 5. Hierarchy series connection: Connect all hierarchies in series, to obtain all factors’ weights. 6. Defuzzification: Convert fuzzy numbers to easy-comprehended definite values, this study adopts the center of gravity method to solve fuzzy numbers.

GðAÞ ¼

Pn i¼1 uA ðxi Þ  xi P n i¼1 uA ðxi Þ

7. Sequencing: Sequence defuzzified criteria. 3. Lubricant regenerative technology selection in Taiwan: a background The sales volume in the Taiwan lubricant market was registered separately as 400,000 kl and 450,000 kl in 2004 and 2005, and the

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generation rate of vehicle waste lubricant and industrial waste lubricant was 90.6% and 55.6%, respectively. According to the ‘‘Planning and Rate Calculation of Waste Lubricant Recovery” formulated by the Environmental Protection Agency (EPA) in 1999, vehicle lubricant accounted for about 59.7%, and industrial lubricant for 40.3% of the Taiwan lubricant market. It is thus estimated that the annual yield of vehicle lubricant was about 240,000 kl (45  59.7%  90.6% = 24.3), and of industrial lubricant about 100,000 kl (45  40.3%  55.6% = 10.0) in 2005. According to the investigation, most of the waste lubricants in Taiwan are recycled and reused as secondary oil and fuel (approx. 94%), but the remaining portion leads to environmental pollution (Table 2). The waste lubricant must meet environmentally-friendly and application criteria for recovery and reuse. Two key indicators include pollution level and viscosity index in this respect. In Europe, the regenerative oils are classified mainly according to the content of chlorides. Since chlorides are harmful to the human body, and complex finishing processes shall be required during the regeneration process, the chlorine content in reclaimed waste oil shall not exceed 50 ppm in EU regulations. A higher viscosity index of waste lubricant means a higher suitability for regeneration into lubricant. Viscosity is the most important consideration in choosing lubricants. The strength of the lubricant film is approximately proportional to its viscosity, so the higher viscosity indicates the stronger strength of the lubricant film. The viscosity index (VI) refers to the changing degree of viscosity dependent on temperature: the lower VI means a higher viscosity change in the case of slight temperature change, and vice versa. Thus, in the case of a higher viscosity index, no finishing process shall be additionally required to improve VI, making it more suitable for recovery and reuse with a relatively smaller operating cost. In 2005, there is approx. 340,000 kl of waste lubricant in Taiwan, so the recovery rate is about 4% if the audited statistical recovery yield of 14,000 kl in the same year is divided by 340,000 kl. As compared with European countries, it is found that Luxembourg had a recovery rate of 39%, and the average recovery rate of Europe was 50% back in 2000.

4. Evaluating model application and results 1. Reviewing relevant literature of lubricant regenerative technology and proposing important criteria: More than 17 criteria for lubricant regenerative technology based on reviewing relevant literature (Begum, Siwar, Pereira, & Jaafar, 2006; Emery, Davies, Griffiths, & Williams, 2007; Finnveden, 1999; International Maritime Organization, 2004; Lin, Lin, & Jong, 2007) and the current lubricant regenerative technology selection approach are proposed. Definitions of evaluating criteria of the lubricant regenerative technology selection are presented in Table 3. 2. Screen important criteria by Fuzzy Delphi Method: This stage includes three sections. Firstly, it lists three main aspects and 17 items as the key evaluation items of lubricant regenerative technology, and a FDM interview table is set up. The second section is the interview with nine experts from the academic community, lubricant oil producers and competent authority officers in Taiwan. Delphi Method mostly aims at easy common understanding of group opinions through twice provision of questionnaires. FDM formed by adding the fuzzy theory in, not only maintains the advantage of Delphi Method, but also reduces the provision times of questionnaires when using traditional Delphi Method as well as the cost. For the third section, the opinions of experts in FDM questionnaires

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Table 2 Distribution and hazards of waste lubricant in Taiwan. Distribution

Common purpose

Percentage

Hazards

Recycling dealer Factories Secondary lubricating in construction Random dumping

Secondary oil and fuel Furnace fuel De-molding

79.5 14 2.5 4

Inferior reclaimed oil, leading to mechanical damage Inclusive of heavy metal, improper incineration leading to serious pollution Pollution transfer Serious environmental pollution

Table 3 Operational type for defining criteria. Aspects

Criteria

The operating type defining

Technology

Operating temperature

During lubricant reclaiming steps, heating shall be used for separation, but different technologies will result in different operating temperatures How much lubricant oil can be extracted from each ton of waste lubricant oil is the calculation principle for recovery rate With reference to standard stipulated by API, there are five types Refers to on the aspect of application, whether this technology is only for experiments or available for industrial mass production Whether reuse products conform to quality and environmental laws of oil products or not

Recovery rate Product quality Development stage Legitimacy of reuse quality specifications Economy

Water cost Cost of overall demand for energy source Proper scale Cost of equipment demand Return on investment Subsidy

Environmental protection

Removal of PCB Whether generate acid sludge or not Whether there is residual oil sludge or not. Hazardous chemical substances used in process Depletion-of non-renewable resources IPCC-greenhouse effect

Take the water consumption in regenerating each ton of lubricant oil as the calculation unit, and compare with water rate to figure out water cost Take the energy source consumption in regenerating each ton of lubricant oil as the calculation unit (fuel oil, natural gas, etc.), and compare with energy source price to figure out energy source cost Take annual handling capacity (kt) as base. 2–10 kt/yr for small scale, 10–50 ht/yr for middle scale, 50 kt/yr above for large scale Whether this technical operation needs more equipments which are more precise Twenty year return on investment The government provides subsidies for waste lubricant oil processing Take 50 ppm as the dividing line, there are pcb residuals if the content exceeds 50 ppm The acid sludge means during operation, the mixed precipitate of waste acid and foreign matter derived from removing foreign matter by sulfuric acid Oil sludge is the asphaltic substances which cannot be fractionated at the end of lubricant oil reclaiming process Hazardous substances to environment or human body used in lubricant oil regenerating. Such as sulfuric acid or organic solvents Take the consumption of non-renewable resources in regenerating each ton of lubricant oil as the calculation unit How much greenhouse effect gas will be generated during regenerating each ton of lubricant oil

are converted to triangular fuzzy numbers, and defuzzified values can be figured out after calculation. This stage adopts elements with threshold above 7, and the key evaluation items with threshold below 7 are deleted. The important evaluation items after screening are listed in Table 4. 3. Establish a hierarchical framework: Based on the FDM, a general consensus among experts can be reached to establish a hierarchical structure. The lubricant regenerative technology can be evaluated based on three evaluation aspects and 17 evaluation criteria (Fig. 3).

4. Interview experts of all domains and integrate their opinions:Subject to who fill in AHP questionnaires possess sufficient professional knowledge, so the interviewees are experts from academia, lubricant producers and competent authority officers. The evaluation of each factor must go through consistency verification to ensure preferable credibility of results. In order to increase the objectivity of results, there are 17 experts to be interviewed. In the past, the integration of opinions from questionnaires mainly adopted geometric mean method, but the unreasonable integration of group opinions therein would

Table 4 Evaluation criteria after FDM screening. Aspects (code number)

Criteria (code number)

Score Min

Max

Average

De-fuzzy

Technology (A1)

Operating temperature (C1) Recovery rate (C2) Product quality (C3) Development stage (C4)

2 4 3 4

10 10 10 10

7.532 8.132 7.765 8.924

7.213 7.824 7.437 8.058

Economy (A2)

Water cost (C5) Cost of overall demand for energy source (C6) Proper scale (C7) Cost of equipment demand (C8)

1 4 4 3

10 10 10 10

7.454 8.688 8.951 7.623

7.127 7.953 8.462 7.145

Environmental protection (A3)

Removal of PCB (C9) Whether acid sludge is generated or not (C10) Whether there is residual oil sludge or not (C11) Hazardous chemical substances used in process (C12)

1 2 4 2

10 10 10 10

7.311 8.259 8.358 8.053

7.102 7.543 7.893 7.347

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Goal

Aspects

Criteria Operating temperature Recovery rate

Technology

Selection for lubricant regenerative technology

Product quality Development stage

Water cost Cost of overall demand for energy source Economy Proper scale Cost of equipment demand

PCB removal

Environmental protection

Acid sludge generated residual oil sludge Hazardous chemical substances used

Fig. 3. The hierarchy model of lubricant regenerative technology selection.

result in incorrect results. Therefore, this study adopts SAM which was proposed by Hsu and Chen (1996), which can integrate group opinions more reasonably, so as to increase the credibility of questionnaires. 5. Calculate the weights of evaluation criteria and weight result of evaluation criteria: The weight values of various elements can be obtained through the opinions of experts resulted from SAM and the FAHP systematic steps. After sequencing, the evaluation criteria have higher significance, so decision makers can make correct judgments more quickly. Table 5 is the evaluation criteria weight by FAHP, the evaluation criteria weight is obtained based on FAHP questionnaire results of experts, finally the questionnaire results of all experts are integrated to become the overall weight. As for different aspects, experts of various fields pay relatively consistent attention to the operation aspect (A1) and economy aspect (A2), they give quite high weight to these aspects, and the experts from industrial cir-

cles lay stress on the operation aspect in particular. However, the experts from various domains have different opinions on the environmental protection aspect (A3); those from academic community and government sectors think a lot of environmental protection aspect, while the experts from industrial circles think less of environmental protection. For the evaluation criteria contained in various aspects, the experts of various fields are consistent with them, only a few evaluation criteria have difference in opinions. For the operation aspect, the experts of various domains don’t have much difference in opinions, most of them lay stress on the evaluation criteria of ‘‘development stage” (C4); for the economy aspect, the experts of various domains have significant difference in ‘‘water cost” (C5), ‘‘cost of overall demand for energy source” (C6) and ‘‘equipment demand” (C8), among which, experts of industrial circles lay stress on ‘‘equipment demand” which is not stressed by the experts of other two domains, but the experts of industrial circles don’t lay stress on ‘‘cost of overall demand for energy source” which is stressed by the other two domains. The industrial circles and the government sectors have much difference in ‘‘water cost”; for the environmental protection aspect, the experts from various domains pay much attention to ‘‘acid sludge generated” (C10), but they have difference in three evaluation criteria such as ‘‘PCB removal” (C9), ‘‘residual oil sludge” (C11) and ‘‘hazardous chemical substances used” (C12), the opinions of experts from industrial circles are different from those of the experts from the other two domains. Fig. 4 shows the weights of lubricant regenerative technology hierarchy model. The maximum weight obtained by combining global priority is technology aspect (0.395) through FAHP, secondly is the economy aspect (0.358) and environmental protection aspect (0.247). As for sequencing the global priority of various evaluation criteria, the weight of the first four evaluation criteria exceeds 0.1, therein the ‘‘proper scale” (0.1292) in the economy aspect possesses the maximum weight, but the second and third evaluation criteria are on the technology aspect. These four evaluation criteria are paid much attention to in lubricant regenerative technology selection; the result demonstrates technology and economy aspects are main consideration in the evaluation process. 5. Conclusions This study investigates the key factors in lubricant regenerative technology selection by combining FDM, SAM and FAHP, and establishes objective and standardized references. A total of 17 factors influencing lubricant regenerative technology selection are analyzed through FDM experts’ opinions investigation, Experts of academia, lubricant oil industry and government sectors were interviewed, and 12 evaluation criteria were obtained as the key factors by interviewed bank experts. SAM and FAHP were used to

Table 5 Evaluation criteria weight of experts from different fields. Aspects

Weights of aspects

Criteria

Weights of criteria Academic community

Industrial circle

Government

Overall

0.395

C1 C2 C3 C4

0.135 0.282 0.274 0.309

0.092 0.308 0.312 0.288

0.091 0.294 0.279 0.336

0.105 0.295 0.284 0.316

0.322

0.358

C5 C6 C7 C8

0.143 0.238 0.377 0.242

0.105 0.192 0.360 0.343

0.215 0.283 0.301 0.201

0.153 0.234 0.361 0.252

0.357

0.247

C9 C10 C11 C12

0.253 0.294 0.128 0.325

0.125 0.399 0.235 0.241

0.261 0.280 0.144 0.315

0.195 0.351 0.168 0.286

Academic community

Industrial circle

Government

Overall

A1

0.354

0.432

0.321

A2

0.324

0.398

A3

0.322

0.170

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Goal

Aspects

Global Ranking priority

Criteria Operating temperature

11

Recovery rate

3

Product quality

4

Development stage

2

Water cost

9

Cost of overall demand for energy source

7

Proper scale

1

Cost of equipment demand

5

Technology

Selection for lubricant regenerative technology

Economy

10

PCB removal

Environmental protection

acid sludge generated

6 11

residual oil sludge Hazardous chemical substances used

8

Fig. 4. The weights of lubricant regenerative technology hierarchy model.

integrate experts’ opinions to obtain the significance evaluation of various evaluation criteria given by experts in group decision. The results from experts of different fields were compared and analyzed to show the similarities and differences of various experts in lubricant regenerative technology selection. Finally, the results of all experts were used as the evaluation index of lubricant regenerative technology selection. The following conclusions were reached by analyzing the evaluation criteria stressed by experts of various domains when evaluating the lubricant regenerative technology selection based on the demonstration of this study. 1. Experts of various domains lay different emphasis on three main aspects: The experts of academic community lay similar stress on three aspects; only the technology aspect has a slightly higher weight. This is probably because the experts of academic community include those of environmental industry, chemical industry, machinery, electric machinery and so on, therefore the three aspects have relatively mean score on weight; the industrial circles lay emphasis on the technology and economy aspects, the weight of environmental protection aspect is obviously low; the government sectors pay attention to the environmental protection aspect, since they care about whether lubricant regenerative technology will generate secondary pollution or not. Due to various domain experts give quite different weights to different aspects; it is necessary to collect all opinions of different domain experts in the course of lubricant regenerative technology selection, so as to make the evaluation more objective and feasible.

2. Experts of various fields pay quite different attention to evaluation criteria in environmental protection aspect: Although the environmental protection aspect has minimum weight, four evaluation criteria in it make experts from three domains have most difference in their opinions. Due to ‘‘PCB removal” and ‘‘hazardous chemical substances used”, these two evaluation criteria because more severe secondary pollution, they are stressed by experts of academic community and government sectors, but the industrial circles don’t. Therefore, the government legislates and sets a baffle plate for the evaluation criteria in environmental protection aspect, and eliminates heavy-pollution technical proposals in advance. 3. Technology aspect is mostly concerned: Due to many technical proposals are still in experimental development stage, or there are a few successful commercial operations, experts of various domains lay stress on the performance of technology aspect, among which, three evaluation criteria such as ‘‘development stage”, ‘‘recovery rate” and ‘‘product quality” rank the second to fourth place in the global priority sequence, its degree of importance is obvious. 4. Proper scale of technology is the most important evaluation criteria: There are quite much waste lubricant oil in Taiwan, however, too many demands of waste lubricant oil recovery processing cannot be satisfied yet, The waste lubricant oil recovery volume and the scale of potential competitors within the regional extent should be considered in the course of lubricant regenerative technology selection, therefore, it is very important to select ‘‘proper scale” technical proposal.

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