The Application of Fuzzy Comprehensive Evaluation on Special Equipment Risk Assessment Yuan-rong Zhang 1, Jian Zhang 2, Yu-dong Li3 Chao Ji4 1, Fujian Special Equipment Inspection and Research Institute, Fuzhou 350008, China Fujian Special Equipment Inspection and Research Institute, Fuzhou 350008, China 3, Business School, Sichuan University, Chengdu 610065, China 4, Business School, Sichuan University, Chengdu 610065, China ([email protected], [email protected], [email protected],[email protected]) 2, Abstract – This paper uses fuzzy comprehensive evaluation method to assess the safety level of special equipments. An assessment model that examines quantity and quality factors was presented. The proposed model has two dimensions, the possibility and severity of accidents. The possibility of accidents was evaluated by dimensions of people, equipment, management and environment. Emergency response was concerned in judging the severity of accidents. Indicators of the assessment model were established based on expert opinions collected via questionnaires. Analytic Hierarchy Process was utilized to calculate the weights of indicators in each layer to construct the assessment model. Finally, the fuzzy comprehensive evaluation method was used to assess the safety level of a portal crane in the case company. Keywords - Risk assessment, Special Equipment, Fuzzy comprehensive evaluation. I. INTRODUCTION China has categorized boiler, pressure vessels (including cylinders), pressure pipelines, elevators, chain blocks, motor vehicles in plant, passenger transport telphers and large amusement facilities as special equipments . Special equipments were widely used in various areas of national economy and people’s daily life. Once accident occurred with special equipments, significant loss and serious adverse social impact will happen. Take the year of 2011 for sample, according to the statistics, there are 296 cases of accidents related to special equipments occurred in China. These accidents caused direct losses of 66.81 million Yuan, with 310 people killed and 247 people injured. Safety assessment can get comprehensive information referring to safety statue and risk level of special equipments in service. It is useful both for enterprises’ risk management improvements and safety supervision institutions’ risk control . In the recent 10 years, risk based inspection (RBI) has been widely used overseas to assess the risk of pressure vessels . RBI is a method for using risk as a basis to prioritize and manage the efforts of an inspection program . But the bases for safety management on special equipments in China are still experiences and laws . II. CONSTRUCTION OF SPECIAL EQUIPMENT RISK ASSESSMENT MODEL A. Constructing the Index System According to the characteristics of risk and examining domestic and international literature, this study uses the two dimensions, the possibility and severity of accidents, to classify the risk level. The present safety management of special equipments are mainly depended on the inspection to equipments. Factors of people, management and environment are usually not concerned. Statics shows that most accidents are related to people directly or indirectly . This study developed a systematic hierarchy index system by examining domestic and international literature    and conducting a questionnaire study. The index system was shown in Fig. 1. B. Establishment of assessment model Regarding the established index system, the weights of each layer should be calculated for a complete equipment risk assessment model. Analytic Hierarchy Process is a simple, flexible and practical multi-criteria decision making method presented by professor T. L. Saaty in the early 1970s. The basic steps of AHP in this study are as follow: Step 1: Define the problem and create hierarchical structure for every relevant factor by experts. Step 2: Design AHP questionnaires and distribute to respondents. Transform geometric means of questionnaires into the pairwise comparison matrix. Step 3: Calculate the weights of each layer and the consistency ratio (CR). The calculation results of each layer are shown as vectors, all the CR was less than 0.1. (a)Weights of the accident possibility indicators A1= （0.4668， 0.2776， 0.1603， 0.0953） B1= (0.0836,0.4443,0.4721) 0.3448， 0.1852， 0.0995 C1= 0.3705， Quality of security annex D13 Fatigue D2 Quality of equipment C4 Quality of safety protection devices D14 Work environment D3 Work satisfaction D4 Skills C2 Experience D5 Educational level D6 Quality of measuring control device D15 Materials quality D16 Technological level D17 Mainly confined to the force structure D18 Quality of system controlled electric power D19 Safety knowledge D7 Operating specifications D12 Equipment factors B2 Consciousness of Safety operation D11 Technique level C5 Quality of important parts D20 Hours worked D10 Work situation C3 Possibility of accidents A1 Personal factors B1 Physiological and psychological C1 Physiological healthy D1 Design level D21 Safety control technology D22 Type tests and examine D23 Equipment installation D24 of enterprise C7 Safety management Safety management system D33 Quality management of Equipment manufacturer D34 Security responsibility system D35 Equipment maintenance D26 Equipment modification D27 Years in service D28 Archives of security technology D29 Self inspection of Equipment safety D36 Complete degree of safety identification D30 Investment on enterprise safety management D37 Performance load D31 Operation environment C9 Corrective efforts of hidden danger D38 Comprehensiveness of safety monitoring D41 Timely manner of safety monitoring D42 Quality of safety monitoring D43 Operating site order D47 Operation space of equipment D48 Facility Layout D49 Material stocking D50 Humanity and natural C10 Scale of safety monitoring team D40 Environment factors B4 Safety education and training D39 Safety supervision C8 Management factors B3 Equipment reparation D25 Use of equipment C6 Personnel allocation of safety administration D32 Engineering level of examination D44 Engineering level of risk warning D45 Publicity efforts of safety knowledge and regulations D46 Natural environment of Equipment operation D51 Corrosion D52 Group safety awareness D53 Severity of accidents A2 Emergency response B6 Consequences B5 Energy conversion of Equipment operation C11 Population scale of accident influence C12 Possible casualties C13 Possible direct economic loss C14 Social influence C15 Effectiveness of emergency measures C16 Emergency response speed C17 Self-help ability of the crowd damaged C18 Fig. 1 Index system for special equipment 0.2017， 0.2454， 0.1019 C2= 0.3720， 0.1634， 0.2970 C3= 0.5396， 0.1634， 0.2970 B2= 0.5396， C4= 0.050， 0.039， 0.071， 0.077， 0.027， 0.027,0.172,0.337 0.3196， 0.1220 C5= 0.5584， C6= (0.2598,0.1602,0.2153,0.0818,0.0825,0.0508,0.0252,0.1245) 0.3333 B3= 0.6667， C7= 0.2022,0.2370,0.1763,0.1168,0.0627,0.0856,0.0422,0.0773 C8= 0.0504,0.2049,0.1751,0.1640,0.2437,0.0826,0.0793 0.2500 B4= 0.7500， C9= 0.1512,0.4098,0.3207,0.1183 (b) Weights of the accident severity indicators A2= 0.7500,0.2500 0.2483,0.4903,0.0966,0.1203 B5= 0.0445， 0.5396， 0.1634 B6= 0.2970， III. APPLYING OF THE MODEL A. Introduce of the Fuzzy Comprehensive Evaluation Method An actual decision making question is often influenced by many attributes or factors, people need to make a comprehensive evaluation by these attributes or factors. In most cases, these attributes or factors are fuzzy, to make comprehensive evaluation of these fuzzy factors is called fuzzy comprehensive evaluation . The basic procedures of multi-level fuzzy evaluation are as follows : ① Partition factor set of evaluation into several subsets according to certain criteria: s U ui i 1 ② Utilize single level fuzzy comprehensive evaluation for every ui Determine level set：V = v1 , v 2, ，v n ，n r22 rm 2 r 1 ir 1 should be determined before the evaluation. The single level evaluation result of ui is： Pui A R (b1 , b2 ,...,bn ) ③ Utilize single level fuzzy comprehensive evaluation for subsets Regard ui as a comprehensive factor，and use Pui to construct the evaluation matrix to calculate the final result. If the division in the first step ui（i=1,2,…，s）is still too much, it can be divided into 3 or more levels. The M10-30 type portal crane was made in May 1989 and was installed in 1990 in Quanzhou harbor. The original design for the biggest elevating capacity is 10 tons, and the hoisting extent maximum 30 m, minimum 8.5 m. At the beginning of putting into use in 1990, as port workload is not heavy, equipment utilization was not high; the load of door crane is small, and crane safe technology to little effect on performance. Since 1999, due to the rapid economy development in Quanzhou, equipment load and utilization has increased significantly. To meet the increasing production capacity requirements, the company entrusted Shanghai Donggang Machinery Corporation to modify the hoist boom in November 2001. Rated lifting weight was increased to 16 tons after the modification. After putting into use for 22 years, fatigue crack of metal structure and aging electrical system would probably be the hidden risk of accidents. C. Determination of Membership Functions As the index system includes both qualitative and quantitative indicators, the judgments were made by scoring the indicators from 1 to 100. In this study, the risk range was divided into five levels, which was shown in Tab. II. The original data was collected by questionnaires and geometric means of scores was calculated. represents the grade number of evaluation. Establish evaluation matrix r12 r pi B. Backgrounds of Case Portal Crane C10= 0.1059,0.5816,0.3090 C11= 0.7500,0.2500 r11 r 21 R= rm1 a Weight vectors Ai ai1 , ai 2 , , aipi , r1n r2 n rmn Data rij denotes the degree that factor i belongs to level j in the evaluation. It is usually calculated from the scoring of factors by a function. TABLE II RISK RANGE AND SET Evaluation set V Scores Good （ level 1 ） ≥90 Preferably （level 2 ） 80 General （level 3） Poorer (level 4) 70 60 Extremely poor （level 5 ） ≤50 According to the evaluation level given in Tab. II and experts’ opinions, the formulas of membership functions were presented below: 0 x＜80 0 ( x 80) / 10 1 Good: u（x）= Preferably: 0 u（x）= ( x 70) / 10 1 (90 x) / 10 0 General: 0 ( x 60) / 10 u（x）= 1 (80 x) / 10 0 Poorer: 0 u（x）= ( x 50) / 10 1 (70 x) / 10 0 80 x＜90 90 x 100 0 x＜70 70 x＜80 x 80 80＜x 90 90＜x 100 0 x＜60 60 x＜70 x 70 70＜x 80 80＜x 100 0 x＜50 50 x＜60 x 60 60＜x 70 70＜x 100 Extremely poor: 1 (60 x) / 10 0 u（x）= 0 x＜50 50 x＜60 60 x 100 We can get fuzzy judging analysis sets according to the formula Pui A R : PA1= 0.14 0.28 0.31 0.11 0.16 Taking the same procedure, the result of severity of accidents can be calculated: PA2= 0.14 0.18 0.37 0.31 0.00 E. Analysis results and recommendations In this study, risk matrix  was used for measuring overall risk level of special equipment. Hidden risks are divided into five levels, shown in Tab. III. Each level represents a corresponding implication, shown in Tab. IV. According to the evaluation results, levels of two dimensions were determined by maximum membership degree principle: ① PA1= 0.14 0.28 0.31 0.11 0.16 ，accident probability belongs to level 3. ② PA2= 0.14 0.18 0.37 0.31 0.00 ，severity of accidents belongs to level 3. According to TABLE III, the potential accident level of case portal crane is General hidden danger. As RA1 demonstrates, PB2= 0.10 0.10 0.22 0.10 0.48 , which means that equipment factors have a rather poor performance. Accidents are likely to occur due to equipment failure. The case crane requires improvement and continual attention to avoid further degeneration. TABLE III SAFETY LEVEL OF SPECIAL EQUIPMENT Severity of Accident D. Calculation of Fuzzy Evaluation Accident Take layer C1, the physiological and psychological factor for example, the fuzzy comprehensive evaluation matrix R1 was calculated by substitute into the membership functions: 0 0 0 0 1 0 1 0 0 R1= 0 1 0 0 0 0 0 0 1 0 0 and，WC1= 0.3705， 0.3448， 0.1852， 0.0995 We can get fuzzy judging analysis sets according to the formula Pui A R : PC1= 0.5626， 0.4374， 0， 0,0 Other fuzzy judgment analysis sets was calculated as same. Regard Bi as a comprehensive factor ， and use PBi,i=1,2,3,4 to construct the evaluation matrix of possibility of accidents RAi: PB1 0.12 0.47 0.29 0.13 0.00 PB 2 0.10 0.10 0.22 0.10 0.48 R A1 = P 0.28 0.25 0.30 0.09 0.08 B3 P 0.12 0.00 0.66 0.08 0.15 （B 4 and, WA1= (0.4668,0.2776,0.1603,0.0953) Possibility Level 1 Level 2 Level 3 Level 4 Level 1 Level 2 Level 3 Level 4 Level 5 Safety Slight Slight General Slight Slight Slight General General Serious Slight Slight General General Serious Serious Super-serious General General General Serious Serious Super-serious Super-serious General Level 5 TABLE IV EVALUATION RISK LEVELS AND CORRESPONDING IMPLICATIONS Risk levels Safety Slight General Serious Super-serious Execution outcomes and implications Excellent performance for equipment safety Failure may occur, requiring continual attention Accidents are likely to occur, requiring improvement and continual attention to avoid further degeneration Safety statue of equipment is poor and accidents are very likely to occur, requiring immediate rectification and improvement with execution feedback Serious accident will occur if emergency measures not be implemented immediately, and equipment should not put into use until hidden risk has been eliminated. IV. DISCUSSION Although the fuzzy evaluation scores was given by relevant experts in this study, the subjectivity of people is still a remarkable question. More objective risk assessment results should be obtained by the analysis of statistical data base. A further research on scoring mechanism should be implemented. What’s more, it is impractical to assure all the evaluators have a good knowledge of math. Thus, professional software should be developed to promote the use of the proposed evaluation method in this study. V. CONCLUSION This article used the fuzzy comprehensive evaluation method to assess the risk level of special equipments. A systematic index system was developed based on literature and experts’ knowledge. Risk level was determined based on risk matrix and opinions from experts in relevant fields. 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