**5. Conclusion**

36 Fuzzy Inference System – Theory and Applications

As explained before, the risk assessment is based on attributes related with three categories of main factors (hazard, safety control factors and potentiating factors). Table 2 illustrates the main factors and examples of corresponding attributes for assessing the risk of "falls from height". For example, "Work at height" is the Hazard and "Height" is the attribute required for this analysis. The list of attributes is used during the data collection phase to ask for the relevant input data for the risk analysis. If the user doesn't provide data to some attribute the model considers that this attribute is in such a state that is not

Table 3 synthesizes the application of the RA\_X model. The collected input data is shown in

Data

Work at height Height 4 m 1 1

Individual Harness/Life line Inadequate 0.75 0.75 Collective Barrier Inexistent 1

floor/Tidiness Inadequate 0.75

power/heavy tools Very adequate 0

Safety behaviour Little adequate 0.5

Safety training Inadequate 0.75

Type of footwear Very adequate 0 0.83

Table 3. RA\_X application example in the assessment of the risk "falls from height" for an

In this case the Height was obtained by measurement and the other data are opinions. The fuzzification of the data was done using the membership function presented in Figure 4 for the Height, and the Linguistic Variable "inadequacy" (Figure 5) for the remaining subjective data (refer to subsection 3.2), and the results of the fuzzification process are presented in column "Fuzzy Attribute Value". The results of the partial fuzzy inference processes are shown in column "Aggregated Values" (refer to subsection 3.3). Finally, the fuzzy risk level and the corresponding crisp level, obtained by defuzzification (see Figure 6) are presented

In short, the risk assessment based on the RA\_X model is that there is a high risk of falls from height for an activity where the workers operate at a height of 4 m, the best protection

Factors Illumination Adequate 0.25 0.25

in column "Fuzzy Risk Level (Crisp Risk Level)" (refer to subsection 3.3.3).

Fuzzy Attribute Value

Aggregated Values

0.75

0.95

Fuzzy Risk Level (Crisp Risk Level)

0.72 (High)

contributing to the risk.

Attribute Raw

Type of

Use of

column "Raw Data".

**Hazard** 

**Safety Control** 

Work Activity

Environmental

activity of pouring concrete

Individual

**Potentiating Factors** 

Fuzzy Logics has been used to handle uncertainty in human-centred systems (e.g., ergonomics, safety, occupational stress) analysis, as a way to deal with complex, imprecise, uncertain and vague data.

This chapter presented the main features of the RA\_X FMADM model, which was developed to implement a fuzzy expert system for supporting risk management activities. In the current stage a prototype was implemented for test and validation purposes. The support of a proactive risk management is achieved by assessing potential factors that contribute for occupational accident occurrence and by guiding on the adoption of safety measures.

The RA\_X is meant to be a flexible and easy to use system, which can process both objective and subjective input data and provide risk assessment and advice for a broad variety of occupational activities. The results are offered using natural language. The system also provides means to perform trend analysis supporting the follow-up and monitoring of risks in work situations.

Following a quite simple Knowledge Engineering process, the Knowledge Base of the RA\_X expert system can be updated to incorporate new risks, broadening the scope of application, and can be customized to different national realities accommodating, for instance, to

Applications of Fuzzy Logic in Risk Assessment – The RA\_X Case 39

Harms-Ringdahl, L. (2001). Safety Analysis: Principles And Practice In Occupational Safety,

HSE (2008). Health and safety training. What you need to know (INDG345). Available at http://www.hse.gov.uk/pubns/indg345.pdf Health and Safety Executive.

http://www.hse.gov.uk/falls/heightaware/flashindex.htm. Health and Safety

Monteiro, T. (2006). Análise de Riscos na Construção Civil. Construção e Validação de Base

NASC (2008). SG4:05 Appendix A. Interim Guidance on Collective Fall Prevention Systems

http://v35.up1.universalpixel.com/ams/assets/NASC532147/SG4\_05%20Append

Nunes, I. L. (2005). Fuzzy Multicriteria Model for Ergonomic workplace analysis and Risk

Nunes, I. L. (2006b). Quantitative Method for Processing Objective Data from Posture

Nunes, I. L. (2007). Knowledge Acquisition for the Development of an Upper- Body Work-

Nunes, I. L. (2009). FAST ERGO\_X – a tool for ergonomic auditing and work-related

Nunes, I. L. (2010a). Handling Human-Centered Systems Uncertainty Using Fuzzy Logics –

Nunes, I. L. (2010b). Risk Analysis for Work Accidents based on a Fuzzy Logics Model. 5th

http://www.osha.gov/Publications/osha3146.pdf, U.S. Department of Labor.

http://63.234.227.130/SLTC/etools/construction/falls/mainpage.html (accessed

OSHA (2010b). Standard 1910.23: Guarding floor and wall openings and holes. http://www.osha.gov/pls/oshaweb/owadisp.show\_document?p\_table=STAND

analysis. Information Technology, Knowledge Management and Engineering for Enterprise Productivity and Quality of Working Life (International Conference: Computer-Aided Ergonomics and Safety - CAES'05), Kosice-Slovak Republic. Nunes, I. L. (2006a). ERGO\_X - The Model of a Fuzzy Expert System for Workstation

Ergonomic Analysis. International Encyclopedia of Ergonomics and Human

Analysis. International Encyclopedia of Ergonomics and Human Factors.

Related Musculoskeletal Disorders Analysis Tool. Human Factors and Ergonomics

musculoskeletal disorders prevention. WORK: A Journal of Prevention,

International Conference of Working on Safety - On the road to vision zero?, Roros.

in November 2010), U.S. Department of Labor. Occupational Safety and Health

de Conhecimento de um Sistema Pericial. Lisboa. Lisboa-Portugal.

in Scaffolding. National Access & Scaffolding Confederation.

NSW. 2011. "Six steps to Occupational Health and Safety. Available at http://www.une.edu.au/od/files/OHSSixsteps.pdf."

Factors. Karwowski, CRC Press: 3114-3121.

Assessment, & Rehabilitation 34(2): 133-148.

A Review. The Ergonomics Open Journal 3: 38-48.

OSHA (1998). OSHA 3146 (Revised): Fall Protection in Construction.

Occupational Safety and Health Administration.

Karwowski, CRC Press: 3306-3309.

in Manufacturing 17(2): 149-162.

Norway.

OSHA (2010a). OSHA Construction eTool.

Administration.

ix%20A\_web.pdf. National Access & Scaffolding Confederation.

Taylor & Francis.

Executive.

HSE (2010). Fallington (Interactive guide). Available at

different legal frameworks or level of action requirements, which affect the assessment process and/or the advice offered.

The advantages of this fuzzy system compared with traditional methodologies based on the estimation of two parameters (probability and severity) are obvious. First, the system is more thorough on the risk assessment, considering a wider range of factors, contributing to the implementation of a holistic approach to the assessment of risks, namely by including organizational and individual factors. Another important advantage is the fact that the methodology used allows the combination of objective and subjective data in a coherent way. Finally, it supports the full cycle of the risk management process (including hazard identification, risk assessment, advice on risk control and monitoring support), which is key for the promotion of safety and health at work.

The RA\_X system is ongoing tests and evaluations by experts that are representative of the expected typical users of this new approach.

A future step is the web implementation of the RA\_X system so that the most updated set of knowledge can be remotely accessed, which allows also exploiting the benefits offered by mobile devices, such as Tablets or iPads.

#### **6. References**


(http://osha.europa.eu/en/publications/reports/208).


 http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=CELEX:32001L0045: EN:HTML.


different legal frameworks or level of action requirements, which affect the assessment

The advantages of this fuzzy system compared with traditional methodologies based on the estimation of two parameters (probability and severity) are obvious. First, the system is more thorough on the risk assessment, considering a wider range of factors, contributing to the implementation of a holistic approach to the assessment of risks, namely by including organizational and individual factors. Another important advantage is the fact that the methodology used allows the combination of objective and subjective data in a coherent way. Finally, it supports the full cycle of the risk management process (including hazard identification, risk assessment, advice on risk control and monitoring support), which is key

The RA\_X system is ongoing tests and evaluations by experts that are representative of the

A future step is the web implementation of the RA\_X system so that the most updated set of knowledge can be remotely accessed, which allows also exploiting the benefits offered by

BSI (2005). BS 8437:2005. Code of practice for selection, use and maintenance of personal fall

BSI (2007). Occupational health and safety management systems – Requirements, BS OHSAS

CEN (2008). EN 363: Personal fall protection equipment. Personal fall protection systems.

EASHW (2002). New trends in accident prevention due to the changing world of work

EC (2009). Occupational Health and Safety Risks in the Healtcare Sector European

EU (2001). Directive 2001/45/EC of 27June 2001 concerning the minimum safety and health

http://eur-lex.europa.eu/LexUriServ/LexUriServ.do?uri=CELEX:32001L0045:

(http://epp.eurostat.ec.europa.eu/cache/ITY\_OFFPUB/KS-SF-09-063/EN/KS-SF-

Gupta, J. N. D., Forgionne, G. A.& M.T., M., Eds., 2006. Intelligent Decision-making Support

Commision http://www.eurogip.fr/docs/Commission\_europeenne\_guide\_

requirements for the use of work equipment by workers at work. Official Journal L

Systems: Foundations, Applications and Challenges (Decision Engineering),

protection systems and equipment for use in the workplace, British Standard

process and/or the advice offered.

for the promotion of safety and health at work.

expected typical users of this new approach.

mobile devices, such as Tablets or iPads.

18001: 2007, British Standard Institutions.

http://osha.europa.eu/en/statistics/index.stm .

secteur\_sante\_2009\_EN.pdf .

195 , 19/07/2001 P. 0046 - 0049

Eurostat (2009). Population and social conditions

European Committee for Standardization - CEN.

European Agency for Safety and Health at Work. (http://osha.europa.eu/en/publications/reports/208).

09-063-EN.PDF). Eurostat. Statistics in focus 63.

EASHW (2010). Statistics European Agency for Safety and Health at Work.

Institutions.

EN:HTML.

Springer.

**6. References** 


**3** 

*1UK 2Iran* 

**A Fuzzy Approach for Risk Analysis with** 

The Critical Path Method (CPM) and its development to probabilistic environment, the Program Evaluation and Review Technique (PERT), are the most common tools for predicting and managing different short time or long time projects. However, one of the main difficulties in using mathematical models in real world applications is the vagueness and uncertainty of data and parameters such as activity durations and risky conditions. The constructed network for project management (as a mathematical model) is an aid for control of project implementation with deterministic time durations. However, realization of this approach is difficult in the situation where most of activities will be executed for the first time. One solution offered for this difficulty is the assignment of probabilistic values for estimated durations of activities. In PERT, three estimations called pessimistic, most likely and optimistic values are assigned for each activity. Then the mean duration and its

> 4 6

6 *b a*

Where a, m and b are the optimistic, most likely and pessimistic values respectively. D is the expected (weighted mean) duration of activity and σ is the standard deviation of the three values (Kerzner, 2009). The project duration (sum of durations of critical path) is estimated by using the estimated durations of activities. Also, the probability of finishing the project before a predicted time (by using PERT) is calculated based on the standard deviations

**1. Introduction** 

and

standard deviation are calculated by

**Application in Project Management** 

*2Department of Industrial Management, Islamic Azad University,* 

Sina Khanmohammadi1 and Javad Jassbi2 *1Faculty of Science, Technology and Creative Arts,* 

*a mb <sup>D</sup>* (1)

(2)

*School of Engineering and Technology, University of Hertfordshire, Hertfordshire,* 

*Science and Research Branch, Tehran,* 

ARDS&p\_id=9715. U.S. Department of Labor. Occupational Safety and Health Administration.

OSHA (2010c). Standard 1926.501: Duty to have fall protection.

 http://63.234.227.130/pls/oshaweb/owadisp.show\_document?p\_table=STANDA RDS&p\_id=10757 (accessed in November 2010). U.S. Department of Labor. Occupational Safety and Health Administration.

