براورد یک مدل جدید ارزیابی ریسک برای شرکت های کوچک و متوسط

The identification, assessment and reduction of the risks is among of the most important issues of the safety at work. This paper’s goal is to demonstrate the effectiveness of a new risk assessment method proposed by the authors and presented in the past (Fera and Macchiaroli, 2009). In general, one can deal with risk assessment using different methods: quantitative, qualitative or a mix; however, the typical models proposed in the literature are difficult to implement in SMEs. The method proposed in this paper is a mixed one whose effectiveness is demonstrated through an application study carried out in different industrial systems, like a steel industry or a logistic services provider.

The injuries statistics (Table 1) released by the International Labour Organization (ILO) for 2007 are very significant.They show how health and safety problems are very far from being solved. It is well known that an effective approach to health and safety at work needs a suitable risk assessment phase, the adoption of prevention and protection actions and the implementation of a severe “safety audit” phase. However, less attention has been paid to these phases in the practice, using non-appropriate tools and methodologies which are either too complex to manage or too simple and subjective, thus not suitable to recognize hazards and reduce the corresponding risks. The aim of this paper is to assess the effectiveness of a new and reliable assessment model presented in Fera and Macchiaroli (2009), able to face the aforesaid applicability difficulties of the models developed so far and to show, through its application to several industrial plants, how an improvement in safety condition can actually be achieved. The proposed model is based on known techniques, such as Failure Modes and Effects Criticality Analysis (FMECA), Scenario Based Risk Assessment (SceBRA) and Italian standard UNI 7249:2007. These techniques are integrated within a procedure composed by seven steps, some quantitative and some qualitative. This model also includes the Analytic Hierarchy Process (AHP) decision making technique, which – as well known – is useful to minimize inconsistencies in experts’ judgments, within the subjective phases of risk assessment. The paper is organized as follows. After discussing the main features of relevant models presented in the literature and the open issues in risk assessment, Section 3 contains a brief overview of the AHP technique in order to underline its importance in the proposed model. Afterwards, the proposed model is described in detail, including a discussion about its main features and advantages. Before concluding, we also report the results from an experimental campaign carried in three manufacturing and services firms.

Starting from the awful statistics of the safety at work, as they result in the EU and worldwide, in this paper we analysed the state of the art in risk assessment methods applied in small and medium enterprises (SMEs) and we found a lack of models applying both quantitative and qualitative methods. So, the attempt was to develop a model able to reduce the uncertainty that subjective models typically offer and the computational complexity that objective and quantitative models normally include (with the related costs and time consumption), thus representing a method that, making use of the same amount of effort, is able to achieve better and more reliable results. The proposed model therefore merged known quantitative models, like the ones using frequency and consequence indexes, with typical subjective models, such as the AHP models. The proposed approach, through the use of AHP, allows to assess also risks related to aspects and dangers which have no history, and for which necessarily a subjective approach applies. The application of the proposed model has shown a good performance in terms of risk assessment “reliability”: by this we mean that the risk prioritization resulting from the proposed risk assessment model is better than the one resulting from traditional methods, when compared with statistic data from the specific firm, as retrieved from the injuries and accident register book, and with the national industrial sector, as retrieved from the national industrial sector statistic survey on injuries and accidents in the Italian firms performed by INAIL. Next steps in the research will deal with the validation of the method for the identification and prioritization of the improvement actions and the application and validation of the model in other industry sectors.