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Nowadays industries have initiative to reduce a number of production injuries and accidents down to zero. This goal could be achieved only through the proactive identification of accident precursors – such as unsafe conditions (UC) and unsafe acts (UA), whose control could prevent occurrence of accidents. At the same time, smartphones (and mobile applications) are taking dominance over PCs, making mobile devices major interface for human interaction with the web. In this term, application of mobile devices in OSH remains to be more exploited and accepted. Takin into account these trends, the present study aims to propose a novel cloud-based mobile framework for the management of UC/UA reports. Compared to previous studies, we considered the recent trends of mobile, cloud and Safety 4.0 in more details – ending up with the solution that is the combo of JavaScript technologies. Additionally, we provided a publically available use case named the SafE-Tag. Particularly, the SafE-Tag was implemented using the React Native for mobile application, Node.js for web-services and Mongo.db NoSQL cloud database. Beside elaborated computational efficiency, these technologies were found as the most optimal in terms of the cost/complexity to develop and/or adapt in an arbitrary SME. It is concluded that the proposed framework brings benefits for both employees and employers through: (1) intuitive and user friendly identification of key safety performance indicators; (2) digitalization and improvement of safety reporting systems; (3) improvement of safety culture; (4) better understanding and measurement of worker’s contribution to safety; and (5) making the technology affordable.

The article deals with an innovative methodology for risk assessment concerning human, organizational and technical/technological (HOT) factors, based on fuzzy set theory. The aim of this paper is to propose user-friendly prognostic risk assessment tool (PgRA) by obtaining reliable results and supporting further decisions of the safety managers. The HOT factors are introduced with associated sub-factors. The user-friendly interface developed in Matlab environment provides multiple opportunities for further improvement. The settings presented in this article are strictly applied for, but not limited to manufacturing sector. Flexibility of the PgRA tool allows adjustments and customize model regarding the group of the companies. With introduction of fuzzy set theory in the risk assessment process, level of subjectivity is reduced to the minimum. Practical applications: Possibilities of the practical application are modeled to assist in decrease of identified risks during daily work. This is a useful visual management tool, helpful to all safety managers in planning workplace improvements. The safety managers are in position to predict risk level before the real measures are taken. They are able to show the possible realistic results and risk trend behaviour to their supervisor/director, without spending any financial resources.

Industrial working environment demonstrates important advances in terms of working conditions. Nevertheless, there are still present manual tasks with high frequency, namely, repetitive tasks. This kind of working tasks are among the most influential for workers’ psychological and myoskeletal health. The concern for the risk derived by the repetitive task is evident by the fact that there is a well-known technical standard dedicated to this named OCRA (Occupational Repetitive Action). The present study uses OCRA for categorizing the risk produced by a replicated real repetitive task in laboratory conditions, and then compares electrophysiological method for deeper investigating into workers’ psychophysiology. The study combines results from OCRA and Electrodermal Activity (EDA) and offers suggestions for work design experts to consider psychophysiological impact metrics derived from low risk repetitive tasks.

There is an obvious need to redefine approach to provide and develop human resources necessary for modern industrial systems and to find new models that will meet the demands of Lean philosophy and concepts of safety and ergonomics. The authors are suggesting Early Human Resources Management (EHRM) model, inspired by developed pillar structures of Lean based World Class Manufacturing (WCM) and Total Productive Maintenance (TPM) industrial systems and based on proactive approach referring to human resources. The EHRM model is designed through the integration of Early Management and Human Resources development concepts and uses the Vertical start-up (VSU) principle for a drastic reduction of time needed for reaching the full potential and achieving the desired level of knowledge and competencies of human resources in Lean industrial systems. Practical applications: EHRM contributes to reducing the gap between expected and real performances of human resources at an early stage of their professional careers and enables the effective and efficient transition from academic to industrial environment. At the same time, cooperation, communication and knowledge transfer between industry and universities are upgraded, development of educational curricula is facilitated and build around the applicative knowledge skills, and methods.

Since small and medium enterprises (SME) generate the most of gross domestic product and employment opportunities in developed countries, further progress of the Industry 4.0 strongly relies on the development of dedicated solutions for SMEs-specific problems. Dimensional inspection of extruded rubber profiles represents one such an open issue in the automotive industry, which currently requires a manual measurement and comparison of profiles' cross section with the corresponding technical drawings. Starting from the requirements acquired from the industry practice, this study proposes a novel solution that automates all steps during the inspection process allowing an operator to make the final decision with respect to his observations. The proposed workflow includes the following steps: 1) image acquisition, 2) system calibration, 3) profile segmentation, 4) landmark registration and 5) augmentation of the referent technical drawing over the acquired image. The overall solution was developed by using a single camera and dedicated algorithms for profile detection and augmentation of the referent technical drawing. The extensive validation showed that the solution increased operators' productivity and reliability by a considerable margin (~6%), while it remains affordable, user-friendly and generic.

In this article, a novel approach for assessment and ranking of maintenance process indicators as well as maintenance cost indicators and maintenance equipment indicators using the fuzzy sets approach and genetic algorithms is presented. Weight values of these indicators are defined using the experience of decision makers from analyzed small and medium enterprises (total number of 197 persons) and calculated using the fuzzy sets approach. In the second step, a model for ranking and optimization of maintenance performance indicators and small and medium enterprises by using genetic algorithm is presented. The presented approach enables multi-objective optimization of selected key performance indicators in the scope of optimization of maintenance performances. The value of optimization was tested on a group of small and medium enterprises which proved that improvement of maintenance performance could be more significant (or performed at the shorter period of time) if the specific key performance indicators were targeted for improvement. The presented solution could provide identification of strengths and weaknesses (comparing key performance indicators), learning from a leading organization (in prioritization of key performance indicator improvement) and improvement of maintenance performance.

The evaluation and ranking of resilience factors (RFs) in an uncertain environment has important implications for the management of any enterprise. Determining an improvement strategy of business process resilience is based on the obtained rank of RFs, and it presents a key success factor for an enterprise in dealing with crisis. The complexity and importance of the treated problem calls for analytic methods rather than intuitive decisions. The relative importance of business processes and the relative importance of RFs under each business process are stated by fuzzy pair-wise comparison matrices. The elements of these matrices are triangular fuzzy numbers (TFNs). The fuzzy Analytic Hierarchy Process (FAHP) is used for determination of relative weights of existing variables. The rank of RFs is obtained by using the extent fuzzy Technique for Order Preference by Similarity to Ideal Solution (FTOPSIS). The real life application on the selection of the management team shows the practical implications in the process industry.

Crucial part of the reduction and prevention of workplace injuries and maintaining occupational safety and health system takes risk assessment model, which appears as one of the most important. Frequent advances in all fields cause changes in risk assessment models in relation to the traditional approach. This article is focused on providing reliable assessment tool that will enable suitable and easy usage of methodology for risk evaluation in the workplaces in manufacturing small and medium enterprises. For that purpose, three groups of factors are introduced and their hierarchical structures are defined. Pre-defined linguistic expressions are used to describe relative importance of factors, sub-factors and values of sub-factors. Fuzzy set theory is used for modeling of existing uncertainties. The levels of identified risks are given by exact way, using fuzzy logic. The proposed model is tested with real-life data from manufacturing small and medium enterprises.

This paper presents recent updates of performed and undergoing ergonomic studies inspired by observed and analyzed industrial case studies. Ergonomic problems and issues from two workplaces at automotive industry were identified and analyzed through their replication in laboratory conditions and implementation of multimodal approach for using of selected neuroergonomic, psychophysiology and Human–Computer Interface (HCI) tools and methods. Initial results shows significant potential for real-time and continuous monitoring and assessment of various parameters that could serve as objective identifications of operators' mental and physical load in operational environment.

This paper is focused on the problem of compliance of interface between clamping/locating fixture elements and workpiece, under dynamic loads during machining. In contrast to previous investigations, the authors have developed a special device dedicated to testing of physical models which represent clamping/locating elements and workpiece. This device allows optimization of a large number of input parameters which are critical to interface compliance. It was used in experimental investigations to establish the impact that the radius of the spherical tip of a clamping/locating element has on the interface compliance and load capacity. The results of experimental investigation show that, under certain conditions, the clamping/locating elements with larger-radius spherical tips provide significantly lower interface compliance. Future investigations should be aimed at finding optimum macro- and micro-geometries of contact interface, as well as the selection of materials for clamping/locating elements.

The problem of measuring static friction at high temperatures and low contact pressures is theo� retically analyzed, as well as the instruments for the accurate determination of the coefficient of static friction at high temperatures for contact pairs made of steel and bronze. The results of experimental investigation show that at low contact pressure and temperature above 120°C coefficient of static friction dramatically increases. This increase in the coefficient of friction can be of great practical value with regard to the load capacity of contacts where external forces are balanced with friction forces.

Serbia is aligning with European Union requirements and the occupational safety and health (OSH) administration is one of the most representative sectors of this alignment. Many efforts were made in this field, by introducing new laws and regulations, but it turned out to be insufficient. OSH professionals need to renovate and strengthen their knowledge in accordance with continuous, updated and improved OSH standards and regulation. Lifelong learning (LLL) programmes can contribute to forming professionals who are always up to date. This paper presents an implemented LLL programme, over the duration of two academic years, dedicated to OSH professionals, and investigates whether this programme will be helpful and accepted by professionals. The results from the study show that the given LLL programme had indeed a positive influence on the professional careers of the participants and that the LLL presents the future trend in OSH education.

Risk and safety management are very important issues in healthcare systems. Those are complex systems with many entities, hazards and uncertainties. In such an environment, it is very hard to introduce a system for evaluating and simulating significant hazards. In this paper, we analyzed different types of hazards in healthcare systems and we introduced a new fuzzy model for evaluating and ranking hazards. Finally, we presented a developed software solution, based on the suggested fuzzy model for evaluating and monitoring risk. risk assessment uncertainty fuzzy model software simulation occupational health and safety

Quality of Work Life (QWL) and Occupational Health and Safety (OHS) are two interconnected and important human needs. Modern industry shows a clear will for improving QWL and OHS, nevertheless, existent automatization and technological advances may negatively influence employees' wellbeing and result as triggers to their health deterioration. Subjective measures of employees workload can help, however, the lack of objectivity may be an issue. Improvement of working life needs objective measures. There is technology for measuring objectively employees' psychophysiology, but is considered to interfere with the flexibility needed for performing working tasks. Today electrophysiological methods require minimal dimensions, are wireless connected, allow movement and are proved to be useful in capturing psychophysical wellbeing. This study shows that the industry is ready to accept electrophysiological measures for monitoring and improving the employees' wellbeing.

Background Cervical dilation using mechanical dilators is associated with various complications, such as uterine perforation, cervical laceration, infections and intraperitoneal hemorrhage. To achieve safe and painless cervical dilation, we constructed a new medical device to achieve confident mechanical cervical dilation: a continuous controllable balloon dilator (CCBD). Methods Controlled pumping of incompressible fluid into the CCBD increases the pressure and outer diameter of the CCBD, continuously dilating the cervical canal. The reliability of the CCBD was confirmed in vitro (testing for consistency and endurance, with no detected risk for breakage) and in vivo. A multi-center clinical study was conducted,with 120 pregnant women randomly assigned to one of three groups: Group I,control group, no dilation;Group II,mechanical dilation, Hegar dilator (HeD); and Group III,CCBD. The tissue material for histological evaluation was obtained from the endocervical mucosa before and after dilation using the HeD or CCBD. Results The CCBD dilations were successful and had no complications in all 40 patients of Group III. The cervical tissue was markedly less damaged after CCBD dilation compared with HeD dilation (epithelium damage: 95% (HeD) vs. 45% (CCBD), P P P Conclusions The CCBD should be used as a replacement for mechanical dilators to prevent uterine and cervical injury during cervical dilation. Trial registration ISRCTN54007498