Browsing by Author "Macuzic, Ivan"

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A new fuzzy model for determining risk level on the workplaces in manufacturing small and medium enterprises
(2015) Djapan M.; Tadić, Danijela; Macuzic, Ivan; Dragojovic P.
© IMechE 2015. 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.
A new model for evaluation of safety grade of indicators based on a fuzzy logic
(2013) Djapan M.; Tadić, Danijela; Macuzic, Ivan; Jeremic B.; Giagloglou, Evanthia
Further researching and development in the field of health and safety at work should be looking beyond traditional principles, on a quite new, innovative and contemporary approach. Changing the approach is natural, obvious and necessary regarding frequent technology improvement on all fields, emerging industrial facilities, big social, economical and demographic changes, as well as changes of workforce that is constantly circulating with various different education, profiles, ages and gender. The necessity of frequent monitoring of the changes in a workplace comes in the foreground in order to identify all the changes that could be the potential safety problems. Every risk assessment is specific and needs to take into account a number of indicators which affect whole assessment process. Complexity of business/production systems and changing dynamics are at much higher and greater level, therefore dictate implementation of new models. Also, limits complying with the requirements of existing risk assessment models are significantly overstrained. By using multi-criteria analysis Analytical Hierarchy Process (AHP), the decision making process could be improved through determination of indicators priority. The contributions of this paper are as follows: it proposes fuzzy safety grades of all indicators and sub-indicators, it handles uncertainty, which is performed by using fuzzy sets and the given results can be used to analyze the safety grade of each indicator and sub-indicator over time. Copyright © 2013, AIDIC Servizi S.r.l.
A smart warehouse 4.0 approach for the pallet management using machine vision and Internet of things (IoT): A real industrial case study
(2021) Vukicevic A.; Mladineo, Marko; Banduka N.; Macuzic, Ivan
Printing companies are commonly SMEs with high flow of materials, which management could be significantly improved through the digitalization. In this study we propose a smart Warehouse 4.0 solution by using QR code, open-source software tools for machine vision and conventional surveillance equipment. Although there have been concerns regarding the usage of QR in logistics, it has shown to be suitable for the particular use-case as pallets are static in the inter-warehouse. The reliability of reading of QR codes was achieved by using multiple IP cameras, so that sub-optimal view angle or light reflection is compensated with alternative views. Since surveillance technology and machine vision are constantly evolving and becoming more affordable, we report that more attention needs to be invested into their adaptation to fit the needs and budgets of SMEs, which are the industrial cornerstone in the most developed countries. The demo of proposed solution is available on the public repository https://github.com/ArsoVukicevic/PalletManagement.
A tool for neuroergonomic study of repetitive operational tasks
(2014) Mijovic P.; Giagloglou, Evanthia; Todorovic, Petar; Macuzic, Ivan; Jeremic B.; Gligorijević I.
The objective of the present work in progress, in the field of neuroergonomics, is to find psychophysiological correlates for vigilance decrement and mental fatigue in industrial environments as well as the measurements of postural loads using multimodal system. This system is composed of (wirelessly obtained) electroencephalographic measurements (EEG), electrodermal activity (EDA) and commercial 3D motion capture sensor kinectTM. The aim of this study is to decrease potential operational error due to slips in attention and mental fatigue of a worker and consequently lead to more reliable and safer production. Further, postural loads could be assessed on-line, thus preventing the over-load of the workers and, consequently, possible work-related MSDs. Copyright is held by the author/owner(s).
A two step fuzzy model for the assessment and ranking of organizational resilience factors in the process industry
(2016) Macuzic, Ivan; Tadić, Danijela; Aleksic, Aleksandar; Stefanovic, Miladin
© 2015 Elsevier Ltd. 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.
An assessment of maintenance performance indicators using the fuzzy sets approach and genetic algorithms
(2017) Stefanovic, Miladin; Nestic, Snezana; Djordjevic, Aleksandar; Djurovic D.; Macuzic, Ivan; Tadić, Danijela; Gacic M.
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.
An implementation of infrared thermography in maintenance plans within a world class manufacturing strategy
(2013) Todorovic, Petar; Gordić, Dušan; Babic, Milun; Jeremic, Branislav; Demichela, Micaela; Macuzic, Ivan
The objective of the paper is to show the implementation of infrared thermography within world class manufacturing maintenance strategy. The results from infrared thermography inspections in a food processing and packaging solutions company were presented. Applicability ofthe infrared thermography, during a two-year period, caused a substantial reduction ofthe potential breakdown in the pilot area. Upon feasibility confirmation, the proposed method was spread to other production equipment ofthe company.
An innovative prognostic risk assessment tool for manufacturing sector based on the management of the human, organizational and technical/technological factors
(2019) Djapan M.; Macuzic, Ivan; Tadić, Danijela; Baldissone G.
© 2018 Elsevier Ltd 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.
Application of digital human models in determination of the pedal force while driving
(2019) Macuzic, Ivan; Lukić, Jovanka
© Published under licence by IOP Publishing Ltd. One of the most important tasks of the car manufacturer is the design of the interior space of the vehicle. Anthropometric characteristics of drivers are also important for designing cars. In this paper the determination of the pedal force has been performed. The force determination was made on digital human models for different populations, a total of 11 different populations of men and women. Analysing was done in the software package Ramsis and subjects were presented using mannequin. The obtained force values were different for different populations. The correlation between the anthropometric measures of the subjects and the force on the pedals was observed. By calculating Pearson R coefficient in both populations, female 5 % and male 95 %, it can be concluded that there is a good correlation between active foot pedal force and driver's height (R2 = 0.84 and R2 = 0.72, respectively). In the case of maximum values of passive forces R coefficient in both populations also have a good correlation between passive pedal force and driver's height (R2 = 0.89 for female 5% population and R2 = 0.69 for male 95 % population). The obtained results are important for designing the interior of the vehicle.
Applied neuroergonomic: Recent updates from automotive industry case studies
(2018) Macuzic, Ivan; Giagloglou, Evanthia; Zivanović-Macuzić I.; Jeremic B.
© 2018 Elsevier Inc. All rights reserved. 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.
Assessment of the Fragility of the Municipal Waste Sector in Serbia Using System Dynamics Modelling
(2022) Jovicic M.; Boškovič G.; Jovicic, Nemanja; Savković, Mile; Macuzic, Ivan; Stefanovic, Miladin; Klochkov, Yury
This research develops a novel methodology for municipal waste management in Ser-bia, based on system dynamics modelling. The methodology shows how a country and relevant institutions should address complexities in the waste management sector. Waste management is a critical issue globally, which heavily impacts the economic development of a country, including the general quality of life within a society. The designed simulation generates different scenarios of the Serbian municipal waste system for reaching the 2035 recycling rate targets. Methodologies such as the theory of constraints, fragility analysis, and systems dynamics were implemented in the model. The scenarios and fragility modelling were conducted with the system dynamics modelling methodology in the Ventity simulation environment. The designed model has elements of discrete event simulations, system dynamics, and agent-based modelling. Importantly, real-world data for the period of five years (from the year 2016 to 2020) was used in the case study. This research undoubtedly reveals that the informal sector is the key source of fragility to the dynamic system considered. During the considered period, the informal sector contributed 62.3% of all separated waste to the system. Consequently, this research concludes that for the waste sector in Serbia to reach the 2035 EU goals, the existing practice in waste management has to be changed significantly and will benefit from the modelling approach used here. The whole system is highly dependent on the informal sector, which, in its current form, is volatile, unregulated, and fragile to aggressive regulative policies.
Assessment of the handcart pushing and pulling safety by using deep learning 3D pose estimation and IoT force sensors
(2021) Vukicevic A.; Macuzic, Ivan; Mijailovic, Natasa; Peulic A.; Radović M.
Pushing and pulling (P&P) are common and repetitive tasks in industry, which non-ergonomic execution is among major causes of musculoskeletal disorders (MSD). The current safety management of P&P assumes restrictions of maximal weight, distance, height – while variable individual parameters (such as the P&P pose ergonomic) remain difficult to account for with the standardized guides. Since manual detection of unsafe P&P acts is subjective and inefficient, the aim of this study was to utilize IoT force sensors and IP cameras to detect unsafe P&P acts timely and objectively. Briefly, after the IoT module detects moments with increased P&P forces, the assessment of pose ergonomics was performed from the employee pose reconstructed with the VIBE algorithm. The experiments showed that turn-points correspond to the high torsion of torso, and that in such moments poses are commonly non ergonomic (although P&P forces are below values defined as critical in previous studies – their momentum cause serious load on the human body). Moreover, the analysis revealed that the loading/unloading of a cargo are also moments of frequent unsafe P&P acts – although they are commonly neglected when studying P&P. The experimental validation of the solution showed good agreement with motion sensors and high potential for monitoring and improving P&P workplace safety. Accordingly, future research will be directed towards: 1) acquisition of P&P data sets for direct recognition and classification of unsafe P&P acts; 2) incorporation of wearable sensors (EMG and EEG) for detecting fatigue and decrease of physical abilities.
BARRIERS, CHALLEGNES AND OPPORTUNITIES TO IMPROVE OCCUPATIONAL HEALTH AND SAFETY MANAGEMENT IN SMALL AND MEDIUM ENTERPRISES IN SERBIA: CASE STUDY APPROACH
(2019) Savković, Marija; Dapan M.; Macuzic, Ivan; Todorovic, Petar; Radenkovic M.; Vukicevic, Arso; Mijović N.
Paper aims is analysis of the current situation in SME in Serbia, identification, analyse and description of the main barriers to the management of OHS in SMEs in Serbia and points to the possibilities of overcoming barriers. Based on interviews and observations, results indicate that the different groups at different hierarchical levels experience different types of barriers. Main barriers in SMEs in Serbia were classified into four categories: lack of top management support, financial capability, lack of employee’s skill and expertise and organizational culture. The number of barriers increases with the size of the enterprise. Also, in this paper authors presented the key factors that affect health and safety at work in SMEs. The most important are: management commitment, air safety, competence and motivation of employees, training and education in the field of security, the implementation of regulations in the field of OHS etc.
Benefits of instructed responding in manual assembly tasks: An ERP approach
(2016) Mijovic, Pavle; Kovic V.; De Vos M.; Macuzic, Ivan; Jeremic, Branislav; Gligorijevic, Ivan
© 2016 Mijović, Ković, De Vos, Mačužić, Jeremić and Gligorijević. The majority of neuroergonomics studies are focused mainly on investigating the interaction between operators and automated systems. Far less attention has been dedicated to the investigation of brain processes in more traditional workplaces, such as manual assembly, which are still ubiquitous in industry. The present study investigates whether assembly workers’ attention can be enhanced if they are instructed with which hand to initiate the assembly operation, as opposed to the case when they can commence the operation with whichever hand they prefer. For this aim, we replicated a specific workplace, where 17 participants in the study simulated a manual assembly operation of the rubber hoses that are used in vehicle hydraulic brake systems, while wearing wireless electroencephalography (EEG). The specific EEG feature of interest for this study was the P300 components’ amplitude of the event-related potential (ERP), as it has previously been shown that it is positively related to human attention. The behavioral attention-related modality of reaction times (RTs) was also recorded. Participants were presented with two distinct tasks during the simulated operation, which were counterbalanced across participants. In the first task, digits were used as indicators for the operation initiation (Numbers task), where participants could freely choose with which hand they would commence the action upon seeing the digit. In the second task, participants were presented with arrows, which served as instructed operation initiators (Arrows task), and they were instructed to start each operation with the hand that corresponded to the arrow direction. The results of this study showed that the P300 amplitude was significantly higher in the instructed condition. Interestingly, the RTs did not differ across any task conditions. This, together with the other findings of this study, suggests that attention levels can be increased using instructed responses without compromising work performance or operators’ well-being, paving the way for future applications in manual assembly task design.
Cognitive status and repetitive working tasks of low risk
(2019) Giagloglou, Evanthia; Mijovic P.; Ranković B.; Antoniou P.; Macuzic, Ivan
© 2017 Elsevier Ltd 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.
Decision Support System for Dimensional Inspection of Extruded Rubber Profiles
(2019) Vukicevic A.; Djapan M.; Todorovic, Petar; Erić, Milan; Stefanovic, Miladin; Macuzic, Ivan
© 2013 IEEE. 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.
Determination of barriers priority that impacts to the implementation of the TPM concept by using Genetic Algorithm
(2019) Komatina, Nikola; Macuzic, Ivan; Aleksic, Aleksandar; Bergam, Tijana
The implementation of the TPM concept brings with it significant benefits for an enterprise, but also faces with numerous barriers that can obstruct the implementation process. Also, an inadequate implementation method can generate some additional problems. In this paper, the problem of barriers priority determination that affects the implementation of the TPM concept by using the Genetic Algorithm is considered. The main goal of this paper is to determine which barriers are the most important to the TPM concept implementation by applying this metaheuristic method, but also those barriers that could be more easily eliminated if the major impact barriers were eliminated first. The considered problem in this paper is set as so-called "P-Median" problem. So far, in the literature it has not been possible to find papers where this type of problem has been solved by the application of any of the metaheuristics or Multi-Criteria Decision-Making methods.
Development of Modular and Adaptive Laboratory Set-Up for Neuroergonomic and Human-Robot Interaction Research
(2022) Savković, Mile; Caiazzo C.; Djapan M.; Vukicevic A.; Pušica M.; Macuzic, Ivan
The industry increasingly insists on academic cooperation to solve the identified problems such as workers' performance, wellbeing, job satisfaction, and injuries. It causes an unsafe and unpleasant working environment that directly impacts the quality of the product, workers' productivity, and effectiveness. This study aimed to give a specialized solution for tests and explore possible solutions to the given problem in neuroergonomics and human–robot interaction. The designed modular and adaptive laboratory model of the industrial assembly workstation represents the laboratory infrastructure for conducting advanced research in the field of ergonomics, neuroergonomics, and human–robot interaction. It meets the operator's anatomical, anthropometric, physiological, and biomechanical characteristics. Comparing standard, ergonomic, guided, and collaborative work will be possible based on workstation construction and integrated elements. These possibilities allow the industry to try, analyze, and get answers for an identified problem, the condition, habits, and behavior of operators in the workplace. The set-up includes a workstation with an industry work chair, a Poka–Yoke system, adequate lighting, an audio 5.0 system, containers with parts and tools, EEG devices (a cap and smartfones), an EMG device, touchscreen PC screen, and collaborative robot. The first phase of the neuroergonomic study was performed according to the most common industry tasks defined as manual, monotonous, and repetitive activities. Participants have a task to assemble the developed prototype model of an industrial product using prepared parts and elements, and instructed by the installed touchscreen PC. In the beginning, the participant gets all the necessary information about the experiment and gets 15 min of practice. After the introductory part, the EEG device is mounted and prepared for recording. The experiment starts with relaxing music for 5 min. The whole experiment lasts two sessions per 60 min each, with a 15 min break between the sessions. Based on the first experiments, it is possible to develop, construct, and conduct complex experiments for industrial purposes to improve the physical, cognitive, and organizational aspects and increase workers' productivity, efficiency, and effectiveness. It has highlighted the possibility of applying modular and adaptive ergonomic research laboratory experimental set-up to transform standard workplaces into the workplaces of the future.
Digital training and advanced learning in occupational safety and health based on modern and affordable technologies
(2021) Vukicevic, Arso; Macuzic, Ivan; Djapan, Marko; Milićević, Vladimir; Shamina L.
Occupational safety and health (OSH) is a very important issue for both practical purposes in industry and business due to numerous reasons, so a number of software, educational and industrial solutions are available. In this paper, the cloud-based mobile application for digital training and advanced learning in the field of occupational safety was presented. The proposed framework architecture was based on a novel approach: Node.JS for the server backend and the React Native for the front-end development; while MongoDB was used for implementing the cloud data storage using sensors that are all available on the Android platform. In the development of this application, a number of options were developed (using open-source software) such as the reading of a QR code, usage of built-in sensors within android platforms, reporting, and voice messages. The developed SafeST solution is presented through a real industry example. It emphasizes two main possibilities of the solution, improving OHS reporting and significant empowerment of the students in the OHS field based on the learning-by-doing approach. In this way, the additional engagement (identification, recording and reporting of UA/UC) of OSH managers has been reduced to a minimum, taking into account requested reports from management and authorities, and the continual training of the employees and preparation of the students for future working activities. The system was tested for educational purposes with the initial idea to develop an application for smartphones which could be useful and well adopted among engineering students in the OSH field.
Do Micro-Breaks Increase the Attention Level of an Assembly Worker? An ERP Study
(2015) Mijovic P.; Kovic, Vanja; Macuzic, Ivan; Todorovic, Petar; Jeremic B.; Milovanović, Miloš; Gligorijević I.
© 2015 The Authors This study investigates the influence of micro-breaks on the attention of an assembly worker, by utilizing wireless electroencephalographic (EEG) measurements. The EEG feature of interest for this study was the P300 event-related potential (ERP) component and P3a and P3b sub-components, as these components reflects the ones attention level. Nine students participated the study and completed the simulated manual assembly task, replicated from one of our industrial partner. We used sustained attention to response task (SART), instead of real industrial information that indicates the beginning of the operation. SART paradigm is “go/no-go” task, and in this version of SART, participants are required to respond to all “go” stimuli, in sense of initiating the action of manual assembly operation, and to withhold the action otherwise. The “no-go” condition was considered as micro-break period, since the participants had approximately five seconds to rest during a continuous simulated working routine. Fifty ERPs preceding and following the “no-go” condition were compared. The results revealed that, on the group level, the values of the amplitude of the P3b sub-component, which is related to the higher-level attention processing, were significantly higher for the ERPs following than preceding the micro-break period. This finding indicates that the frequent micro-breaks increase the attention of the manual assembly workers.