Safety Management System: a System Dynamics Approach to Manage Risks in a Process Plant

Nardo, Mario Di; Madonna, Marianna; Santillo, Liberatina Carmela

doi:10.15866/iremos.v9i4.9688

Cited by 12 publications

(10 citation statements)

References 0 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Simulation tools, already used in different contexts (Di Nardo & Gallo et al, 2015), help this new paradigm of Industry. In fact, for the new manufacturing context, Wörn et al (2000) identify the processes of new approaches where simulation takes an important role (Di Nardo et al, 2016). As described by J Lee et al (2015) the CPS has a certain 5 c architecture, with 5 different levels: Connection, Conversion, Cyber, Cognition, and Configuration.…”

Section: Introductionmentioning

confidence: 99%

The evolution of man–machine interaction: the role of human in Industry 4.0 paradigm

Nardo

Forino

Murino

2020

Production & Manufacturing Research

135

View full text Add to dashboard Cite

Industry 4.0 is a new paradigm in the manufacturing world and it has deeply changed the Human-machine interaction. This paper focus is on the nature of this interaction, which is made possible thanks to the Internet of Things (IoT), and Cyber-Physical System (CPS). These Industry 4.0 key technologies are studied related to the standard Deming cycle, in order to underline the importance of Humanmachine interaction. The Fourth Industrial Revolution involves several changes in the workforce's key features. In this paper, a new perspective based on the centrality of humans is given in the new Industry era. The importance of the human factor will be deeply studied through the implementation of the 'Sand Cone Model'. A new framework is proposed in order to explain the quality measures addiction on the workforce quality skills, and how it engraves on improving efficiency and effectiveness of an industrial process. ARTICLE HISTORY

show abstract

Section: Introductionmentioning

confidence: 99%

The evolution of man–machine interaction: the role of human in Industry 4.0 paradigm

Nardo

Forino

Murino

2020

Production & Manufacturing Research

135

View full text Add to dashboard Cite

show abstract

“…As the constant velocity and constant turn models were assumed for the prediction of the moving objects in the tracking filter, the application of the variable velocity and random motion models will assist in improving the performance of the safety algorithms in predicting the nonlinear motions of the objects in future work. System dynamics [25,26] can also be considered for an extension of the current work to enhance the predictive capability of the developed algorithms by investigating the interrelations among the factors causing safety incidents, such as worker-machine interaction.…”

Section: Discussionmentioning

confidence: 99%

“…i is the prediction step. By using Equations ( 24) and ( 25), the x (horizontal position) of the point p (P 1~P3-2 ) is calculated as shown in Equation (26). The predicted horizontal displacements, x pre,p,i can be generated using Equation (27).…”

Section: Calculation Of the Excavator's Working Areamentioning

confidence: 99%

Development of Sensing Algorithms for Object Tracking and Predictive Safety Evaluation of Autonomous Excavators

2021

View full text Add to dashboard Cite

This article presents the sensing and safety algorithms for autonomous excavators operating on construction sites. Safety is a key concern for autonomous construction to reduce collisions and machinery damage. Taking this point into consideration, our study deals with LiDAR data processing that allows for object detection, motion tracking/prediction, and track management, as well as safety evaluation in terms of potential collision risk. In the safety algorithm developed in this study, potential collision risks can be evaluated based on information from excavator working areas, predicted states of detected objects, and calculated safety indices. Experiments were performed using a modified mini hydraulic excavator with Velodyne VLP-16 LiDAR. Experimental validations prove that the developed algorithms are capable of tracking objects, predicting their future states, and assessing the degree of collision risks with respect to distance and time. Hence, the proposed algorithms can be applied to diverse autonomous machines for safety enhancement.

show abstract

“…In the model, the function that links the labor force to the available capital has been obtained by interpolating available data in [20]. The Tables 1 and 2 show the human resources data in terms of operator and system safety.…”

Section: Figure 4economic Loss Functionmentioning

confidence: 99%

Modelling A Safety Management System Using System Dynamics at the Bhopal Incidental Event

Nardo¹,

Madonna²,

Murino³

et al. 2019

Preprint

Self Cite

View full text Add to dashboard Cite

In Safety Management System (SMS), the risk management plays a key role for the prevention of accidents. The aim of this paper is to propose a Safety Management model using a system dynamic approach to update conventional industrial safety into the new industrial safety 4.0 that is time to developed. This study analyzes some safety 4.0 aspects lacked in the Bhopal incidental event by considering different data detected in the industrial Plant. The model proposed in this paper discusses the relationships among the main causes that have contributed to the occurrence of the incidental event studied, such as broken safety devices, inadequate personnel experience, operator decisions, manager production strategy, policy decision, as deduced from the relevant literature about Bhopal incidental dynamic.

show abstract

Safety Management System: a System Dynamics Approach to Manage Risks in a Process Plant

Cited by 12 publications

References 0 publications

The evolution of man–machine interaction: the role of human in Industry 4.0 paradigm

The evolution of man–machine interaction: the role of human in Industry 4.0 paradigm

Development of Sensing Algorithms for Object Tracking and Predictive Safety Evaluation of Autonomous Excavators

Modelling A Safety Management System Using System Dynamics at the Bhopal Incidental Event

Contact Info

Product

Resources

About