scholarly journals Decision-Making Framework for Implementing Safer Human–Robot Collaboration Workstations: System Dynamics Modeling

Safety ◽  
2021 ◽  
Vol 7 (4) ◽  
pp. 75
Author(s):  
Guilherme Deola Borges ◽  
Angélica Muffato Reis ◽  
Rafael Ariente Neto ◽  
Diego Luiz de Mattos ◽  
André Cardoso ◽  
...  
Keyword(s):  
Decision Making ◽  
System Dynamics ◽  
Computational Model ◽  
Actual Behavior ◽  
Dynamics Modeling ◽  
Work Related ◽  
Industrial Assembly ◽  
Process System ◽  
Decision Making Framework ◽  
Human Robot Collaboration

Human–Robot Collaboration (HRC) systems are often implemented seeking for reducing risk of Work-related Musculoskeletal Disorders (WMSD) development and increasing productivity. The challenge is to successfully implement an industrial HRC to manage those factors, considering that non-linear behaviors of complex systems can produce counterintuitive effects. Therefore, the aim of this study was to design a decision-making framework considering the key ergonomic methods and using a computational model for simulations. It considered the main systemic influences when implementing a collaborative robot (cobot) into a production system and simulated scenarios of productivity and WMSD risk. In order to verify whether the computational model for simulating scenarios would be useful in the framework, a case study in a manual assembly workstation was conducted. The results show that both cycle time and WMSD risk depend on the Level of Collaboration (LoC). The proposed framework helps deciding which cobot to implement in a context of industrial assembly process. System dynamics were used to understand the actual behavior of all factors and to predict scenarios. Finally, the framework presented a clear roadmap for the future development of an industrial HRC system, drastically reducing risk management in decision-making.

scholarly journals System Dynamics Model Application for Ergonomic Assessment of Manual Material Handling Tasks

2016 ◽  
Author(s):  
Hossein Abaeian ◽  
Osama Moselhi ◽  
Mohamad Al-Hussein
Keyword(s):  
System Dynamics ◽  
Material Handling ◽  
Dynamic Equilibrium ◽  
Project Managers ◽  
Dynamics Modeling ◽  
Work Related ◽  
Manual Material Handling ◽  
Compressive Loads ◽  
Levels Of Automation ◽  
Free Body

Despite increased levels of automation in manufacturing occupations in recent years, many activities are still performed through human intervention and involve Manual Material Handling (MMH), thus exposing workers to stress due to over-exertion and potential Work-Related Musculoskeletal Disorders (WRMSDs). An early ergonomic and physical demand assessment of work activities is critical to reducing exposure to risk and to maintaining desired levels of productivity. Biomechanics consists of applying concepts of static and dynamic equilibrium to different parts of the human musculoskeletal system using free-body diagrams to estimate muscle force and loads generated across the joints and tissues. System dynamics is a powerful tool applied in resolving complex problems with different influencing variables. This technique can help designers and managers to understand, evaluate and simulate the factors causing problems in the system. This paper presents the application of System Dynamics modeling to assess the biomechanical risks associated with manual material handling tasks. The case study presents predicted cumulative biomechanical compressive loads from material handling task and can assist project managers to understand and reduce exposure to ergonomic risks in the workplace.

scholarly journals Computational Modeling of the Effects of Sleep Deprivation on the Vigilance Decrement

2019 ◽  
Vol 61 (7) ◽  
pp. 1099-1111
Author(s):  
Robert Earl Patterson ◽  
Darrell Lochtefeld ◽  
Kathleen G. Larson ◽  
Amanda Christensen-Salem
Keyword(s):  
Sleep Deprivation ◽  
System Dynamics ◽  
Computational Modeling ◽  
Computational Model ◽  
Detection Performance ◽  
Dual Process ◽  
System Dynamics Modeling ◽  
Dynamics Modeling ◽  
Feedback Systems ◽  
Vigilance Decrement

Objective: We developed a computational model of the effects of sleep deprivation on the vigilance decrement by employing the methods of system dynamics modeling. Background: Situations that require sustained attention for a prolonged duration can cause a decline in cognitive performance, the so-called vigilance decrement. One factor that should influence the vigilance decrement is fatigue in the form of sleep deprivation. Method: We employed the methods of system dynamics modeling (numerical-integration techniques for modeling complex feedback systems) to create a computational model of the vigilance decrement. We then simulated the computational effects of sleep deprivation on the behavior of that model, using empirical data obtained from the literature for calibrating such effects. Results: Sleep deprivation of 2 hr over a 14-day period should produce an additional decline of 9% in detection performance over that found with the typical vigilance decrement, whereas 4 hr of sleep deprivation over 14 days should produce an additional decline of 14% in detection performance. Conclusion: With respect to dual-process theory, it is through its deleterious effects on analytical cognition that sleep deprivation should impact the vigilance decrement. Application: Such computational modeling may be advantageous for human-machine teaming by theoretically allowing a future autonomous software agent to anticipate the decline of human performance and compensate accordingly.

scholarly journals Engaging Stakeholders for Collaborative Decision Making in Humanitarian Logistics Using System Dynamics

2019 ◽  
Vol 17 (1) ◽  
Author(s):  
Xuesong Guo ◽  
Naim Kapucu
Keyword(s):  
Decision Making ◽  
System Dynamics ◽  
Performance Improvement ◽  
Humanitarian Logistics ◽  
System Thinking ◽  
System Dynamics Modeling ◽  
Dynamics Modeling ◽  
Collaborative Decision Making ◽  
Collaborative Decision ◽  
Sd Model

Abstract Participatory System Dynamics modeling is presented as a methodology to engage stakeholders in collaborative decision making in scenarios involving humanitarian logistics. Using the System Dynamics (SD) model, we simulated different scenarios, the results of which yielded factors that influence performance of humanitarian logistics. Once these were identified and discussed, different options on performance improvement were tested. This approach showed that the SD model can facilitate system thinking for stakeholders and form shared mental models critical to reaching consensus-based decisions in humanitarian logistics situations.

scholarly journals Modeling and Simulation of Consumer Preference Decision for Commercial Complex Location Based on System Dynamics

2022 ◽  
Vol 2022 ◽  
pp. 1-10
Author(s):  
Bin Guo ◽  
Bing Zhang ◽  
Yang Li
Keyword(s):  
Decision Making ◽  
System Dynamics ◽  
Site Selection ◽  
Influence Factors ◽  
Calculated Data ◽  
Consumer Preference ◽  
Commercial Real Estate ◽  
Shopping Behavior ◽  
Dynamics Modeling ◽  
Selection Decision

The influencing factors of consumer shopping behavior play a key role in the later performance of commercial real estate enterprises. On the basis of analyzing the influence factors of customer patronage and the influence factors of commercial complex site selection decision and their relationship, a causal relationship graph and a system dynamic model are established, which can describe the influence of customer preference on commercial complex site selection decision. And introducing customer subjective factors optimize the original pure objective factors site selection decision model. The model is implemented by using the system dynamics modeling tool Vensim. At the same time, the model is verified by using the data of the first-hand investigation. The results show that the calculated data of the model is in good agreement with the actual data. The results show that the system dynamics method can effectively simulate the influence of various factors on the decision-making of the commercial complex. As the forecast of the model, the key indexes of the decision-making of the city commercial complex are discussed, and the measures to be taken are put forward, which can provide reference for the decision-making of the location.

System Dynamics Modeling of the Time Course of the Recognition-Primed Decision Model

2009 ◽  
Vol 3 (3) ◽  
pp. 253-279 ◽  
Author(s):  
Robert Patterson ◽  
Lisa Fournier ◽  
Byron J. Pierce ◽  
Marc D. Winterbottom ◽  
Lisa M. Tripp
Keyword(s):  
Decision Making ◽  
System Dynamics ◽  
Decision Model ◽  
Time Course ◽  
System Dynamics Modeling ◽  
Dynamics Modeling ◽  
Dynamics Model ◽  
Course Of Action ◽  
Decision Making Processes ◽  
Benefits And Costs

Two types of decision-making processes have been identified in the literature: an analytical process and an intuitive process. One conceptual model of the latter is the recognition-primed decision (RPD) model (e.g., Klein, 2008). According to this model, decision making in naturalistic contexts entails a situational pattern-recognition process that, if subsequent expectancies are confirmed, leads the decision maker to render a decision to engage in a given course of action. In this paper, we describe a system dynamics model of Klein's RPD framework that focuses upon the dynamics of the decision-making process. The structure of our RPD model is based on a model of a set of laboratory phenomena called conjunction benefits and costs (e.g., L. R. Fournier, Patterson, Dyre, Wiediger, & Winters, 2007), which was extended to encompass the RPD framework. The results of our simulations suggest that decision priming (a bias toward rendering a given decision based on prior information) is a phenomenon that should occur in many naturalistic settings.

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