Working Situation Reference Model for Risk Assessment on Automated Assembly Lines

Duponnois, Romain; Lamy, Pascal; Levrat, Éric; Siadat, Ali

doi:10.3850/978-981-14-8593-0_3970-cd

Cited by 1 publication

(5 citation statements)

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“…The perception of the technical drift is perceived by the operator through the drift of interactions between themselves and the technical component of the working situation (Duponnois et al 2020).…”

Section: Operator Responsementioning

confidence: 99%

“…In this first step, we will use the Working situation model presented in (Duponnois et al 2020) as a reference to model the working situation studied.…”

Section: Modeling the Working Situation (R1)mentioning

confidence: 99%

“…The goal of sub-step R1.7 is to model all the interactions between the operator, tools, products and machine components. The way these interactions are modeled is presented in (Duponnois et al 2020).…”

Section: Sub-steps Proposalsmentioning

confidence: 99%

“…Existing (nominal) interactions are represented in the instantiated model of the working situation (data model) (Duponnois et al 2020). An interaction can be seen as a flow; representing an interaction's drift is described as a drift of one of its Time-Space-Shape properties:  Time: duration, frequency, start time.…”

Section: Proposals Of Sub-stepsmentioning

confidence: 99%

“…Emerging interactions are new interactions that did not occur in the nominal working situation. These interactions are characterized in the same way as nominal interactions (Duponnois et al 2020). For each drifting or emerging interaction, the potential perception of this drift by the operator is estimated and is also reported in the table, in the Detection column (D-mark).…”

Section: Proposals Of Sub-stepsmentioning

confidence: 99%

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Working Situation Health Monitoring: Proposal of Method and Case Study

Duponnois¹,

Levrat²,

Siadat³

et al. 2021

Proceedings of the 31st European Safety and Reliability Conference (ESREL 2021)

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In a working situation on an automated assembly machine, technical drifts during operation can lead to machine dysfunctions. These dysfunctions may cause the operator supervising the machine to adapt and respond to reduce the effect of these technical drifts on the rest of the working situation. To respond to these dysfunctions the operator may expose him or herself to hazards and thus be in a hazardous situation. (Lamy & Perrin, 2020) showed the feasibility of identifying this kind of potentially hazardous situation by observing the working situation. Here, we propose a method called Working Situation Health Monitoring (WSHM). The goal of this method is to identify these potentially hazardous situations by analyzing the potential drift of working situations and monitor the advent of potentially hazardous situations using equipment and production data. It consists of three steps: firstly, we model the working situation studied to characterize the nominal working situation; secondly, we analyze cause-and-effect relationships between potential process drifts, potential operator responses and potentially hazardous situations; and thirdly, we construct a health indicator of the working situation based on knowledge of potentially hazardous situations identified in the second step and by equipment data. This paper also presents the application of the method to a case study (an educational automated assembly machine).

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Section: Operator Responsementioning

confidence: 99%

“…In this first step, we will use the Working situation model presented in (Duponnois et al 2020) as a reference to model the working situation studied.…”

Section: Modeling the Working Situation (R1)mentioning

confidence: 99%

Section: Sub-steps Proposalsmentioning

confidence: 99%

Section: Proposals Of Sub-stepsmentioning

confidence: 99%

Section: Proposals Of Sub-stepsmentioning

confidence: 99%

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