Some insights to determine the proper level of descriptions about proceduralized tasks

Park, Jinkyun; Park, Soon-Yeol; Cho, Sungi

doi:10.1016/j.pnucene.2009.06.012

Cited by 4 publications

(2 citation statements)

References 19 publications

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“…A certain amount of system knowledge is required to carry out an action and to understand the complications of the task. The capacity of an operator, in terms of the precision and cognitive effort, during the execution of a task, along with the specific resources required by the task, contribute to the performance level of a human operator [104]. Table 10 outlines a proposed user skill level paradigm.…”

Section: Skills Required To Program and Control A Cobotmentioning

confidence: 99%

Task Complexity and the Skills Dilemma in the Programming and Control of Collaborative Robots for Manufacturing

et al. 2023

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While traditional industrial robots participate in repetitive manufacturing processes from behind caged safety enclosures, collaborative robots (cobots) offer a highly flexible and human-interactive solution to manufacturing automation. Rather than operating from within cages, safety features such as force and proximity sensors and programmed protection zones allow cobots to work safely, close to human workers. Cobots can be configured to either stop or slow their motion if they come in contact with a human or obstacle or enter a protection zone, which may be a high pedestrian traffic area. In this way, a task can be divided into sub-processes allocated to the cobot or the human based on suitability, capability or human preference. The flexible nature of the cobot makes it ideal for low-volume, ‘just-in-time’ manufacturing; however, this requires frequent reprogramming of the cobot to adapt to the dynamic processes. This paper reviews relevant cobot programming and control methods currently used in the manufacturing industry and alternative solutions proposed in the literature published from 2018 to 2023. The paper aims to (1) study the features and characteristics of existing cobot programming and control methods and those proposed in the literature, (2) compare the complexity of the task that the cobot is to perform with the skills needed to program it, (3) determine who is the ideal person to perform the programming role, and (4) assess whether the cobot programming and control methods are suited to that person’s skillset or if another solution is needed. The study is presented as a guide for potential adopters of cobots for manufacturing and a reference for further research.

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Section: Skills Required To Program and Control A Cobotmentioning

confidence: 99%

Task Complexity and the Skills Dilemma in the Programming and Control of Collaborative Robots for Manufacturing

et al. 2023

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“…In summary, our study and other empirical studies imply that SPAR-H tends to evaluate human reliability optimistically for computerized tasks. According to the distinction of a task and a step made by Park et al, (61,62) an action as a task in SPAR-H may include more than one step, that is, the nominal HEP for a step should be less than 0.001. If this is the case, a larger difference between the EHEP and PHEP would be observed.…”

Section: Human Error Probabilitiesmentioning

confidence: 99%

Human Error Data Collection and Comparison with Predictions by SPAR‐H

Liu

2014

Risk Analysis

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There is a scarcity of empirical data on human error for human reliability analysis (HRA). This situation can increase the variability and impair the validity of HRA outcomes in risk analysis. In this work, a microworld study was used to investigate the effects of performance shaping factors (PSFs) and their interrelationships and combined effects on the human error probability (HEP). The PSFs involved were task complexity, time availability, experience, and time pressure. The empirical data obtained were compared with predictions by the Standardized Plant Analysis Risk-Human Reliability Method (SPAR-H) and data from other sources. The comparison included three aspects: (1) HEP, (2) relative effects of the PSFs, and (3) error types. Results showed that the HEP decreased with experience and time availability levels. The significant relationship between task complexity and the HEP depended on time availability and experience, and time availability affected the HEP through time pressure. The empirical HEPs were higher than the HEPs predicted by SPAR-H under different PSF combinations, showing the tendency of SPAR-H to produce relatively optimistic results in our study. The relative effects of two PSFs (i.e., experience/training and stress/stressors) in SPAR-H agreed to some extent with those in our study. Several error types agreed well with those from operational experience and a database for nuclear power plants (NPPs).

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Operating Procedure

Park¹

2017

Handbook of Safety Principles

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Some insights to determine the proper level of descriptions about proceduralized tasks

Cited by 4 publications

References 19 publications

Task Complexity and the Skills Dilemma in the Programming and Control of Collaborative Robots for Manufacturing

Task Complexity and the Skills Dilemma in the Programming and Control of Collaborative Robots for Manufacturing

Human Error Data Collection and Comparison with Predictions by SPAR‐H

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