Competency Model for Logistics Employees in Smart Factories

Kohl, Markus; Heimeldinger, Carina; Brieke, Michael; Fottner, Johannes

doi:10.1007/978-3-030-20494-5_13

“…However, while learning factories can support proof-ofconcept integration, they do not scale up adequately to real industrial challenges as human operators, who should work in close collaboration with various machines or robots, lack the required qualifications [15]. Therefore, several employee qualification and competency building models have been developed where a variety of personal, social, action-related and domain-related competencies can be improved [16], [17].…”

Section: Related Workmentioning

confidence: 99%

Hey Max, can you help me? An Intuitive Virtual Assistant for Industrial Robots

Li¹,

Chrysostomou²,

Pinto³

et al. 2022

Preprint

2

0

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<p>Assisting employees in acquiring the knowledge and skills necessary to grasp and use new services and technologies on the shop floor is critical for manufacturers to adapt to Industry 4.0 successfully. In this paper, we employ a Learning, Training, Assistance (LTA) approach and propose a framework for a Language-enabled Virtual Assistant (VA) to facilitate this adaptation. In our system, the human-robot interaction is achieved through spoken natural language and a dashboard implemented as a web-based application. This type of interaction enables operators of all levels to control a collaborative robot intuitively in several industrial scenarios and use it as a complementary tool for developing their competencies. Our proposed framework has been extensively tested with 29 users who completed various tasks while interacting with the proposed VA and industrial robots. Through three different scenarios, we evaluated the usability of the system for LTA based on an established System Usability Scale and the cognitive effort required by the users based on the standardised NASA TLX questionnaire. The qualitative and quantitative results of the study show that users of all levels found the VA user friendly with low requirements for physical and mental effort during the interaction. Additionally, the study demonstrates that the VA enables operators to streamline the learning and training phases of new tasks and improve their user experience during the assistance phase for daily tasks. The source code of the proposed VA and the supplementary material of the user study are accessible at https://bit.ly/VA MAX to support the reproducibility of the proposed framework.</p>

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“…They do not scale up adequately to real industrial challenges because human operators who should work in close collaboration with various machines or robots lack the required qualifications [23]. Therefore, several employee qualification and competency building models have been developed where a variety of personal, social, action-related and domain-related competencies can be improved [24]- [26].…”

Section: Related Workmentioning

confidence: 99%

Hey Max, can you help me? An Intuitive Virtual Assistant for Industrial Robots

Li¹,

Chrysostomou²,

Pinto³

et al. 2022

Preprint

1

0

View full text Add to dashboard Cite

<p>Assisting employees in acquiring the knowledge and skills necessary to grasp and use new services and technologies on the shop floor is critical for manufacturers to adapt to Industry 4.0 successfully. In this paper, we employ a Learning, Training, Assistance (LTA) approach and propose a framework for a Language-enabled Virtual Assistant (VA) to facilitate this adaptation. In our system, the human-robot interaction is achieved through spoken natural language and a dashboard implemented as a web-based application. This type of interaction enables operators of all levels to control a collaborative robot intuitively in several industrial scenarios and use it as a complementary tool for developing their competencies. Our proposed framework has been extensively tested with 29 users who completed various tasks while interacting with the proposed VA and industrial robots. Through three different scenarios, we evaluated the usability of the system for LTA based on an established System Usability Scale and the cognitive effort required by the users based on the standardised NASA TLX questionnaire. The qualitative and quantitative results of the study show that users of all levels found the VA user friendly with low requirements for physical and mental effort during the interaction. Additionally, the study demonstrates that the VA enables operators to streamline the learning and training phases of new tasks and improve their user experience during the assistance phase for daily tasks. The source code of the proposed VA and the supplementary material of the user study are accessible at https://bit.ly/VA MAX to support the reproducibility of the proposed framework.</p>

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“…Information processing Bouri et al, 2018;Hecklau et al, 2016;Hummel et al, 2015;Kohl et al, 2019;Morgan et al, 2016 2. Network and information security 3.…”

Section: Table 1 Digital Skills -Disl Perspectivementioning

confidence: 99%

The Influence of Managerial, Digital, Relational and Behavioural Skills on the Perception of Barriers and Drivers of Implementing Digital Intelligent and Sustainable Logistics

T.¹,

Razniewska²,

Brzezinski³

et al. 2022

ERSJ

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Purpose:The purpose of the paper is to investigate the influence of different skills (managerial, digital, relational, behavioural) on the perception of barriers and drivers of implementing Digital Intelligent and Sustainable Logistics (DISL) in companies. Design/Methodology/Approach: To determine the impact of the level of skills on the perception of barriers and drivers of implementation of DISL, a survey was carried out among randomly selected logistics and production companies operating in Poland. Further, to test the research model and proposed hypothesis, this study applies Partial Least Squares Path Modelling (PLS), a variance-based structural equation modelling technique (SEM). Findings: The results of the conducted research allow us to conclude that there is a statistically significant relationship between the identified level of skills in a company and the perception of the significance level of barriers and drivers of DISL implementation (higher level of behavioural skills causes a stronger perception of barriers and drivers).Practical Implications: The findings can be used in decision making process on developing different skills in order to improve the perception of barriers and drivers and further support the implementation of DISL related solution in companies. Originality/Value: The paper contributes to the newest trends in literature on supply chain management (covering digitalization and smart and sustainable logistics) and specifically highlights the relation of skills with barriers and drivers on the implementation of DISL.

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Competency Model for Logistics Employees in Smart Factories

Cited by 11 publications

References 14 publications

Hey Max, can you help me? An Intuitive Virtual Assistant for Industrial Robots

Hey Max, can you help me? An Intuitive Virtual Assistant for Industrial Robots

Hey Max, can you help me? An Intuitive Virtual Assistant for Industrial Robots

The Influence of Managerial, Digital, Relational and Behavioural Skills on the Perception of Barriers and Drivers of Implementing Digital Intelligent and Sustainable Logistics

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