Optimizing human-machine interaction in manual assembly

Stork, Sonja; Stößel, Christian; Schubö, Anna

doi:10.1109/roman.2008.4600652

Cited by 11 publications

(4 citation statements)

References 10 publications

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“…From these results, one can conclude that complex assembly primitives benefit more from support by AR-based communication modes than easier ones. The experiments demonstrate an effect of task difficulty and attentional guidance on task performance [162], [163]. The observed interplay of mental processes (e.g., searching for assembly parts or for assembly positions) and action execution (e.g., grasping or joining) seems to be an indicator for task complexity and an important factor for the prediction of performance times.…”

Section: ) Resultsmentioning

confidence: 80%

Artificial Cognition in Production Systems

Bannat¹,

Bautze²,

Beetz³

et al. 2011

IEEE Trans. Automat. Sci. Eng.

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Abstract-Today's manufacturing and assembly systems have to be flexible to adapt quickly to an increasing number and variety of products, and changing market volumes. To manage these dynamics, several production concepts (e.g., flexible, reconfigurable, changeable or autonomous manufacturing and assembly systems) were proposed and partly realized in the past years. This paper presents the general principles of autonomy and the proposed concepts, methods and technologies to realize cognitive planning, cognitive control and cognitive operation of production systems. Starting with an introduction on the historical context of different paradigms of production (e.g., evolution of production and planning systems), different approaches for the design, planning, and operation of production systems are lined out and future trends towards fully autonomous components of an production system as well as autonomous parts and products are discussed. In flexible production systems with manual and automatic assembly tasks, human-robot cooperation is an opportunity for an ergonomic and economic manufacturing system especially for low lot sizes. The state-of-the-art and a cognitive approach in this area are outlined. Furthermore, introducing self-optimizing and self-learning control systems is a crucial factor for cognitive systems. This principles are demonstrated by a quality assurance and process control in laser welding that is used to perform improved quality monitoring. Finally, as the integration of human workers into the workflow of a production system is of the highest priority for an efficient production, worker guidance systems for manual assembly with environmentally-and situationally dependent triggered paths on state-based graphs are described in this paper.Note to Practitioners-Today's manufacturing enterprises have to face a number of challenges in a turbulent environment that originates amongst other from saturated markets, unprecedented and abrupt changes in market demands, an ever increasing number of product variants and smaller lot sizes. A recent research trend in Germany is the so called Cognitive Factory, where artificial cognitive capabilities are introduced to the control of production systems. The applications range from production planning and control, human-robot-cooperation, automatic robot programming to intuitive worker guidance systems.The concept of fully automated production systems is no longer a viable vision, as it has been shown, that the conventional automa- tion is not able to deal with the ever-rising complexity of modern production systems. Especially, a high reactivity, agility and adaptivity that is required by modern production systems, can only be reached by human operators with their immense cognitive capabilities, which enable them to react to unpredictable situations, to plan their further actions, to learn and to gain experience and to communicate with others. Thus, new concepts are required, that apply these cognitive principles to the planning processes and control systems of pr...

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Section: ) Resultsmentioning

confidence: 80%

Artificial Cognition in Production Systems

Bannat¹,

Bautze²,

Beetz³

et al. 2011

IEEE Trans. Automat. Sci. Eng.

Self Cite

View full text Add to dashboard Cite

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“…Summarizing, complex assembly primitives benefited more from support by AR-based communication modes than easier ones. These results demonstrate a statistical interaction between task difficulty and attentional guidance on task performance [24,39].…”

Section: Resultsmentioning

confidence: 69%

A multi-dimensional measure for determining the complexity of manual assembly operations

Zaeh

Wiesbeck

Stork

et al. 2009

Prod. Eng. Res. Devel.

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A key to solving the discrepancies of deterministic and static assembly sequences at manual work places is seen in situation-oriented and cognitive methodologies in assembly. These provide means for efficient and ergonomically feasible worker guidance. An accurate and detailed technique of adjusting the instructional content is seen as a prerequisite. In this context the authors present factors for a multi-dimensional measurement of the degree of detail and complexity of manual assembly tasks. It extends the concept and application of common systems of predetermined times. It includes dimensions of actual human performance and attention allocation, as well as learning effects based on the product and its reference levels. It is assumed that identifying global attributes that contribute to assembly difficulty will provide means for predicting assembly complexity more effectively.

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“…interaction forms are becoming more complex with the trend of the application of robots in new contexts, such as human-machine interactions in a working environment [21]. These assistive systems need to be flexible and adaptive.…”

Section: Task Allocation: Worker Skills and Robot Abilitiesmentioning

confidence: 99%

Characterizing the State of the Art of Human-Robot Coproduction

2015

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Abstract-It is expected that soon, systems consisting of a blend of humans and robots be devised in such a way that higher productivities will be achieved. The main enabler for this is expected to be the possibility of collaboration between workers and robots. HRI (Human Robot Interaction) is the field in which such phenomena are studied. A growing number of investigators treat the collaboration of robots and workers (humans) in many contexts, however attention towards the manufacturing industry is predominantly focused on full automation of human tasks. Industrial robots have long been unsafe to work in close vicinity to workers due to their duty to be fast and powerful. However, nowadays, with the drive from emerging technologies, this is changing. Safe worker-robot collaborations are beginning to take shape and the HRI community is beginning to study such scenarios. Despite being a very effective form of interaction, a key research question is whether collaboration is a suitable mode of interaction for manufacturing environments. To be able to address this question, we found a collection of ten workerrobot systems that constitute a first step in outlining coproduction characteristics. This collection allowed us to identify differences in task initiative and product handling and component handling, while we frame coproduction as an extension of man. Challenges that require additional attention are workflow planning and defining proper performance indicators. We conclude with the fact that, although the worker-robot collaboration systems are inspiring and redefine labor, no sufficient knowledge or tools exists to reproduce such qualities in different manufacturing settings. Further work will be focused on modeling and assessing the performance and bottlenecks of systems based on novel robotic systems.

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Optimizing human-machine interaction in manual assembly

Cited by 11 publications

References 10 publications

Artificial Cognition in Production Systems

Artificial Cognition in Production Systems

A multi-dimensional measure for determining the complexity of manual assembly operations

Characterizing the State of the Art of Human-Robot Coproduction

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