ADAPT - A decision-model-based Approach for Modeling Collaborative Assembly and Manufacturing Tasks

Lindorfer, Rene; Froschauer, Roman; Schwarz, Georg

doi:10.1109/indin.2018.8472064

Cited by 10 publications

(4 citation statements)

References 27 publications

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“…In the scope of the herein presented approach, the problem of optimizing workflows is treated as a multi-objective optimization problem [1], utilizing ADAPT [6] for the formal representation of workflows and the HeuristicLab framework [9] for the optimization of such workflows. For this purpose we employ implementations of a set of suitable algorithms, such as NSGA-II [2] and NSGA-III [11].…”

Section: Methodology and Technologiesmentioning

confidence: 99%

“…The FELICE project 1 aims to provide a new solution for digitized and flexible assembly lines to increase both the level of automatism and the ability to react to a dynamic and changing environment. Premise of this solution is a formal representation of any given workflow containing all necessary assembly tasks executed during manufacturing, for which the ADAPT 2 modeling approach [6] is utilized. This formal representation of a workflow provides the opportunity for computational parsing, monitoring, execution and optimization.…”

Section: Background and Motivationmentioning

confidence: 99%

“…For workflows, e.g. representing assembly tasks, BPMN [10] is a well established standard and the theoretical origin of other approaches, such as the ADAPT [6] modeling approach. An overview of the core elements is illustrated in Figure 1 and a more detailed explanation is given as follows.…”

Section: Adapt Modeling Approachmentioning

confidence: 99%

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Multi-criteria Optimization of Workflow-Based Assembly Tasks in Manufacturing

Holzinger

Beham

2022

Lecture Notes in Computer Science

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Industrial manufacturing is currently amidst it's fourth great revolution, pushing towards the digital transformation of production processes. One key element of this transformation is the formalization and digitization of processes, creating an increased potential to monitor, understand and optimize existing processes. However, one major obstacle in this process is the increased diversification and specialisation, resulting in the dependency on multiple experts, which are rarely amalgamated in small to medium sized companies. To mitigate this issue, this paper presents a novel approach for multi-criteria optimization of workflow-based assembly tasks in manufacturing by combining a workflow modeling framework and the HeuristicLab optimization framework. For this endeavour, a new generic problem definition is implemented in HeuristicLab, enabling the optimization of arbitrary workflows represented with the modeling framework. The resulting Pareto front of the multi-criteria optimization provides the decision makers a set of optimal workflows from which they can choose to optimally fit the current demands. The advantages of the herein presented approach are highlighted with a real world use case from an ongoing research project.

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Section: Methodology and Technologiesmentioning

confidence: 99%

Section: Background and Motivationmentioning

confidence: 99%

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Multi-criteria Optimization of Workflow-Based Assembly Tasks in Manufacturing

Holzinger

Beham

2022

Lecture Notes in Computer Science

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“…HRTM com-bines the methods time measurement (MTM) approach, which is used for modeling the working steps of human workers, and the robot time and motion (RTM) approach, which is used for modeling the working steps of robots. Froschauer et al [50] extended HRTM by combining it with ADAPT [51], a universal modeling approach that allows a shift of programming complexity from the end-user to a modeling expert. However, the modeled BPMN workflows do not include an automatic trigger for robots to perform the corresponding command at the right time.…”

Section: Bpmn Modelingmentioning

confidence: 99%

Novel Approach Using Risk Analysis Component to Continuously Update Collaborative Robotics Applications in the Smart, Connected Factory Model

et al. 2022

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Building on the idea of Industry 4.0, new models of the highly connected factory that leverage factory-generated data to introduce cost-effective automation and involve the human worker for creating higher added value are possible. Within this context, collaborative robots are becoming more common in industry. However, promises regarding flexibility cannot be satisfied due to the challenging process of ensuring human safety. This is because current regulations and standards require updates to the risk assessment for every change to the robotic application, including the parts involved, the robotic components, and the type of interaction within the workspace. This work presents a novel risk analysis software tool that was developed to support change management for adaptive collaborative robotic systems in the connected factory model. The main innovation of this work is the tool’s ability to automatically identify where changes have been made to components or processes within a specific application through its integration with a connected factory architecture. This allows a safety expert to easily see where updates to the risk assessment are required, helping them to maintain conformity with the CE marking process despite frequent changes. To evaluate the benefits of this tool, a user study was performed with an exemplary use-case from the SHOP4CF project. The results show that this newly developed technology for risk assessment has better usability and lower omission errors when compared to existing methods. Therefore, this study underlines the need for tools that can help safety engineers cope with changes in flexible robotics applications and reduce omission errors.

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