Modelling and Assessing Line-less Mobile Assembly Systems

Hüttemann, Guido; Buckhorst, Armin F.; Schmitt, Robert

doi:10.1016/j.procir.2019.03.184

Cited by 38 publications

(9 citation statements)

References 20 publications

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“…The availability of industrial production data in a networked system landscape acts in this background as a technical enabler to increase the relevance of topics, such as AI and data-driven approaches. This further opens up new potentials for optimizing (novel) manufacturing systems, e.g., line-less mobile assembly systems in Figure 3 , which enable agile assembly of large components by leveraging modeling and scheduling systems [ 85 ]. The primary objective of utilizing AI at this level is to improve the adaptability of DTs to dynamically changing boundary conditions on the factory and shop floor scale.…”

Section: Sustainable Resilient Manufacturingmentioning

confidence: 99%

A Survey on AI-Driven Digital Twins in Industry 4.0: Smart Manufacturing and Advanced Robotics

Huang

Shen²,

et al. 2021

Sensors

160

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Digital twin (DT) and artificial intelligence (AI) technologies have grown rapidly in recent years and are considered by both academia and industry to be key enablers for Industry 4.0. As a digital replica of a physical entity, the basis of DT is the infrastructure and data, the core is the algorithm and model, and the application is the software and service. The grounding of DT and AI in industrial sectors is even more dependent on the systematic and in-depth integration of domain-specific expertise. This survey comprehensively reviews over 300 manuscripts on AI-driven DT technologies of Industry 4.0 used over the past five years and summarizes their general developments and the current state of AI-integration in the fields of smart manufacturing and advanced robotics. These cover conventional sophisticated metal machining and industrial automation as well as emerging techniques, such as 3D printing and human–robot interaction/cooperation. Furthermore, advantages of AI-driven DTs in the context of sustainable development are elaborated. Practical challenges and development prospects of AI-driven DTs are discussed with a respective focus on different levels. A route for AI-integration in multiscale/fidelity DTs with multiscale/fidelity data sources in Industry 4.0 is outlined.

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Section: Sustainable Resilient Manufacturingmentioning

confidence: 99%

A Survey on AI-Driven Digital Twins in Industry 4.0: Smart Manufacturing and Advanced Robotics

Huang

Shen²,

et al. 2021

Sensors

160

View full text Add to dashboard Cite

show abstract

“…Yang et al propose that KPI selection for the smart automation of manufacturing systems needs to be company and location-specific and that the KPIs variation and sensitivity to the introduction of new Industry 4.0 technology needs to be a key driver for developing a strategy for smart assembly automation [106]. For evaluating the performance of Line-less Mobile Assembly Systems (LMAS), Hüttemann et al developed a set of 11 specific KPIs, 6 of which are adapted from conventional KPIs to account for the wide variety of products being made in the assembly system, and 5 are specific to LMAS (e.g., overall traveled distance, number of station configuration reconfigurations) [107].…”

Section: Key Performance Indicators For Assemblymentioning

confidence: 99%

Lean Manual Assembly 4.0: A Systematic Review

2020

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In a demand context of mass customization, shifting towards the mass personalization of products, assembly operations face the trade-off between highly productive automated systems and flexible manual operators. Novel digital technologies—conceptualized as Industry 4.0—suggest the possibility of simultaneously achieving superior productivity and flexibility. This article aims to address how Industry 4.0 technologies could improve the productivity, flexibility and quality of assembly operations. A systematic literature review was carried out, including 234 peer-reviewed articles from 2010–2020. As a result, the analysis was structured addressing four sets of research questions regarding (1) assembly for mass customization; (2) Industry 4.0 and performance evaluation; (3) Lean production as a starting point for smart factories, and (4) the implications of Industry 4.0 for people in assembly operations. It was found that mass customization brings great complexity that needs to be addressed at different levels from a holistic point of view; that Industry 4.0 offers powerful tools to achieve superior productivity and flexibility in assembly; that Lean is a great starting point for implementing such changes; and that people need to be considered central to Assembly 4.0. Developing methodologies for implementing Industry 4.0 to achieve specific business goals remains an open research topic.

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“…Examples are the parallelization of multiple lines or a matrix layout. Now, each product follows an individually optimized processing route through the assembly resources (Hüttemann et al, 2016;Hüttemann et al, 2019).…”

Section: Introductionmentioning

confidence: 99%

Industrial applications of a modular software architecture for line-less assembly systems based on interoperable digital twins

et al. 2023

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In manufacturing, rising demands for customized products have led to increased product variance and shortened product life cycles. In assembly lines, an increased variant diversity impedes the product flow. As a result, the utilization of assembly resources decreases, and production costs grow. An approach to increase the flexibility and adaptability of the assembly system is the implementation of the concept of line-less assembly. In the first step, the assembly line is dissolved. Then, stations are reallocated and linked by automated guided vehicles resulting in a loosely coupled layout, for example, a parallelization and interconnection of multiple lines or a matrix layout. A key requirement for the successful operation and control of a line-less assembly system is the collection and correct interpretation of data. To fully exploit the flexibility and adaptability of the concept of line-less assembly, a software architecture for planning and control must base on an information model allowing the fast integration of all shop floor assets and other data resources. Therefore, a modular data model with standardized interfaces for interoperable data exchange like a digital twin is needed. The aim of this paper is the development and implementation of a software architecture for planning and control of a line-less assembly system. Moreover, the architecture should integrate an interoperable digital twin of the physical system. To satisfy the criteria of interoperability and fast deployment, the digital twins are evolved following the methodology of a digital twin pipeline. Furthermore, a physical demonstrator serves as a testbed for the developed software architecture and digital twins. On the level of production planning and control, relevant industrial applications are identified and implemented in the form of use cases to show the functionality of the line-less assembly system as cyber-physical production system.

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Modelling and Assessing Line-less Mobile Assembly Systems

Cited by 38 publications

References 20 publications

A Survey on AI-Driven Digital Twins in Industry 4.0: Smart Manufacturing and Advanced Robotics

A Survey on AI-Driven Digital Twins in Industry 4.0: Smart Manufacturing and Advanced Robotics

Lean Manual Assembly 4.0: A Systematic Review

Industrial applications of a modular software architecture for line-less assembly systems based on interoperable digital twins

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