Simulation of Production Processes Involving Cyber-physical Systems

Lachenmaier, Jens F.; Lasi, Heiner; Kemper, Hans-Georg

doi:10.1016/j.procir.2016.06.074

Cited by 24 publications

(14 citation statements)

References 15 publications

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“…Due to the complexity of I4.0 and the challenges associated with its implementation and coordination, simulation can be used to facilitate the usage of all components of such systems, such as robots, information technology, manufacturing, and logistics [ 59 ] . MS technology can be used to solve manufacturing industry challenges, deal with complex systems, solve uncertain problems, and problems that cannot be solved by conventional mathematical models [75,76]. MS technologies are being used to simulate and model processes and products (for example, finite element analysis (FEA)), production lines, workstations, and internal logistics (for example, discrete event simulation (DES)), and enterprises, supply chains, and networks (for example, system dynamics (SD) and agent-based simulation (ABS)) [59].…”

Section: B Industry 40 Technologiesmentioning

confidence: 99%

The Impact of Industry 4.0 Technologies on Manufacturing Strategies: Proposition of Technology-Integrated Selection

2022

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Industry 4.0 (I4.0) has increasingly been adopted as an advanced manufacturing strategy to counter global competition. The capability of a company to compete on various manufacturing strategy outputs (MSOs) such as cost, quality, delivery, flexibility, performance and innovativeness play a significant role in motivating the whole company to take advantage of its competitors. I4.0 is comprised of various technologies, and how I4.0 technologies can influence the MSOs are still unclear, and it took less interest in the literature. This article aims to analyze the influence of the I4.0 technologies on MSOs to achieve market competitiveness from the perspective of academic and industry experts. To do so, the influence of the adoption of various I4.0 technologies on the MSOs was investigated. Expert opinions were gathered on the relationship between manufacturing competitive capabilities and I4.0 technologies. The identification of the influential relationships provides arguments for the proposed I4.0 technology selections, which will allow companies to gain a highly competitive advantage. The results showed that the performance (regarding the MSOs) had a high potential for integration with different I4.0 technologies.

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Section: B Industry 40 Technologiesmentioning

confidence: 99%

The Impact of Industry 4.0 Technologies on Manufacturing Strategies: Proposition of Technology-Integrated Selection

2022

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“…However, the higher process flexibility is, the more difficult it is to achieve a high manufacturing efficiency, an issue that can be properly addressed by the use of automation [98]. As the mass customization challenge requires the use of more flexible resources [99], from here we will consider the idea of addressing it through the use of an Industry 4.0 environment [100][101][102], more specifically, the use of a CPS-based smart manufacturing system.…”

Section: Sustainability and Manufacturing Efficiencymentioning

confidence: 99%

“…[106], and [107] agrees with the idea of the sustainability implications (for an organization) from the implementation of the Industry 4.0 concept. For example, a smart manufacturing system, an associated technology to Industry 4.0, is defined as a CPS coupled with (1) a decentralized, self-contained execution and decision-making structure, [108], and (2) a "self-conscious" environment [99]. The use of this technology makes it feasible to achieve the high levels of efficiency needed for a sustainable environment [109][110][111].…”

Section: Sustainability and Industry 40mentioning

confidence: 99%

Towards the Development of a Digital Twin for a Sustainable Mass Customization 4.0 Environment: A Literature Review of Relevant Concepts

Martínez-Olvera

2022

Automation

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Digital Twins (DTs) are one of the disruptive technologies associated with the Industry 4.0 concept. A DT connects the physical manufacturing system with the digital cyberspace, via the synchronization of the simulation (i.e., physical configurations) and data models (i.e., product, process, and resource models) of the manufacturing system. This synchronization of both worlds—the physical and digital—allows one to address the issue of manufacturing customized products. This challenge of mass customization (1) puts forward the goal of achieving the highest level of customer satisfaction, and (2) creates the need for the optimization of the complete value creation process. Within an Industry 4.0 context, the latter is translated as the interlinking of production resources and systems, via a DT, as it is in the physical world where the actual value-creation process takes place. The success of an Industry 4.0 mass customization environment (or mass customization 4.0), depends on its degree/level of sustainability. For these reasons, the present paper presents a review of relevant concepts related to the role of DTs in the achievement of a mass customization 4.0 environment, plus some proposals of how to address the identified research challenges. A future research agenda is proposed at the end of the paper.

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“…In manufacturing processes, simulation has mainly been applied to adjust the process schedule or visualize the workload balance of production lines [12][13][14]. Recently, however, the interest in CPS-linked simulation has increased [15][16][17]. In the garment industry, simulation is used for various purposes such as the analysis of sewing waiting time, production capacity, and line balancing considering the state of the line [18][19][20].…”

Section: Literature Reviewmentioning

confidence: 99%

Simulation-Based Hybrid Optimization Method for the Digital Twin of Garment Production Lines

Jung

Park²,

Lee³

et al. 2021

Journal of Computing and Information Science in Engineering

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Implementing digital transformation in the garment industry is very difficult, owing to its labor-intensive structural characteristics. Further, the productivity of a garment production system is considerably influenced by a combination of processes and operators. This study proposes a simulation-based hybrid optimization method to maximize the productivity of a garment production line. The simulation reflects the actual site characteristics, i.e., process and operator level indices, and the optimization process reflects constraints based on expert knowledge. The optimization process derives an optimal operator sequence through a genetic algorithm, and sequentially removes bottlenecks through workload analysis based on the results. The proposed simulation optimization method improved productivity by ∼67.4%, which is 52.3% higher than that obtained by the existing meta-heuristic algorithm. The correlation between workload and production was verified by analyzing the workload change trends. This study holds significance because it presents a new simulation-based optimization model that further applies the workload distribution method by eliminating bottlenecks and digitizing garment production lines.

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Simulation of Production Processes Involving Cyber-physical Systems

Cited by 24 publications

References 15 publications

The Impact of Industry 4.0 Technologies on Manufacturing Strategies: Proposition of Technology-Integrated Selection

The Impact of Industry 4.0 Technologies on Manufacturing Strategies: Proposition of Technology-Integrated Selection

Towards the Development of a Digital Twin for a Sustainable Mass Customization 4.0 Environment: A Literature Review of Relevant Concepts

Simulation-Based Hybrid Optimization Method for the Digital Twin of Garment Production Lines

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