Anpassungsintelligenz von Fabriken im dynamischen und komplexen Umfeld

Delbrügger, Tim; Döbbeler, Frederik; Graefenstein, Julian; Lager, Hendrik; Lenz, Lisa; Meißner, Matthias; Müller, Daniel B.; Regelmann, Philipp; Scholz, David; Schumacher, Christin; Winkels, Jan; Wirtz, Andreas; Zeidler, Felix

doi:10.3139/104.111731

Cited by 7 publications

(7 citation statements)

References 9 publications

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“…Besides the energy turnaround, which sets new challenges for industry, the surrounding of factories is becoming increasingly dynamic and complex [7]. For example, the lot size to be produced is becoming smaller and smaller.…”

Section: Introductionmentioning

confidence: 99%

Modeling the electrical power and energy consumption of automated guided vehicles to improve the energy efficiency of production systems

Meißner

Massalski

2020

Int J Adv Manuf Technol

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Due to the advancing energy system transformation and the increasingly complex and dynamic environment in which factories have to operate, the energy efficiency and flexible design of production systems are becoming more important. Since the use of automated guided vehicles is a promising approach to enhance the flexibility of intralogistics, their electrical power requirements are analyzed. Based on the measurement data obtained, different movement modules of an automated guided vehicle are identified and then modeled using physical laws. These movement modules are the translatory movement, rotary movement, and the lifting and lowering of the load-carrying platform. The measurement data show, for example, that the energy requirement for translational and rotational movement increases in relation to the payload weight. At the same time, however, it is also shown that an increase in speed of the automated guided vehicle leads to a lower energy requirement, although the power requirement grows. Consequently, one result is that an automated guided vehicle works most efficiently when the maximum payload is transported at the highest speed. With regard to the lifting and lowering of loads, the result is an increasing energy requirement depending on the payload weight. The comparison between the collected measurement data and the outcomes of the implemented simulation model shows only minor deviations. Thus, the implemented simulation model of automated guided vehicles can be used with regard to their electrical power consumption, for example, in production planning to comprehensively raise the energy efficiency of production systems.

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Section: Introductionmentioning

confidence: 99%

Modeling the electrical power and energy consumption of automated guided vehicles to improve the energy efficiency of production systems

Meißner

Massalski

2020

Int J Adv Manuf Technol

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“…By consolidating the objects with individual items of a bill of quantities, a model-based cost calculation can be automatically carried out. [20] Furthermore, the use of the BIM method offers the potential to optimize processes under consideration of the whole life cycle of a factory, such as supporting the factory adaptation process and its more efficient and faster implementation [5] With the purpose of make interdisciplinary planning more efficient, while taking factory planning and building planning into account, it is advisable to implement the modular planning approaches of the factory within building planning and combine them with the BIM method. Therefore, it is recommended to consider the components respectively objects of the building as modules.…”

Section: Figure 6: Separation Of Conventional Design and Constructionmentioning

confidence: 99%

“…Despite using new production technologies such as autonomous controlled AGVs or 3d printing for rapid prototyping or other solutions that become highly anticipated in the 4th industrial revolution, it is necessary to change the way companies plan their reconfiguration of the existing system in order to exploit crucial time benefits as a first step [5]. Time and costs are key factors in the reconfiguration process.…”

Section: Introductionmentioning

confidence: 99%

A Hybrid Approach of Modular Planning – Synchronizing Factory and Building Planning by Using Component based Synthesis

Graefenstein¹,

Winkels²,

Lenz³

et al. 2020

Proceedings of the Annual Hawaii International Conference on System Sciences

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The more and more rising complexity of the industrial environment is triggering companies in a way that is more challenging than ever before. Not only are factory planning projects difficult to handle because of the dynamics and complexity also the necessary planning of the accompanied building gets more and more difficult. To handle this complexity and reduce time and effort for planning as a major factor of success the mainly separately done planning aspects needs to be synchronized. This paper will show an approach of a hybrid factory-building planning method in order to be able to shorten planning time and effort. By using a constraint solving technique the necessary planning tasks are aligned partly automatically and will be processed as a useful planning workflow in form of a gantt diagram for the overall project management.

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“…Increasing uncertainty resulting from higher individualization levels, shorter product life cycles and fluctuating market demand leads to greater product and market complexity, to which companies must constantly adapt in order to survive. High dynamics and intensity of changes call for a short-term adaptability which in turn requires a holistic interoperability of production equipment, products, value chains and business processes [1][2][3]. Existing production concepts in industrial manufacturing have not yet been able to satisfy these requirements [2,4,5].…”

Section: Introductionmentioning

confidence: 99%

“…High dynamics and intensity of changes call for a short-term adaptability which in turn requires a holistic interoperability of production equipment, products, value chains and business processes [1][2][3]. Existing production concepts in industrial manufacturing have not yet been able to satisfy these requirements [2,4,5].…”

Section: Introductionmentioning

confidence: 99%

Business Model Innovation in Manufacturing Equipment Companies

2021

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Higher individualization levels, shorter product life cycles and fluctuating market demand influence manufacturing environments considerably, leading for example to a greater planning complexity and more frequent reconfiguration of production equipment and systems. These factors generate high nonvalue-added production costs that reduce factory adaptability.In this context, automobile manufacturers demand a reduction in installation and integration activities that allow for an increase in the versatility of their production facilities. Business model innovations are hence required for manufacturing equipment suppliers to meet their customers' demands and stay competitive in the long term.This paper identifies promising approaches for manufacturing business model innovation, including preliminary assessment within the research campus ARENA2036. The approaches lead to alternative business models that represent a possible way out of the conventional business dynamics between automobile manufacturers and their equipment suppliers, currently inhibiting innovation towards more flexible production systems.

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Anpassungsintelligenz von Fabriken im dynamischen und komplexen Umfeld

Cited by 7 publications

References 9 publications

Modeling the electrical power and energy consumption of automated guided vehicles to improve the energy efficiency of production systems

Modeling the electrical power and energy consumption of automated guided vehicles to improve the energy efficiency of production systems

A Hybrid Approach of Modular Planning – Synchronizing Factory and Building Planning by Using Component based Synthesis

Business Model Innovation in Manufacturing Equipment Companies

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