Framework for planning and implementation of Digital Process Twins in the field of internal logistics

Zuhr, Pascal; Rissmann, Lukas; Meißner, Sebastian

doi:10.1016/j.ifacol.2022.10.038

Cited by 3 publications

(2 citation statements)

References 10 publications

Supporting

Mentioning

Contrasting

Order By: Relevance

“…The advantage of this study in comparison with [2,[6][7][8][9][10][11]] is that the proposed evaluation methodology makes it possible to analyzed not only the technological, but also the financial impact of the digital twin technologies on the manufacturing plant. In comparison with the works [33, 34], the simulation is suitable to solve not only technological and logistics problems, but also financial aspects of technological improvement can be analyzed.…”

Section: Discussion Of Results Determining the Impact Of Digital Twin...mentioning

confidence: 99%

“…One of the most important achievement of a digital twin deployment project is to estimate the financial impact of the investment. A wide range of articles discusses the positive impact of digital twin applications in the field of automotive industry [5], food industry [6], agriculture [7], health care [8], logistics [9], facility management [10], but these researches are generally focusing on the performance indicators (lead time, efficiency, availability, capacity utilization, flexibility, productivity) and only a few of them analysis the financial impact. Based on this fact, research on the financial evaluation of Industry 4.0 technologies is important, especially in the case of expensive, integrated technological solutions, such as digital twin, where a wide range of state of the art technologies are applied to improve the flexibility and productivity of production systems.…”

Section: Introductionmentioning

confidence: 99%

See 1 more Smart Citation

Identification of influence of digital twin technologies on production systems: a return on investment-based approach

Banyai,

Kovacs

2023

EEJET

View full text Add to dashboard Cite

The object of this study is the impact of different digital twin solutions on the performance of job-shop manufacturing systems, while economic aspects are also taken into consideration. This paper proposes an approach to analyze the impact of different identification systems on the efficiency and ROI of digital twin deployment in production systems. In order to achieve this aim, let’s analyze the investment and operation cost of different Internet of Things technologies. The next phase of the research work was the definition of performance parameters, which makes it possible to analyze the impact of different digital twin solutions on the productivity of the job-shop manufacturing system. It is possible to choose four financial indicators to analyze the economic impact of digital twin solution on job-shop manufacturing: return on investment, compound annual growth rate, internal rate of return and net present value. Our approach is based on a novel agent-based simulation model using AnyLogic simulation tool. From the results of this productivity analyses, the model computes the financial indicators, which describe the expected financial impact of the investment and operation cost. It is compared the impact of barcodes and radiofrequency identification technologies on the financial and technological impact of the job-shop manufacturing environment. The numerical analysis of a job-shop manufacturing system shows, that the radiofrequency identification-based digital twin solution has 9.2 % higher return on investment, 53 % higher net present value and 1.6 % higher compound annual growth rate. The model can be easily converted to analyze other types of manufacturing systems, which can lead to increased efficiency of digital twin solutions

show abstract