Skip to main content
SpringerLink
Log in

A digital modeling framework for the motorcycle industry with advanced computer design

  • Focus
  • Published:
Soft Computing Aims and scope Submit manuscript

Abstract

A digital modeling framework for motorcycles (DMF) involves applying advanced computer design, computer-assisted analysis, and computer-assisted development. Data processing technology simulated prototype product, fast prototype technology, standard technology, etc. It is an interdisciplinary, systematic technology in the entire process of product design, production, and manufacture. DMF solves single-model production and constrained capacity building to satisfy the industry's demand for individual and diverse motorcycle goods. DMF sets forward several approaches within it, including parametric technologies for design, technology dependent on experience, design application, and data integration trends. The DMF provides the basis for a synthesis of motorcycles' production and demand. The result illustrates that digital concept strategies and approaches can be used in the motorcycle industry in reality with the highest efficiency (97.32%), emission rate (25.16%), speed rate (95.23%), exhaust rate (41.32%), heat loss rate (6.18%), performance metrics rate (9.32%), and error rate (5.44%), compared to other popular methods. For the 100 motorcycles, the average charging capacity, speed, distance traveled, and implementation cost ratio are observed at 97.11%, 85–100 km/h, 80–100 km, and 9.32%, respectively.

This is a preview of subscription content, log in via an institution to check access.

Access this article

Log in via an institution

Price excludes VAT (USA)
Tax calculation will be finalised during checkout.

Instant access to the full article PDF.

Institutional subscriptions

Fig. 1
Fig. 2
Fig. 3
Fig. 4
Fig. 5
Fig. 6
Fig. 7
Fig. 8
Fig. 9
Fig. 10

Similar content being viewed by others

References

  • Alazab M (2020) Cyber security researcher and practitioner with industry and academic experience. Cybernomics 2(1):56–56

    Google Scholar 

  • Balaanand M, Karthikeyan N, Karthik S (2020) Designing a framework for communal software: based on the assessment using relation modeling. Int J Parallel Prog 48(2):329–343

    Article  Google Scholar 

  • Cai W, Lai KH, Liu C, Wei F, Ma M, Jia S et al (2019) Promoting the sustainability of the manufacturing industry through lean energy-saving and emission-reduction strategy. Sci Total Environ 665:23–32

    Article  Google Scholar 

  • Capriglione D, Carratu M, Pietrosanto A, Sommella P (2019) Online fault detection of rear stroke suspension sensor in a motorcycle. IEEE Trans Instrum Meas 68(5):1362–1372

    Article  Google Scholar 

  • Caraballo SC, Fernandez RA (2020) A performance-based design framework for enhancing decision-making at the conceptual phase of a motorcycle rear suspension development. Optim Eng 21(4):1283–1317

    Article  Google Scholar 

  • Farid A, Ksaibati K (2021) Modeling severities of motorcycle crashes using random parameters. J Traff Transp Eng (English Edition) 8(2):225–236

    Article  Google Scholar 

  • Fischer D, Harbrecht A, Surmann A, McKenna R (2019) Electric vehicles’ impacts on residential electric local profiles—a stochastic modeling approach considering socio-economic, behavioural and spatial factors. Appl Energy 233:644–658

    Article  Google Scholar 

  • Frizziero L, Liverani A, Nannini L (2019) Design for six sigma (DFSS) applied to a new eco-motorbike. Machines 7(3):52

    Article  Google Scholar 

  • Gao X, Lee GM (2019) Moment-based rental prediction for bicycle-sharing transportation systems using a hybrid genetic algorithm and machine learning. Comput Ind Eng 128:60–69

    Article  Google Scholar 

  • Huang HB, Wu JH, Huang XR, Yang ML, Ding WP (2020) A generalized inverse cascade method to identify and optimize vehicle interior noise sources. J Sound Vib 467:115062

    Article  Google Scholar 

  • Jin JG, Nieto H, Lu L (2020) Robust bike-sharing stations allocation and path network design: a two-stage stochastic programming model. Transp Lett 12(10):682–691

    Article  Google Scholar 

  • Julsrud TE, Farstad E (2020) Car sharing and transformations in households travel patterns: insights from emerging proto-practices in Norway. Energy Res Soc Sci 66:101497

    Article  Google Scholar 

  • Kumar A, Abhishek K, Nerurkar P, Ghalib MR, Shankar A, Cheng X (2020) Secure smart contracts for cloud-based manufacturing using Ethereum blockchain. Trans Emerg Telecommun Technol. https://doi.org/10.1002/ett.4129

    Article  Google Scholar 

  • Leach F, Kalghatgi G, Stone R, Miles P (2020) The scope for improving the efficiency and environmental impact of internal combustion engines. Transp Eng 1:100005

    Article  Google Scholar 

  • Li J, Dai B, Li X, Xu X, Liu D (2019) A dynamic Bayesian network for vehicle maneuver prediction in highway driving scenarios: framework and verification. Electronics 8(1):40

    Article  Google Scholar 

  • Liu C, Wang G, Zhou H, Mei Y, Li Y, Li Y, Zhang L (2020) Design of two-wheeled motorcycle tire crown contour bioinspired by cat paw pads. Appl Bionics Biomech. https://doi.org/10.1155/2020/8898413

    Article  Google Scholar 

  • Liu Y, Zhang J, Li Y, Hansen P, Wang J (2021) Human–computer collaborative interaction design of intelligent vehicle—a case study of HMI of adaptive cruise control

  • Molano JIR, Lovelle JMC, Montenegro CE, Granados JJR, Crespo RG (2018) Metamodel for integration of internet of things, social networks, the cloud and industry 4.0. J Ambient Intell Hum Comput 9(3):709–723

    Article  Google Scholar 

  • Polanía-Restrepo S, Jaramillo-González S, Osorio-Gómez G (2020) Electric hybridization kit for modification of a manual transmission motorcycle. Int J Interact Des Manuf IJIDeM. https://doi.org/10.1007/s12008-020-00649-w

    Article  Google Scholar 

  • Purwanto K, Hariadi TK, Muhtar MY (2019) Microcontroller-based RFID, GSM and GPS for motorcycle security system. Int J Adv Comput Sci Appl 10(3):447–451

    Google Scholar 

  • Sornalakshmi M, Balamurali S, Venkatesulu M, Navaneetha Krishnan M, Ramasamy LK, Kadry S et al (2020) Hybrid method for mining rules based on enhanced Apriori algorithm with minimal sequential optimization in healthcare industry. Neural Comput Appl. https://doi.org/10.1007/s00521-020-04862-2

    Article  Google Scholar 

  • Spanoudakis P, Christenas E, Tsourveloudis NC (2020) Design and structural analysis of a front single-sided swingarm for an electric three-wheel motorcycle. Appl Sci 10(17):6063

    Article  Google Scholar 

  • Trianni A, Cagno E, Accordini D (2019) Energy efficiency measures in electric motors systems: a novel classification highlighting specific implications in their adoption. Appl Energy 252:113481

    Article  Google Scholar 

  • Wu HC, Ai CH, Chang YY (2021) What drives experiential sharing intentions towards motorcycle touring? The case of Taiwan. J China Tour Res 17(1):90–119

    Article  Google Scholar 

  • Xiao H, Muthu B, Kadry SN (2020) Artificial intelligence with robotics for the advanced manufacturing industry using robot-assisted mixed-integer programming model. Intell Serv Robot 1–10

  • Xu X, Han M, Nagarajan SM, Anandhan P (2020) Industrial Internet of Things for smart manufacturing applications using hierarchical trustful resource assignment. Comput Commun 160:423–430

    Article  Google Scholar 

  • Zhang K, Chen Y, Li C (2019) Discovering the tourists’ behaviours and perceptions in a tourism destination by analyzing photos’ visual content with a computer deep learning model: the case of Beijing. Tour Manag 75:595–608

    Article  Google Scholar 

Download references

Funding

This research was supported by the National Key R&D Program of China (Grant No. 2019YFE0197000).

Author information

Authors and Affiliations

  1. Weifang University of Science and Technology, Weifang, 262700, Shandong, China

    Ping Wang & Youxiang Zhang

  2. Zhejiang ChuangTai Motorcycle Co., Ltd, Taizhou, 318020, Zhejiang, China

    Ping Wang, Jianghong Li, Qiang Su & Changqun Shen

  3. Weifang Key Lab of Advanced Light Materials Manufacturing and Forming, Weifang University of Science and Technology, Weifang, 262700, Shandong, China

    Xiufeng Tan & Guanqin Wang

Authors
  1. Ping Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  2. Xiufeng Tan
    View author publications

    You can also search for this author in PubMed Google Scholar

  3. Guanqin Wang
    View author publications

    You can also search for this author in PubMed Google Scholar

  4. Jianghong Li
    View author publications

    You can also search for this author in PubMed Google Scholar

  5. Qiang Su
    View author publications

    You can also search for this author in PubMed Google Scholar

  6. Changqun Shen
    View author publications

    You can also search for this author in PubMed Google Scholar

  7. Youxiang Zhang
    View author publications

    You can also search for this author in PubMed Google Scholar

Contributions

All the authors reviewed and approved the paper for submission. PW, XT, GW, JL, QS, CS, and YZ have contributed to the paper in terms of framework modeling, strategizing according to the analysis, and illustrating a highly efficient approach.

Corresponding author

Correspondence to Youxiang Zhang.

Ethics declarations

Conflict of interest

There is none to declare.

Additional information

Communicated by Soft computing in decision making and in modeling in economics.

Publisher's Note

Springer Nature remains neutral with regard to jurisdictional claims in published maps and institutional affiliations.

Rights and permissions

Reprints and permissions

About this article

Check for updates. Verify currency and authenticity via CrossMark

Cite this article

Wang, P., Tan, X., Wang, G. et al. A digital modeling framework for the motorcycle industry with advanced computer design. Soft Comput 25, 12465–12476 (2021). https://doi.org/10.1007/s00500-021-05966-0

Download citation

  • Accepted:

  • Published:

  • Issue Date:

  • DOI: https://doi.org/10.1007/s00500-021-05966-0

Keywords

Search

Navigation