TY - GEN
T1 - E-Manufacturing Model Using Crowdsourcing Technologies for Production Efficiency in Railway Transport Manufacturing Companies in South Africa
AU - Bakam, Genevieve
AU - Mpofu, Khumbulani
AU - Mbohwa, Charles
N1 - Publisher Copyright:
© The Author(s), under exclusive license to Springer Nature Switzerland AG 2024.
PY - 2024
Y1 - 2024
N2 - Advanced manufacturing practices require smarter technologies such as crowdsourcing to enhance continuous production improvement. It happens that crowdfunding is more popular in South Africa compared to crowdsourcing especially in the manufacturing field due to the lack of technical expertise in engineering fields. Also, previous literature focused on smart factories and smart road transportation systems using industrial 4.0 initiatives without shedding light on the application of crowdsourcing and crowdsensing in railway manufacturing industries. This paper proposed a model for the e-manufacturing of trains using crowdsourcing technologies for production efficiency in railway transport manufacturing companies in South Africa. A systematic analysis based on synthetised literature and empirical evidence was employed to compile factors enabling crowdsourcing initiatives and to design a transformative crowdsourcing manufacturing (TCM) model. Findings showed that a well-defined manufacturing process, network collaborators, crowdsourcing platforms, crowdsourcing forms, systems communication and participation are core factors enabling crowdsourcing execution regarding well-designed trains and railway innovations in railway transportation systems. Despite the lack of public data sharing, cyberattacks, a less digitalized country and an uneducated crowd in South Africa, the proposed TCM model revealed that crowdsourcing is a problem-solving and decision-making tool that promotes productivity, efficient trains, effective booking and payment systems leading to passenger satisfaction, inclusive growth and sustainability. However, the South African government should define a conducive regulatory system and compatible network communication infrastructures that enable the deployment of crowdsourcing ingenuities to revitalise the railway transport system.
AB - Advanced manufacturing practices require smarter technologies such as crowdsourcing to enhance continuous production improvement. It happens that crowdfunding is more popular in South Africa compared to crowdsourcing especially in the manufacturing field due to the lack of technical expertise in engineering fields. Also, previous literature focused on smart factories and smart road transportation systems using industrial 4.0 initiatives without shedding light on the application of crowdsourcing and crowdsensing in railway manufacturing industries. This paper proposed a model for the e-manufacturing of trains using crowdsourcing technologies for production efficiency in railway transport manufacturing companies in South Africa. A systematic analysis based on synthetised literature and empirical evidence was employed to compile factors enabling crowdsourcing initiatives and to design a transformative crowdsourcing manufacturing (TCM) model. Findings showed that a well-defined manufacturing process, network collaborators, crowdsourcing platforms, crowdsourcing forms, systems communication and participation are core factors enabling crowdsourcing execution regarding well-designed trains and railway innovations in railway transportation systems. Despite the lack of public data sharing, cyberattacks, a less digitalized country and an uneducated crowd in South Africa, the proposed TCM model revealed that crowdsourcing is a problem-solving and decision-making tool that promotes productivity, efficient trains, effective booking and payment systems leading to passenger satisfaction, inclusive growth and sustainability. However, the South African government should define a conducive regulatory system and compatible network communication infrastructures that enable the deployment of crowdsourcing ingenuities to revitalise the railway transport system.
KW - Crowdsourcing
KW - E-manufacturing
KW - production efficiency
KW - transport system and South Africa
UR - http://www.scopus.com/inward/record.url?scp=85213301972&partnerID=8YFLogxK
U2 - 10.1007/978-3-031-74482-2_38
DO - 10.1007/978-3-031-74482-2_38
M3 - Conference contribution
AN - SCOPUS:85213301972
SN - 9783031744815
T3 - Lecture Notes in Mechanical Engineering
SP - 341
EP - 348
BT - Flexible Automation and Intelligent Manufacturing
A2 - Wang, Yi-Chi
A2 - Chan, Siu Hang
A2 - Wang, Zih-Huei
PB - Springer Science and Business Media Deutschland GmbH
T2 - 33rd International Conference on Flexible Automation and Intelligent Manufacturing, FAIM 2024
Y2 - 23 June 2024 through 26 June 2024
ER -