@article{Sriviboon2025,

title = {A gamification training system designed according to a mental model structure: A case study of universal robots},

author = {Yada Sriviboon and Arisara Jiamsanguanwong and Parames Chutima and Oran Kittithreerapronchai},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105022936760&doi=10.1038%2fs41598-025-27670-x&partnerID=40&md5=f9365896439f79e1bac5b3fb328bf14e},

doi = {10.1038/s41598-025-27670-x},

year  = {2025},

date = {2025-01-01},

journal = {Scientific Reports},

volume = {15},

number = {1},

note = {Cited by: 0; All Open Access, Gold Open Access, Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Chinwattanawongwan2025,

title = {Granule Moisture Content Prediction During Fluid Bed Drying},

author = {Paloch Chinwattanawongwan and Narueporn Sutanthavibul and Oran Kittithreerapronchai},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105013285548&doi=10.1208%2fs12249-025-03207-3&partnerID=40&md5=9fc2129426896346c304bb2d654cd323},

doi = {10.1208/s12249-025-03207-3},

year  = {2025},

date = {2025-01-01},

journal = {AAPS PharmSciTech},

volume = {26},

number = {7},

note = {Cited by: 0},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Jiamsanguanwong2025,

title = {Redesigning Telemedicine for Traditional Chinese Medicine: Service Design Approach to Digital Transformation},

author = {Arisara Jiamsanguanwong and Romanee Luo and Ratchapoom Kaingam and Oran Kittithreerapronchai and Waratta Authayarat},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-105025999978&doi=10.2196%2f76752&partnerID=40&md5=81b680f4bf9c99659ef37f40cce4c729},

doi = {10.2196/76752},

year  = {2025},

date = {2025-01-01},

journal = {JMIR Human Factors},

volume = {12},

note = {Cited by: 0; All Open Access, Gold Open Access, Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Chinajitphan2024,

title = {Implementation of good distribution practice in a Thai pharmaceutical manufacturer},

author = {Pana Chinajitphan and Oran Kittithreerapronchai},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85212529083&doi=10.69598%2fsehs.18.24040003&partnerID=40&md5=667515602185f1355312d522b8705608},

doi = {10.69598/sehs.18.24040003},

year  = {2024},

date = {2024-01-01},

journal = {Science, Engineering and Health Studies},

volume = {18},

note = {Cited by: 0; All Open Access, Gold Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Pararug2024,

title = {Robust design space of compression parameters for initial and reprocessed granules},

author = {Supanat Pararug and Jittima Chatchawalsaisin and Oran Kittithreerapronchai},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85197078699&doi=10.1016%2fj.jddst.2024.105888&partnerID=40&md5=beb495dd263205a80a0aa929adbdf3a6},

doi = {10.1016/j.jddst.2024.105888},

year  = {2024},

date = {2024-01-01},

journal = {Journal of Drug Delivery Science and Technology},

volume = {98},

note = {Cited by: 0},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Jiamsanguanwong202351,

title = {Improving patients’ experience concerning insufficient informational flow to patients during COVID-19 pandemic: Case study of a traditional Chinese medicine clinic},

author = {Arisara Jiamsanguanwong and Chayapol Ophaswongse and Chaianan Chansirinthorn and Narun Kitirattragarn and Oran Kittithreerapronchai},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85132675098&doi=10.1080%2f20479700.2022.2071801&partnerID=40&md5=ed6738e77e5a1e887e7d3e8540a184f2},

doi = {10.1080/20479700.2022.2071801},

year  = {2023},

date = {2023-01-01},

journal = {International Journal of Healthcare Management},

volume = {16},

number = {1},

pages = {51 – 60},

publisher = {Taylor and Francis Ltd.},

abstract = {Objective: To improve patients’ experience concerning insufficient informational flow to patients waiting at the dispensary station–case study of a traditional Chinese medicine clinic. Method: The service system was explored via qualitative techniques such as interviews and constructing the customer journey map. Then, experience and operational issues were defined through experience ratings at each touchpoint, patient interviews, and root cause analysis. The solution was identified via brainstorming and prototyping. A prescription tracking system was proposed with a finish time estimation algorithm. Results: The overall satisfaction score at the dispensary station, comparing before-after system implementation in 2019, was increased 37% from the average score of 3.27 to 4.47 using 5-point Likert scales. The mean absolute percentage error (MAPE) of the waiting time estimation model that included the buffer time (upper bound at 95%) is 52%. Conclusion: This methodology, which included both patient experience and operational improvement viewpoints, could successfully improve both the patient experience and the related operation system at its critical touchpoints. Moreover, the data from the prescription tracking system could be used to estimate the number of patients waiting in the system, allowing the clinic to better manage its waiting space and capacity during the COVID-19 pandemic. © 2022 Informa UK Limited, trading as Taylor & Francis Group.},

note = {Cited by: 2},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Thongdonnoi202393,

title = {Application of Collaborative Robots for Increasing Productivity in an Eyeglasses Lenses Manufacturer},

author = {Chanatip Thongdonnoi and Parames Chutima and Arisara Jiamsanguanwong and Oran Kittithreerapronchai and Manida Swangnetr Neubert},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85176564994&doi=10.4186%2fej.2023.27.10.93&partnerID=40&md5=1468211c0a610031cb1d733f3ae0e50e},

doi = {10.4186/ej.2023.27.10.93},

year  = {2023},

date = {2023-01-01},

journal = {Engineering Journal},

volume = {27},

number = {10},

pages = {93 – 112},

publisher = {Chulalongkorn University, Faculty of Fine and Applied Arts},

abstract = {This research focuses on a framework for making decisions when adopting collaborative robots (cobots) to collaborate with or replace human workers. Top management at a real-life case study firm that manufactures a variety of eyeglasses lenses wants to implement cobots in the sorting process since such a repetitive task has been shown to have a significant negative influence on workers' ergonomic ailments. Its current procurement decision-making process focuses solely on financial perspectives without taking into account any other significant criteria. Therefore, the purpose of this study is to investigate the elements that are crucial in deciding whether to use cobots in manufacturing lines., Multivariate statistical methods, comprising the exploratory factor analysis (EFA) and confirmatory factor analysis (CFA), are applied to analyse the elements that are associated with the latent variables such as safety, ergonomics, productivity, quality, system, internal organisation and external organisation. In addition, alternative deployments of cobots in the case study are validated through the ARENA simulation software. More specifically, the results showed that using cobots in the workplace might boost output while lowering WIP, waiting times, the number of tasks in queue, and the workforce. In addition, cobots may reduce employee ergonomic risk and enhance workplace safety. © 2023, Chulalongkorn University, Faculty of Fine and Applied Arts. All rights reserved.},

note = {Cited by: 5; All Open Access, Gold Open Access, Green Open Access},

keywords = {},

pubstate = {published},

tppubtype = {article}

}

@article{Chamnanthongpaivanh20221235,

title = {Artificial Neural Network and Support Vector Regression Modeling for Prediction of Mixing Time in Wet Granulation},

author = {Boonyasith Chamnanthongpaivanh and Jittima Chatchawalsaisin and Oran Kittithreerapronchai},

url = {https://www.scopus.com/inward/record.uri?eid=2-s2.0-85119194031&doi=10.1007%2fs12247-021-09597-8&partnerID=40&md5=e9cffff1ba51fad2d86e6acb7fce3e79},

doi = {10.1007/s12247-021-09597-8},

year  = {2022},

date = {2022-01-01},

journal = {Journal of Pharmaceutical Innovation},

volume = {17},

number = {4},

pages = {1235 – 1246},

note = {Cited by: 2},

keywords = {},

pubstate = {published},

tppubtype = {article}

}