An Efficiency Analysis Using Value Stream Mapping to the Supply Chain Management of Exporting Thai Pineapples to China
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Abstract
Supply chain management (SCM) for exporting Thai pineapples to China is a critical component of Thailand’s agricultural export sector. However, the export process faces significant challenges
due to inadequate communication and coordination among upstream and downstream actors. For example, farmers often lack close contractual relationships with factories, shippers, and dealers, which leads to problems with product quality, post-harvest handling, and damage during processing and transportation. The aim of this study was to analyze the Thai pineapple export supply chain to China with R3A route (Chiang Rai to Kunming) by using Value Stream Mapping (VSM). Data collection involved interviews and on-site observations with all stakeholders in the export process, such as farmers, trimming factory, shippings, customs and dealers from China. The interactions among these groups are critical for identifying and minimizing waste across the supply chain. The result of this study could identified 38 activities across the supply chain. The VSM results showed 5 activities, 10.70% were NVA, 30 activities 82.12% were NNVA, and 8 activities 7.18% were VA. The activities could be reduce time and improve efficiency was NVA and NNVA. For instance, dealers waiting time confirmation from factory 1,440 mins, waiting truck to load in pineapple farm 60 mins. The principles of lean manufacturing are applied through close communication, effective collaboration, and contract farming among farmers, trimming factories, and dealers. Lead times are thereby reduced, and the efficiency of supply chain management for Thai pineapple exports to China is enhanced.
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References
Arwatchananukul, S., Chaiwong, S., Charoenkwan, P., Punvichai, T., Chen, M., & Saengrayap, R. (2025). Classification of translucent flesh defects in phulae pineapples using stacking ensemble classifiers and deep neural networks. Applied Food Research, 5(2), 101460.
Carrijo, P. R. S., Rader, M. L. B., Batalha, M. O., Filho, G., (2024). Lean manufacturing in agriculture: adapting the value stream mapping approach for farm management, Volume 17, pages 1444–1468.
Dara, H. M., Raut, A., Adamu, M., Ibrahim, Y. E., & Ingle, P. V. (2024). Reducing non-value added (NVA) activities through lean tools for the precast industry. Heliyon, 10(7), e29148. https://doi.org/10.1016/J.HELIYON.2024.E29148
Ditkaew, K. (2022). The Effect of Lean Accounting Implementation on Organizational Performance. International Journal of Asian Business and Information Management, 13(1). https://doi.org/10.4018/IJABIM.309134
Ferreira, W. de P., Armellini, F., Santa-Eulalia, L. A. de, & Thomasset-Laperrière, V. (2022). Extending the lean value stream mapping to the context of Industry 4.0: An agent-based technology approach. Journal of Manufacturing Systems, 63, 1–14. https://doi.org/10.1016/J.JMSY.2022. 02.002
Heydarzade, A., Rezaei, N., Vaezi, S. A., & Camelio, J. A. (2025). Multi-layer multi-variable value stream mapping: A comprehensive framework across operational, environmental, and social layers with integrated KPIs interrelationships. Manufacturing Letters, 44, 184–194. https://doi.org/10.1016 /J.MFGLET.2025.06.023
Hossain, M. M., & Purdy, G. (2023). Integration of Industry 4.0 into Lean production systems: A systematic literature review. Manufacturing Letters, 35, 1347–1357. https://doi.org/10.1016/J.MFGLET.2023.08.098
Kongsuwan, A., Suthiluk, P., Theeppakorn, T. and Srilaong, V., 2009, Bioactive compounds and antioxidant capacities of phulae and nanglae pineapple, Asian Journal Of Food & Agro-industry. Special Issue, S44- S50.
Martins, A. D. O., Anjos, F. E. V., Silva, D. O. The Lean Farm: Application of Tools and Concepts of Lean Manufacturing in Agro-Pastoral Crops. Sustainability, Vol. 15(3), 2597
Melin, M., Barth, H. 2020. Value stream mapping for sustainable change at a Swedish dairy farm. Int. J. of Environment and Waste Management, Vol. 25, No. 1. P. 130-140.
Naeemah, A. J., & Wong, K. Y. (2023). Sustainability metrics and a hybrid decision-making model for selecting lean manufacturing tools. Resources, Environment and Sustainability, 13, 100120. https://doi.org/10.1016/J.RESENV.2023.100120
Phuangsubsin, C., Jantakard, H., & Vinitpittayakul, K. (2024). Risk Assessment of Sustainable Pineapple Supply Chain Management. In Thai Environmental Engineering Journal (Vol. 38, Issue 1).
Salano, N. E. C., Llinás, G. A. G., Torres, J. R. M. (2019). Towards the integration of lean principles and optimization for agricultural production systems: a conceptual review proposition. Vol. 100. Iss. 2. P. 453-464.
Touriki, F. E., Benkhati, I., Kamble, S. S., Belhadi, A., & El fezazi, S. (2021). An integrated smart, green, resilient, and lean manufacturing framework: A literature review and future research directions. Journal of Cleaner Production, 319, 128691. https://doi.org/10.1016/J.JCLEPRO.2021.128691