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Faculty Member

Pisal Yenradee.jpg

DR. PISAL YENRADEE
(ASSOCIATE PROFESSOR)

CONTACT

pisal@siit.tu.ac.th

+66-2-986-9009, +66-2-986-9101, +66-2-564-3226

Phone Extension: 2107

EDUCATION

  • B.Eng. (1st Class Honors) in Production Engineering, King Mongkut s Institute of Technology North Bangkok, Thailand

  • M.Eng. in Industrial Engineering and Management, Asian Institute of Technology (AIT), Thailand

  • D.Eng. in Industrial Engineering and Management, Asian Institute of Technology (AIT), Thailand

WORK EXPERIENCES

  • 1993-Present: SIIT

  • 2000-2004: Assistant Director for Special Affairs, SIIT

  • 1997-1999: Deputy Chairperson, Department of Industrial Engineering, SIIT

  • 1995-1996: Chairperson, Department of Industrial Engineering, SIIT

  • 1992: Associated Faculty, Industrial Engineering, Faculty of Engineering, Thammasat University

  • 1992: Consultant, Tanin Union Industries Co., Ltd., Thailand

  • 1989: Management Trainee, Lever Brothers Co., Ltd., Thailand

 

    Teaching Courses

 

  • Operations Research I

  • Industrial Plant Design

  • Engineering Management

  • Material Management and Inventory Control

ACADEMIC AWARDS

  • Government of Germany Scholarship for Master's Degree at Asian Institute of Technology (June 1987 - Dec. 1988)

  • Government of Japan Scholarship for Doctoral Degree at Asian Institute of Technology (Jan. 1990 - Dec. 1992)

  • First Prize: Aggregate Production Planning, Master Production Scheduling, and Material Requirement Planning in a Garment Factory, Industrial Engineering Senior Project Contest 2005-2006, organized by Industrial Engineering Academic Committee, The Engineering Institute of Thailand Under H.M. The King s Patronage (E.I.T.), February 2006. (the award is received on behalf of a senior project advisor of B. Eng. students).

  • First Prize: Thai Small- to Medium-Sized Industries Production Planning and Inventory Control Software, Industrial Application Software Contest: Student Category, organized by Industrial Promotion Department, Ministry of Industry, and Institute of Electric and Electronics, December 19, 2003 (the award is received on behalf of a thesis advisor of Ph.D. student).

  • Consolation Prize: Application of Theory of Constraints in a flexible job shop, Best Practices of Industrial Engineering Technique Awards 2004-2005, organized by Industrial Engineering Academic Committee, Engineering Institute of Thailand, April 29, 2004 (the award is received on behalf of a thesis advisor of M. Eng. student).

RESEARCH AREAS

  • Production and Inventory control (P&IC) systems, JIT, MRP, and TOC; P&IC systems for Thai industries; P&IC in supply chain, Applied operations research; Systems simulation.

RESEARCH INTERESTS

  • Small- to medium-sized industries (SMIs) in Thailand face considerable production and inventory control (P&IC) problems. These problems greatly deteriorate the manufacturing competitiveness of SMIs. In order to alleviate the problems, their characteristics and causes should be analyzed. Some causes of the problems are manageable while others are non-manageable. The non-manageable problems must be considered as constraints for developing the P&IC systems. The P&IC systems suitable for the SMIs in Thailand should be developed based on these constraints. Particular research topics in this research area are listed as follows:

​

    Analyses of Production and Inventory Control Problems in Thai Industries

​

  • There are various possible problems related to the production and inventory control (P&IC) systems in Thai industries. The nature, characteristics, and causes of such problems should be known in order to design an appropriate P&IC system or to improve the performance of the system. This research aims to identify the characteristics and also real causes of the encountered P&IC problems in Thai industries using an interview survey and case studies.

​

    Guideline or Methodology for Developing the Appropriate P&IC System for Thai Industries

​

  • It is reasonable to assume that the situation of industries in developed and developing countries are different. Therefore, the P&IC systems widely used in developed countries, for example, Just-in-Time, MRP, and TOC (Theory of Constraints) may not be suitable for Thai industries. An entirely new system or a modification of certain existing systems may be required by Thai industries. This research aims to recommend P&IC techniques or systems suitable for Thai industries by focusing on aggregate planning, master production scheduling, detailed production and purchasing scheduling, and shop floor control.

LIST OF PUBLICATIONS

Pannakkong, W., Vinh, V. T., Tuyen, N. N. M., & Buddhakulsomsiri, J. (2023). A Reinforcement Learning Approach for Ensemble Machine Learning Models in Peak Electricity Forecasting. Energies, 16(13), 5099.

 

Ji, J., Pannakkong, W., & Buddhakulsomsiri, J. (2023). A Computer Vision-Based System for Metal Sheet Pick Counting. Computers, Materials & Continua, 75(2).

 

Aswanuwath, L., Pannakkong, W., Buddhakulsomsiri, J., Karnjana, J., & Huynh, V. N. (2023). A Hybrid Model of VMD-EMD-FFT, Similar Days Selection Method, Stepwise Regression, and Artificial Neural Network for Daily Electricity Peak Load Forecasting. Energies, 16(4), 1860.

 

Duc, N. T. T., Buddhakulsomsiri, J., & Tai, P. D. (2023). A Mathematical Model for the Integrated Problem of Production Network Design and Inventory Positioning. Available at SSRN 4516180.

 

Ji, J., Pannakkong, W., & Buddhakulsomsiri, J. (2022). A Computer Vision-Based Model for Automatic Motion Time Study. Computers, Materials & Continua, 73(2).

 

Tai, P. D., Buddhakulsomsiri, J., & Duc, T. T. H. (2022). Revisiting measurement of compound bullwhip with asymmetric reference price. Computers & Industrial Engineering, 172, 108510.

 

Duc, N. T. T., Tai, P. D., & Buddhakulsomsiri, J. (2022). Inventory Positioning in Supply Chain Network: A Service-Oriented Approach. IEEE Access, 10, 92986-93002.

 

Tai, P. D., Duc, T. T. H., & Buddhakulsomsiri, J. (2022). Value of information sharing in supply chain under promotional competition. International Transactions in Operational Research, 29(4), 2649-2681.

 

Pannakkong, W., Parthanadee, P., & Buddhakulsomsiri, J. (2022). Impacts of harvesting age and pricing schemes on economic sustainability of cassava farmers in Thailand under market uncertainty. Sustainability, 14(13), 7768.

 

Pannakkong, W., Harncharnchai, T., & Buddhakulsomsiri, J. (2022). Forecasting daily electricity consumption in Thailand using regression, artificial neural network, support vector machine, and hybrid models. Energies, 15(9), 3105.

 

Duc, N. T. T., Tai, P. D., & Buddhakulsomsiri, J. (2022). A Markovian approach to modeling a periodic order‐up‐to‐level policy under stochastic discrete demand and lead time with lost sales. International Transactions in Operational Research, 29(2), 1132-1158.

 

Pannakkong, W., Thiwa-Anont, K., Singthong, K., Parthanadee, P., & Buddhakulsomsiri, J. (2022). Hyperparameter tuning of machine learning algorithms using response surface methodology: a case study of ANN, SVM, and DBN. Mathematical problems in engineering, 2022, 1-17.

 

Tivattanasuk, A., & Buddhakulsomsiri, J. (2022). Estimate optimal warehouse design for the beverage distribution center (Doctoral dissertation, Thammasat University).

 

Siriapichart, S., Buddhakulsomsiri, J., & Tai, P. D. (2022). Model for vehicle routing problem with loaded distance by clustering algorithm (Doctoral dissertation, Thammasat University).

 

Boonsem, T., Pannakkong, W., & Buddhakulsomsiri, J. (2022). Surface defect detection in lime by using computer vision (Doctoral dissertation, Thammasat University).

 

Singha, K., Buddhakulsomsiri, J., & Parthanadee, P. (2022). A two-stage method to determine parameters of (R, Q) inventory policy with storage capacity for a single item and multiple items. International Journal of Logistics Systems and Management, 43(3), 366-394.

 

Pham, T. D., Sahasoontaravuti, S., & Buddhakulsomsiri, J. (2022). Determining (s, S) Inventory Policy for Healthcare System: A Case Study of a Hospital in Thailand. International Journal of Knowledge and Systems Science (IJKSS), 13(1), 1-18.

 

Jinawat, K., Tai, P. D., & Buddhakulsomsiri, J. (2021). A bi-objective model for determining an optimal warehouse capacity, and product allocation in a green multi-product, multi-period distribution network. International Journal of Applied Research in Management and Economics, 4(3), 63-72.

 

Leelertkij, T., Parthanadee, P., & Buddhakulsomsiri, J. (2021). Vehicle routing problem with transshipment: mathematical model and algorithm. Journal of Advanced Transportation, 2021, 1-15.

 

Vinh, V. T., Pannakkong, W., & Buddhakulsomsiri, J. (2021). Implement tuned reinforcement learning in selecting different machine learning models prediction for peak electricity consumption (Doctoral dissertation, Thammasat University).

 

Kitsomcheep, B., & Buddhakulsomsiri, J. (2021). Market basket analysis of drug store in seasonal period (Doctoral dissertation, Thammasat University).

 

Chaiwong, N., Pannakkong, W., & Buddhakulsomsiri, J. (2021). Classifying saleability of lime by using convolutional neural network (CNN) approach (Doctoral dissertation, Thammasat University).

 

Sadibhakdi, P., & Buddhakulsomsiri, J. (2021). Market basket analysis of drugs stores in a monthly period (Doctoral dissertation, Thammasat University).

 

Doungploy, W., & Buddhakulsomsiri, J. (2021). Inventory optimization with (S, s) policy and partial backlog under stochastic discrete demand and lead time (Doctoral dissertation, Thammasat University).

 

Kittitharayada, P., Buddhakulsomsiri, J., & Pannakkong, W. (2021). Using design of experiments during the process of tuning hyperparameters in machine learning algorithms(Doctoral dissertation, Thammasat University).

 

Klaisangh, P., & Buddhakulsomsiri, J. (2021). Canned fruit brix prediction using machine learning using deep neural network (Doctoral dissertation, Thammasat University).

 

Akrajittham, S., Tai, P. D., & Buddhakulsomsiri, J. (2021). Vehicle route problem in cold chain logistics (Doctoral dissertation, Thammasat University).

 

Harncharnchai, T., & Buddhakulsomsiri, J. (2021). Prediction daily electricity consumption in Thailand using multiple linear regression, artificial neural network, support vector machine, and hybrid models (Doctoral dissertation, Thammasat University).

 

Sahasoontaravuti, M. S., & Buddhakulsomsiri, J. (2021). Determining (s, S) inventory policy for health care system: a case study of hospital in Thailand (Doctoral dissertation, Thammasat University).

 

Jeenanunta, C., Kongtarat, V., & Buddhakulsomsiri, J. (2021). A simulation-optimisation approach to determine optimal order-up-to level for inventory system with long lead time. International Journal of Logistics Systems and Management, 38(2), 253-276.

 

Tai, P., Huyen, P., & Buddhakulsomsiri, J. (2021). A novel modeling approach for a capacitated (S, T) inventory system with backlog under stochastic discrete demand and lead time. International Journal of Industrial Engineering Computations, 12(1), 1-14.

 

Maitreesorasuntee, C., Jeenanunta, C., Buddhakulsomsiri, J., Pannakkong, W., Chaysiri, R., Masahiro, N., & Karnjana, J. (2020). A Steel Tube Production Planning and Scheduling with Product-Dependent Changeover Time Using Digital Twin. INTERNATIONAL SCIENTIFIC JOURNAL OF ENGINEERING AND TECHNOLOGY (ISJET), 4(2), 13-19.

 

Duc, N. T. T., Tai, P. D., & Buddhakulsomsiri, J. (2020, April). Approximating Measures of Performance of a Periodic Review Inventory System by Using Markov Chain. In 2020 IEEE 7th International Conference on Industrial Engineering and Applications (ICIEA) (pp. 543-547). IEEE.

 

Kongsri, P., & Buddhakulsomsiri, J. (2020, April). A mixed integer programming model for unrelated parallel machine scheduling problem with sequence dependent setup time to minimize makespan and total tardiness. In 2020 IEEE 7th International Conference on Industrial Engineering and Applications (ICIEA) (pp. 605-609). IEEE.

 

Thiwa-anont, K., Buddhakulsomsiri, J., & Pannakkong, W. (2020, April). Raw Material Characteristic Prediction for Packing Media Preparation in Canned Pineapple Production Line. In 2020 IEEE 7th International Conference on Industrial Engineering and Applications (ICIEA) (pp. 350-354). IEEE.

 

Thy, N. N. A., Buddhakulsomsiri, J., & Parthanadee, P. (2020, April). A mathematical model for optimizing organic feed mix problem. In 2020 IEEE 7th International Conference on Industrial Engineering and Applications (ICIEA) (pp. 570-573). IEEE.

 

Sudmee, M. P., & Buddhakulsomsiri, J. (2020). Optimization for cold chain management in northern Thailand: a case study in sweet corn supply chain (Doctoral dissertation, Thammasat University).

 

Thianthong, A., & Buddhakulsomsiri, J. (2020). Survey study on supply chain disruption from COVID-19 (Doctoral dissertation, Thammasat University).

 

Thiensiri, M. P., & Buddhakulsomsiri, J. (2020). Optimization of fruit cold chain management: a case study of mayongchid supply chain in central Thailand (Doctoral dissertation, Thammasat University).

 

Kongsri, M. P., & Buddhakulsomsiri, J. (2020). Dynamic dispatching rule based-heuristics for unrelated parallel machine scheduling problem with machine and sequence-dependent setup time (Doctoral dissertation, Thammasat University).

 

Sinlapachai, M., & Buddhakulsomsiri, J. (2020). Market basket analysis using association rule in drug and health store (Doctoral dissertation, Thammasat University).

 

Jiaranaicharoen, C., & Buddhakulsomsiri, J. (2020). Optimization for cold chain management in eastern Thailand: a case study in mangosteen supply chain (Doctoral dissertation, Thammasat University).

 

Singthong, K., & Buddhakulsomsiri, J. (2020). Forecasting using artificial intelligence or machine learning algorithm (Doctoral dissertation, Thammasat University).

 

Nittayawan, J., & Buddhakulsomsiri, J. (2020). Market basket analysis in retails: study on the promotional pricing effect on frequent itemsets against demand elasticity in a retail store (Doctoral dissertation, Thammasat University).

 

Samatiat, M. S., & Buddhakulsomsiri, J. (2020). Optimization of fruit cold chain management: a case study of mangosteen supply chain in southern Thailand (Doctoral dissertation, Thammasat University).

 

Tanutammakun, M. S., & Buddhakulsomsiri, J. (2020). Car damage classification for car insurance company by using Colab with convolutional neural networks deep learning method (No. 181816). Thammasat University.

 

Thiwa-anont, K., & Buddhakulsomsiri, J. (2020). Predictive machine learning models for packing media preparation in canned pineapple production process (Doctoral dissertation, Thammasat University).

 

Intaruk, M. R., & Buddhakulsomsiri, J. (2020). Optimization of fruit cold chain management: a case study of coconut supply chain in western Thailand (Doctoral dissertation, Thammasat University).

 

Ji, J., Pannakkong, W., Tai, P. D., Jeenanunta, C., & Buddhakulsomsiri, J. (2020). Motion time study with convolutional neural network. In Integrated Uncertainty in Knowledge Modelling and Decision Making: 8th International Symposium, IUKM 2020, Phuket, Thailand, November 11–13, 2020, Proceedings 8 (pp. 249-258). Springer International Publishing.

 

Tai, P. D., Duc, T. T. H., & Buddhakulsomsiri, J. (2019, December). Information Sharing with Multiple Customer Segmentations. In 2019 IEEE International Conference on Industrial Engineering and Engineering Management (IEEM)(pp. 876-880). IEEE.

 

Pannakkong, W., Aswanuwath, L., Buddhakulsomsiri, J., Jeenanunta, C., & Parthanadee, P. (2019, November). Forecasting medium-term electricity demand in Thailand: Comparison of ANN, SVM, DBN, and their ensembles. In 2019 17th International Conference on ICT and Knowledge Engineering (ICT&KE) (pp. 1-6). IEEE.

 

Paopongchuang, B., Yenradee, P., & Buddhakulsomsiri, J. (2019). Finite capacity material requirement planning system for supply chain network (Doctoral dissertation, Thammasat University).

 

Tai, M. P. D., Buddhakulsomsiri, J., & Duc, T. T. H. (2019). Marketing-operations interface: a study of compound bullwhip effect and information sharing in supply chain (Doctoral dissertation, Thammasat University).

 

Duc, M. N. T. T., & Buddhakulsomsiri, J. (2019). A Markovian approach for optimizing A (T, S) inventory system under stochastic discrete demand and lead time with lost sales(Doctoral dissertation, Thammasat University).

 

Thy, M. N. N. A., & Buddhakulsomsiri, J. (2019). Fuzzy linear programming model of animal feeds raw material procurement problem to study the impacts of government policies (Doctoral dissertation, Thammasat University).

 

Le, C. T. D., Buddhakulsomsiri, J., Jeenanunta, C., & Dumrongsiri, A. (2019). Determining an optimal warehouse location, capacity, and product allocation in a multi-product, multi-period distribution network: a case study. International Journal of Logistics Systems and Management, 34(4), 510-532.

 

Singha, K., Buddhakulsomsiri, J., & Parthanadee, P. (2019). Computational experiment of methods to determine periodic (R, Q) inventory policy parameters: a case study of information decentralised distribution network. International Journal of Industrial and Systems Engineering, 32(2), 212-242.

 

Tai, P. D., Duc, T. T. H., & Buddhakulsomsiri, J. (2019). Measure of bullwhip effect in supply chain with price-sensitive and correlated demand. Computers & Industrial Engineering, 127, 408-419.

 

Buddhakulsomsiri, J., Parthanadee, P., and Pannakkong, W. Prediction models of starch content in fresh cassava roots for a tapioca starch manufacturer in Thailand, Computers and Electronics in Agriculture, 2018, 154, 296-303.

Duc, T. T. H., Loi, N. T., and Buddhakulsomsiri, J. Buyback contract in a risk-averse supply chain with a return policy and price dependent demand, International Journal of Logistics Systems and Management, 2018, 30 (3), 298-329.

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