Optimizing Production Planning in the Banbury Mixing Process via Modified FCMRP: A Tire Manufacturing Case Study
Main Article Content
Abstract
Production planning in the Banbury mixing process presents unique scheduling challenges,
primarily due to complex alternative Bill of Materials (BOM) routing and mandatory natural aging
constraints. This study addresses the severe operational inefficiencies—specifically, excessive lead
times and high machine idle time ratios—currently faced by a real-world tire manufacturing company.
To resolve these issues, we propose a modified Finite Capacity Material Requirements Planning
(FCMRP) framework. This approach dynamically calculates job release times based on predecessor
due times and previous order finish times to effectively accommodate mandatory resting periods. To
determine the most effective scheduling strategy, we systematically evaluate the company's baseline
Highest Order Quantity (HOQ) rule against standard Earliest Release Time (ERT) and Shortest
Processing Time (SPT) heuristics. Furthermore, we introduce a novel Non-Alternative Machine (NAM)
sub-rule designed to intelligently isolate and reallocate movable excess jobs to alleviate machine
bottlenecks. The experimental results demonstrate that combining the ERT rule with the NAM sub-rule
successfully reduces bottleneck workloads and yields the optimal overall lead time. Conversely,
applying ERT without the NAM logic provides the best machine idle time ratio. Ultimately, this
research delivers a practical, data-driven framework for selecting priority rules to optimize complex
mixing processes in the manufacturing industry.
Article Details
This work is licensed under a Creative Commons Attribution-NonCommercial-NoDerivatives 4.0 International License.
References
D. Rajamani, G. K. Adil, Scheduling and sequencing of rubber compounds on Banbury mixers in a tyre company, The International Journal of Advanced Manufacturing Technology 14(4) (1998) 298 – 305. https://doi.org/10.1007/BF01199885.
M. Taal, J. C. Wortmann, Integrating MRP and finite capacity planning, Production Planning & Control 8(3) (1997) 245 – 251. https://doi.org/10.1080/095372897235307.
P. C. Pandey, P. Yenradee, S. Archariyapruek, A finite capacity material requirements planning system, Production Planning & Control 11(2) (2000) 113 – 121. https://doi.org/10.1080/095372800232315.
T. Wuttipornpun, P. Yenradee, Development of finite capacity material requirement planning system for assembly operations, Production Planning & Control 15(5) (2004) 534 – 549. https://doi.org/10.1080/09537280412331270797.
T. Wuttipornpun, P. Yenradee, Performance of TOC based finite capacity material requirement planning system for a multi-stage assembly factory, Production Planning & Control 18(8) (2007) 703 – 715. https://doi.org/10.1080/09537280701702061.
H. G. Lee, N. Park, J. Park, A high performance finite capacitated MRP process using a computational grid, International Journal of Production Research 47(8) (2009) 2109 – 2123. https://doi.org/10.1080/00207540802132775.
X. Li, L. Gao, C. Zhang, X. Shao, A review on integrated process planning and scheduling, International Journal of Manufacturing Research 5(2) (2010) 161 – 180. https://doi.org/10.1504/IJMR.2010.031630.
M. A. Wazed, S. Ahmed, Y. Nukman, Commonality in manufacturing resources planning – issues and models: A review, European Journal of Industrial Engineering 4(2) (2010) 167 – 188. https://doi.org/10.1504/EJIE.2010.031076.
L. A. Hadidi, U. M. Al-Turki, A. Rahim, Integrated models in production planning and scheduling, maintenance and quality: A review, International Journal of Industrial and Systems Engineering 10(1) (2012) 21 – 50. https://doi.org/10.1504/IJISE.2012.044042.
H. Jodlbauer, S. Reitner, Material and capacity requirements planning with dynamic lead times, International Journal of Production Research 50(16) (2012) 4477 – 4492. https://doi.org/10.1080/00207543.2011.603707.
M. R. Pérez-Salazar, I. Rivera, I. M. Cristóbal-Vázquez, ERP selection: A literature review, International Journal of Industrial and Systems Engineering 13(3) (2013) 309 – 324. https://doi.org/10.1504/IJISE.2013.052279.
T. Wuttipornpun, P. Yenradee, Finite capacity material requirement planning system for assembly flow shop with alternative work centres, International Journal of Industrial and Systems Engineering 18(1) (2014) 95 – 124. https://doi.org/10.1504/IJISE.2014.064343.
K. R. Baker, Sequencing rules and due-date assignments in a job shop, Management Science 30(9) (1984) 1093 – 1104. https://doi.org/10.1287/mnsc.30.9.1093.
L. Özdamar, G. Ulusoy, A note on an iterative forward/backward scheduling technique with reference to a procedure by Li and Willis, European Journal of Operational Research 89(2) (1996) 400 – 407. https://doi.org/10.1016/0377-2217(94)00272-X.
W. Sukkerd, T. Wuttipornpun, Hybrid genetic algorithm and tabu search for finite capacity material requirement planning system in flexible flow shop with assembly operations, Computers & Industrial Engineering 97 (2016) 157 – 169. https://doi.org/10.1016/j.cie.2016.05.006.
W. Songserm, T. Wuttipornpun, MIP-based heuristic algorithm for finite capacity MRP problem in hybrid flow shop with unrelated parallel machines, International Journal of Industrial and Systems Engineering 33(2) (2019) 181 – 203. https://doi.org/10.1504/IJISE.2019.102470.