In this study, we developed a continuous-time Markov chain (CTMC) state-space model for the reliability and availability analysis of a representative bamboo plywood manufacturing line composed of nine repairable subsystems. The plant operated a single sequential line with an average daily throughput of approximately 18 m3 of finished panel; failure and repair data were extracted from 26 months of daily operational logs (January 2022–February 2024) covering 1,134 failure events across equipment with service ages ranging from 3 to 11 years. A 34-state model was formulated, capturing full-capacity operation, reduced-capacity operation for the steaming chamber and dryer, and complete failure of each subsystem. Prior to model construction, an Anderson-Darling goodness-of-fit test was applied to inter-arrival and repair-time samples for each subsystem; the exponential distribution was retained for nine of eleven failure processes and eight of nine repair processes at the 5% significance level, providing empirical support for the Markovian assumption. Transient reliability over a 360-day horizon was obtained with a fourth-order Runge-Kutta integrator (step size h = 0.05 day, initial condition f1(0) = 1, relative tolerance 10-6), and long-run availability was computed by Gaussian elimination on the steady-state balance equations with subsequent normalization. Bootstrap resampling (B = 1,000) was used to attach 95% confidence intervals to every reported availability and MTBF figure. Under baseline conditions, the system achieved a long-run availability of 0.973 ± 0.011 and an MTBF of approximately 760 hours. Sensitivity analysis identified the steaming chamber, hot press, and peeling machine as the most influential subsystems; Birnbaum importance measures confirmed this ranking and revealed that single-parameter sensitivities, although indicative, understate the joint influence of the steaming chamber when correlated rate variation is considered. A simple downtime-cost model converted the availability gains into expected annual savings of approximately USD 2,900 for a 10% improvement in steaming-chamber repair rate. The results support reliability-centered and condition-based maintenance prioritization and provide a transferable quantitative template for engineered-wood processing lines.
Citation: Suresh Kumar Sahani, Tsair-Fwu Lee, Digvijay Pandey, Binay Kumar Pandey, Kameshwar Sahani. Reliability and availability analysis of a bamboo plywood manufacturing system using a continuous-time Markov state-space model[J]. Journal of Industrial and Management Optimization, 2026, 22(10): 5154-5193. doi: 10.3934/jimo.2026178
In this study, we developed a continuous-time Markov chain (CTMC) state-space model for the reliability and availability analysis of a representative bamboo plywood manufacturing line composed of nine repairable subsystems. The plant operated a single sequential line with an average daily throughput of approximately 18 m3 of finished panel; failure and repair data were extracted from 26 months of daily operational logs (January 2022–February 2024) covering 1,134 failure events across equipment with service ages ranging from 3 to 11 years. A 34-state model was formulated, capturing full-capacity operation, reduced-capacity operation for the steaming chamber and dryer, and complete failure of each subsystem. Prior to model construction, an Anderson-Darling goodness-of-fit test was applied to inter-arrival and repair-time samples for each subsystem; the exponential distribution was retained for nine of eleven failure processes and eight of nine repair processes at the 5% significance level, providing empirical support for the Markovian assumption. Transient reliability over a 360-day horizon was obtained with a fourth-order Runge-Kutta integrator (step size h = 0.05 day, initial condition f1(0) = 1, relative tolerance 10-6), and long-run availability was computed by Gaussian elimination on the steady-state balance equations with subsequent normalization. Bootstrap resampling (B = 1,000) was used to attach 95% confidence intervals to every reported availability and MTBF figure. Under baseline conditions, the system achieved a long-run availability of 0.973 ± 0.011 and an MTBF of approximately 760 hours. Sensitivity analysis identified the steaming chamber, hot press, and peeling machine as the most influential subsystems; Birnbaum importance measures confirmed this ranking and revealed that single-parameter sensitivities, although indicative, understate the joint influence of the steaming chamber when correlated rate variation is considered. A simple downtime-cost model converted the availability gains into expected annual savings of approximately USD 2,900 for a 10% improvement in steaming-chamber repair rate. The results support reliability-centered and condition-based maintenance prioritization and provide a transferable quantitative template for engineered-wood processing lines.
| [1] |
N. Singhal, S. P. Sharma, Availability analysis of industrial systems using Markov process and generalized fuzzy numbers, MAPAN, 34 (2019), 79–91. https://doi.org/10.1007/s12647-018-0290-4 doi: 10.1007/s12647-018-0290-4
|
| [2] |
Y. Sun, H. Tao, V. Stojanović, Open-set classification method via latent representation prompt and time-frequency fusion toward unknown fault recognition, Adv. Eng. Inform., 68 (2025), 103779. https://doi.org/10.1016/j.aei.2025.103779 doi: 10.1016/j.aei.2025.103779
|
| [3] |
M. Hajeeh, D. Chaudhuri, Reliability and availability assessment of reverse osmosis, Desalination, 130 (2000), 185–192. https://doi.org/10.1016/S0011-9164(00)00086-2 doi: 10.1016/S0011-9164(00)00086-2
|
| [4] |
M. R. Rotab Khan, A. B. M. Zohrul Kabir, Availability simulation of an ammonia plant, Reliab. Eng. Syst. Saf., 48 (1995), 217–227. https://doi.org/10.1016/0951-8320(95)00020-3 doi: 10.1016/0951-8320(95)00020-3
|
| [5] | R. W. Butler, S. C. Johnson, Techniques for Modeling the Reliability of Fault-Tolerant Systems with the Markov State-Space Approach, Hampton: NASA Langley Research Center, 1995. |
| [6] | K. S. Trivedi, A. Bobbio, Reliability and Availability Engineering: Modeling, Analysis, and Applications, Cambridge: Cambridge University Press, 2017. https://doi.org/10.1017/9781316163047 |
| [7] | C. A. Petri, Kommunikation mit Automaten [Communication with Automata], Bonn: Institut für Instrumentelle, 1962. |
| [8] |
A. Sachdeva, D. Kumar, P. Kumar, Planning and optimizing the maintenance of paper production systems in a paper plant, Comput. Ind. Eng., 55 (2008), 817–829. https://doi.org/10.1016/j.cie.2008.03.004 doi: 10.1016/j.cie.2008.03.004
|
| [9] |
A. Bahl, A. Sachdeva, R. K. Garg, Availability analysis of distillery plant using Petri nets, Int. J. Qual. Reliab. Manag., 35 (2018), 2373–2387. https://doi.org/10.1108/IJQRM-06-2017-0108 doi: 10.1108/IJQRM-06-2017-0108
|
| [10] |
N. Kumar, P. C. Tewari, A. Sachdeva, Performance modeling and analysis of refrigeration system of a milk processing plant using Petri nets, Int. J. Perform. Eng., 15 (2019), 1751–1759. https://doi.org/10.23940/ijpe.19.07.p1.17511759 doi: 10.23940/ijpe.19.07.p1.17511759
|
| [11] |
N. Kumar, P. C. Tewari, A. Sachdeva, Performance modelling and availability analysis of a milk pasteurising system using Petri nets formalism, Int. J. Simul. Process Model., 15 (2020), 401–409. https://doi.org/10.1504/IJSPM.2020.110915 doi: 10.1504/IJSPM.2020.110915
|
| [12] |
N. Kumar, P. C. Tewari, A. Sachdeva, Petri nets modelling and analysis of the veneer layup system of plywood manufacturing plant, Int. J. Eng. Model., 33 (2020), 95–107. https://doi.org/10.31534/engmod.2020.1-2.ri.07v doi: 10.31534/engmod.2020.1-2.ri.07v
|
| [13] | J. A. Orlicky, Material Requirements Planning (MRP): The New Way of Life in Production and Inventory Management, New York: McGraw-Hill, Inc, 1974. |
| [14] | E. A. Silver, D. F. Pyke, R. Peterson, Inventory Management and Production Planning and Scheduling, 3 Eds., New York: Wiley, 1998. |
| [15] | R. F. Baldwin, Plywood and Veneer-Based Products: Manufacturing Practices, San Francisco: Miller Freeman Books, 1995. |
| [16] | A. Schramm, Complete Guide to Hardwood Plywood and Face Veneer, West Lafayette: Purdue University Press, 2003. |
| [17] |
P. Bekhta, R. Marutzky, Reduction of glue consumption in the plywood production by using previously compressed veneer, Holz Roh Werkst., 65 (2007), 87–88. https://doi.org/10.1007/s00107-006-0142-8 doi: 10.1007/s00107-006-0142-8
|
| [18] |
P. Bekhta, S. Hiziroglu, O. Shepelyuk, Properties of plywood manufactured from compressed veneer as building material, Mater. Des., 30 (2009), 947–953. https://doi.org/10.1016/j.matdes.2008.07.001 doi: 10.1016/j.matdes.2008.07.001
|
| [19] |
I. Aydin, G. Colakoglu, Effects of surface inactivation, high-temperature drying and preservative treatment on surface roughness and colour of alder and beech wood, Appl. Surf. Sci., 252 (2005), 430–440. https://doi.org/10.1016/j.apsusc.2005.01.022 doi: 10.1016/j.apsusc.2005.01.022
|
| [20] |
I. Aydin, Activation of wood surfaces for glue bonds by mechanical pre-treatment and its effects on some properties of veneer surfaces and plywood panels, Appl. Surf. Sci., 233 (2004), 268–274. https://doi.org/10.1016/j.apsusc.2004.03.230 doi: 10.1016/j.apsusc.2004.03.230
|
| [21] |
G. I. Mantanis, R. A. Young, R. M. Rowell, Swelling of wood: Part Ⅰ. Swelling in water, Wood Sci. Technol., 28 (1994), 119–134. https://doi.org/10.1007/BF00192691 doi: 10.1007/BF00192691
|
| [22] |
L. Blomqvist, J. Johansson, D. Sandberg, Shape stability of laminated veneer products: An experimental study of the influence on distortion of some material and process parameters, Wood Mater. Sci. Eng., 8 (2013), 198–211. https://doi.org/10.1080/17480272.2013.803501 doi: 10.1080/17480272.2013.803501
|
| [23] |
B. Shivamurthy, N. Naik, B. H. S. Thimappa, R. Bhat, Mechanical property evaluation of alkali-treated jute fiber reinforced bio-epoxy composite materials, Mater. Today: Proc., 28 (2020), 2116–2120. https://doi.org/10.1016/j.matpr.2020.04.016 doi: 10.1016/j.matpr.2020.04.016
|
| [24] |
T. Wang, Y. Wang, R. Crocetti, M. Walinder, R. Bredesen, L. Blomqvist, Adhesively bonded joints between spruce glulam and birch plywood for structural applications: Experimental studies by using different adhesives and pressing methods, Wood Mater. Sci. Eng., 18 (2023), 1141–1150. https://doi.org/10.1080/17480272.2023.2201577 doi: 10.1080/17480272.2023.2201577
|
| [25] | J. F. Siau, Transport Processes in Wood, Berlin: Springer, 1984. https://doi.org/10.1007/978-3-642-69213-0 |
| [26] | A. Pizzi, K. L. Mittal, Handbook of Adhesive Technology, 3 Eds., Boca Raton: CRC Press, 2017. https://doi.org/10.1201/9781315120942 |
| [27] |
L. Blomqvist, S. Berg, D. Sandberg, Distortion in laminated veneer products exposed to relative-humidity variations: Experimental studies and finite-element modelling, BioResources, 14 (2019), 3768–3779. https://doi.org/10.15376/biores.14.2.3768-3779 doi: 10.15376/biores.14.2.3768-3779
|
| [28] |
J. Friederich, S. Lazarova-Molnar, Reliability assessment of manufacturing systems: A comprehensive overview, challenges and opportunities, J. Manuf. Syst., 72 (2024), 38–58. https://doi.org/10.1016/j.jmsy.2023.11.001 doi: 10.1016/j.jmsy.2023.11.001
|
| [29] |
A. K. Singh, P. C. Tewari, An overview of reliability, availability, maintainability, and safety strategies for complex systems in various process industries, Int. J. Perform. Eng., 19 (2023), 788–796. https://doi.org/10.23940/ijpe.23.12.p3.788796 doi: 10.23940/ijpe.23.12.p3.788796
|
| [30] |
A. Sheeba Angel, R. Jayaparvathy, Performance modeling of an intelligent emergency evacuation system in buildings on accidental fire occurrence, Saf. Sci., 112 (2019), 196–205. https://doi.org/10.1016/j.ssci.2018.10.027 doi: 10.1016/j.ssci.2018.10.027
|
| [31] | M. D. Smith, S. E. Schechter, Computer Security Strength & Risk: A Quantitative Approach, Cambridge: Harvard University, 2004. |
| [32] |
S. K. Sahani, R. K. Raj, K. Sathishkumar, G. N. Keshava Murthy, S. B. Manojkumar, K. B. Naveen, et al., Mechanical Process Control and Statistical Process Control for Reducing Butter-Oil Defects in Industrial Production, Rep. Mech. Eng., 7 (2026), 169–184. https://doi.org/10.31181/rme575 doi: 10.31181/rme575
|
| [33] |
S. K. Sahani, S. K. Oruganti, K. Satish Kumar, K. Sahani, B. K. Pandey, D. Pandey, Case Study on Mechanical and Operational Behavior in Steel Production: Performance and Process Behavior in Steel Manufacturing Plant, Rep. Mech. Eng., 6 (2025), 180–197. https://doi.org/10.31181/rme496 doi: 10.31181/rme496
|
 jimo-22-10-178-s001.pdf |
 |
Figures(7) / Tables(20)
Suresh Kumar Sahani, Tsair-Fwu Lee, Digvijay Pandey, Binay Kumar Pandey, Kameshwar Sahani. Reliability and availability analysis of a bamboo plywood manufacturing system using a continuous-time Markov state-space model[J]. Journal of Industrial and Management Optimization, 2026, 22(10): 5154-5193. doi: 10.3934/jimo.2026178
DownLoad: