Production
https://prod.org.br/doi/10.1590/0103-6513.170514
Production
Article

Process capability index Cpk for monitoring the thermal performance in the distribution of refrigerated products

Novaes, Antonio Galvão Naclério; Lima Jr, Orlando Fontes; Carvalho, Carolina Corrêa de; Aragão Junior, Dmontier Pinheiro

Downloads: 0
Views: 929

Abstract

The temperature of refrigerated products along the cold chain must be kept within pre-defined limits to ensure adequate safety levels and high product quality. Because temperature largely influences microbial activities, the continuous monitoring of the time-temperature history over the distribution process usually allows for the adequate control of the product quality along both short- and medium-distance distribution routes. Time-Temperature Indicators (TTI) are composed of temperature measurements taken at various time intervals and are used to feed analytic models that monitor the impacts of temperature on product quality. Process Capability Indices (PCI), however, are calculated using TTI series to evaluate whether the thermal characteristics of the process are within the specified range. In this application, a refrigerated food delivery route is investigated using a simulated annealing algorithm that considers alternative delivery schemes. The objective of this investigation is to minimize the distance traveled while maintaining the vehicle temperature within the prescribed capability level.

Keywords

Refrigerated products. Vehicle routing. Simulated annealing. TTI. PCI.

References

Amorim, P., Günther, H. O., & Almada-Lobo, B. (2012). Multi-objective integrated production and distribution planning of perishable products. International Journal of Production Economics, 138, 89-101. http://dx.doi.org/10.1016/j.ijpe.2012.03.005

Anis, M. Z. (2008). Basic process capability indices: An expository review. International Statistical Review, 76, 347-367. http://dx.doi.org/10.1111/j.1751-5823.2008.00060.x

Azi, N., Gendreau, M., & Potvin, J. Y. (2007). An exact algorithm for a simple-vehicle routing problem with time windows and multiple routes. European Journal of Operational Research, 178, 755-766. http://dx.doi.org/10.1016/j.ejor.2006.02.019

Barriga, G. D. C., Ho, L. L., & Borges, W. S. (2003). Process capability index for one-sided specification limit. Production, 13, 40-49.

Bittanti, S., Lovera, M., & Moiraghi, L. (1998). Application of non-normal process capability indices to semiconductor quality control. IEEE Transactions on Semiconductor Manufacturing, 11, 296-303. http://dx.doi.org/10.1109/66.670179

Borch, E., & Arinder, P. (2002). Bacteriological safety issues in red meat and ready-to-eat meat products, as well as control measures. Meat Science, 62, 381-390. http://dx.doi.org/10.1016/S0309-1740(02)00125-0

Breedam, A. V. (1995). Improvement heuristics for the vehicle routing problem based on simulated annealing. European Journal of Operational Research, 86, 480-490. http://dx.doi.org/10.1016/0377-2217(94)00064-J

Bulba, E. A., & Ho, L. L. (2004). Capability index for linear and non-linear functions. Production, 14, 6-11.

Burr, I. W. (1973). Parameters for a general system of distributions to match a grid of a 3 and a 4 . Communications in Statistics – Theory and Methods, 2, 1-21.

Chang, Y. S. (2009). Interval estimation of capability index C pmk for manufacturing processes with asymmetric tolerances. Computers & Industrial Engineering, 56, 312-322. http://dx.doi.org/10.1016/j.cie.2008.06.004

Chang, Y. S., & Bai, D. S. (2001). Control charts for positively-skewed populations with weighted standard deviations. Quality and Reliability Engineering International, 17, 397-406. http://dx.doi.org/10.1002/qre.427

Chang, Y. S., Choi, I. S., & Bai, D. S. (2002). Process capability indices for skewed populations. Quality and Reliability Engineering International, 18, 383-393. http://dx.doi.org/10.1002/qre.489

Chen, H. K., Hsueh, C. F. & Chang, M. S. (2009). Production scheduling and vehicle routing with time windows for perishable food products. Computers & Operations Research, 36, 2311-2319. http://dx.doi.org/10.1016/j.cor.2008.09.010

Chen, J. P. & Ding, C. G. (2001). A new process capability index for non-normal distributions. The International of Quality and Reliability Management, 18, 762-770. http://dx.doi.org/10.1108/02656710110396076

Elderton, W. P., & Johnson, N. L. (1969). Systems of Frequency Curves. Cambridge: Cambridge University Press. http://dx.doi.org/10.1017/CBO9780511569654

Estrada-Flores, S., & Eddy, A. (2006). Thermal performance indicators for refrigerated road vehicles. International Journal of Refrigeration, 29, 889-898. http://dx.doi.org/10.1016/j.ijrefrig.2006.01.012

Flick, D., Hoang, H. M., Alvarez, G., & Laguerre, O. (2012). Combined deterministic and stochastic approaches for modelling the evolution of food products along the cold chain. Part I: Methodology. International Journal of Refrigeration, 35, 907-914. http://dx.doi.org/10.1016/j.ijrefrig.2011.12.010

Food Refrigeration & Process Engineering Research Centre – FRPERC (2000). Coolvan Manual (Version 3.0). University of Bristol, UK.

Giannakourou, M. C., & Taoukis, P. S. (2003). TTI- based distribution management system for quality optimization of frozen vegetables at the consumer end. Journal of Food Science, 68, 201-209. http://dx.doi.org/10.1111/j.1365-2621.2003.tb14140.x

Giannakourou, M. C., Koutsoumanis, K., Nychas, G. J., & Taoukis, P. S. (2005). Field evaluation of the application of time temperature integrators for monitoring fish quality in the chill chain. International Journal of Food Microbiology, 102, 323-336. PMid:16014299. http://dx.doi.org/10.1016/j.ijfoodmicro.2004.11.037

Gigiel, A. J., James S. J., & Evans, J. A. (1998). Controlling temperature during distribution and retail. In Proceedings 3 rd Karlsruhe Nutrition Symposium , Karlsruhe, Germany.

Gonçalez, P. U., & Werner, L. (2009). Comparação dos índices de capacidade do processo para distribuições não- normais. Gestão & Produção, 16(1), 121-132. http://dx.doi.org/10.1590/S0104-530X2009000100012

Havelaar, A. H., Brul, S., De Jong, A., De Jonge, R., Zietering, M. H., & Ter Kuile, B. (2010). Future challenges to microbial food safety. International Journal of Food Microbiology, 139, S79-S94. PMid:19913933. http://dx.doi.org/10.1016/j.ijfoodmicro.2009.10.015

Hosseinifard, S. Z., Abassi, B., Ahmad, S., & Abdollahian, M. (2009). A transformation technique to estimate the process capability index for non-normal data. The International Journal of Advanced Manufacturing Technology, 40, 512-517. http://dx.doi.org/10.1007/s00170-008-1376-x

Hsu, C. I., Hung, S. F., & Li, H. C. (2007). Vehicle routing problem with time-windows for perishable food delivery. Journal of Food Engineering, 80, 465-475. http://dx.doi.org/10.1016/j.jfoodeng.2006.05.029

James, S. J., & James, C. (2010). The cold chain and climate change. Food Research International, 43, 1944-1956. http://dx.doi.org/10.1016/j.foodres.2010.02.001

James, S. J., James, C., & Evans, J. A. (2006). Modelling of food transportation systems – a review. International Journal of Refrigeration, 29, 947-957. http://dx.doi.org/10.1016/j.ijrefrig.2006.03.017

Jedermann, R., Ruiz-Garcia, L., & Lang, W. (2009). Spatial temperature profiling by semi-passive RFID loggers for perishable food transportation. Computers and Electronics in Agriculture, 65(2), 145-154. http://dx.doi.org/10.1016/j.compag.2008.08.006

Kaya, I., & Kahraman, C. (2010). A new perspective on fuzzy process capability indices: Robustness. Expert Systems with Applications, 37, 4593-4600. http://dx.doi.org/10.1016/j.eswa.2009.12.049

Kirkpatrick, S., Gellat, C. D., & Vecchi, M. P. (1983). Optimization by simulated annealing. Science, 220, 671-680. PMid:17813860. http://dx.doi.org/10.1126/science.220.4598.671

Leung, S. C. H., Zhang, Z., Zhang, D., Hua, X., & Lim, M. K. (2013). A meta-heuristic algorithm for heterogeneous fleet routing problems with two-dimensional loading constraints. European Journal of Operational Research, 225, 199-210. http://dx.doi.org/10.1016/j.ejor.2012.09.023

Lin, P. H., & Chen, F. L. (2006). Process capability analysis of non-normal process data using the Burr XII distribution. The International Journal of Advanced Manufacturing Technology, 27, 975-984. http://dx.doi.org/10.1007/s00170-004-2263-8

Magalhães, M. S., & Moura Neto, F. D. (2011). Economic- statistical design of variable parameters non-central chi-square control chart. Production, 21, 259-270.

Mauri, G. R., & Lorena, L. A. N. (2009). A new approach for the dial-a-ride problem. Production, 19, p. 41-54. McMeekin, T., Bowman, J., McQuestin, O., Mellefont, L., Ross, T., & Tamplin, M. (2008). The future of predictive microbiology: Strategic research, innovative applications and great expectations. International Journal of Food Microbiology, 128, 2-9. PMid:18703250. http://dx.doi.org/10.1016/j.ijfoodmicro.2008.06.026

Mingoti, S. A., & Glória, F. F. F. (2008). Comparing Mingoti and Glória’s and Niverthi and Dey’s multivariate capability indexes. Production, 18, 598-608.

Mingoti, S. A., Oliveira, F. L. P., & Conceição, M. M. C. (2011). Capability indices for independent multivariate processes: extensions of Niverthi and Dey’s and Mingoti and Glória’s indices. Production, 21, 94-105.

Moureh, J., & Derens, E. (2000). Numerical modelling of the temperature increase in frozen food packaged in pallets in the distribution chain. International Journal of Refrigeration, 23, 540-552. http://dx.doi.org/10.1016/S0140-7007(99)00081-X

Osman, I. H. (1993). Metastrategy simulated annealing and tabu search algorithms for the vehicle routing problem. Annals of Operations Research, 41(4), 421-451. http://dx.doi.org/10.1007/BF02023004

Oswald, A., & Stirn, L. Z. (2008). A vehicle routing algorithm for the distribution of fresh vegetables and similar perishable food. Journal of Food Engineering, 85, 285-295. http://dx.doi.org/10.1016/j.jfoodeng.2007.07.008

Pearn, W. L., & Lin, P. C. (2004). Testing process performance based on capability index C pk with critical values, Computers & Industrial Engineering, 47, 351-369. http://dx.doi.org/10.1016/j.cie.2003.03.001

Pereira, V. F., Dória, E. C. B, Carvalho Júnior, B. C., Neves Filho, L. C., & Silveira Júnior, V. (2010). Avaliação de temperaturas em câmaras frigoríficas de transporte urbano de alimentos resfriados e congelados. Ciência e Tecnologia de Alimentos, 30, 158-165. http://dx.doi.org/10.1590/S0101-20612010000100024

Sahin, E., Babaï, M. Z., Dallery, Y., & Vaillant, R. (2007). Ensuring supply chain safety through time temperature integrators. International Journal of Logistics Management, 18, 102-124. http://dx.doi.org/10.1108/09574090710748199

Simpson, R., Almonacid, S., Nuñez, H., Pinto, M., Abakarov, A., & Teixeira, A. (2012). Time-temperature indicator to monitor cold chain distribution of fresh salmon (salmo salar). Journal of Food Process Engineering, 35, 742-750. http://dx.doi.org/10.1111/j.1745-4530.2010.00623.x

Smolander, M., Alakomi, H.-L., Ritvanen, T., Vainionpää, J., & Ahvenainen, R. (2004). Monitoring of the quality of modified atmosphere packaged broiler chicken cuts stored in different temperature conditions. A. Time- temperature indicators as quality-indicating tools. Food Control, 15, 217-229. http://dx.doi.org/10.1016/S0956-7135(03)00061-6

Syslo, M. M., Deo, N., & Kowalik, J. S. (2006). Discrete Optimization Algorithms with Pascal Programs. Mineola: Dover Publications.

Tarantilis, C. D., & Kiranoudis, C. T. (2002). Distribution of fresh meat. Journal of Food Engineering, 51, 85-91. http://dx.doi.org/10.1016/S0260-8774(01)00040-1

Tso, C. P., Yu, S. C. M., Poh, H. J., & Jolly, P. G. (2002). Experimental study on the heat and mass transfer characteristics in a refrigerated truck. International Journal of Refrigeration, 25, p. 340-350. http://dx.doi.org/10.1016/S0140-7007(01)00015-9

Wu, C. W., Pearn, W. L., & Kotz, S. (2009). An overview of theory and practice on process capability indices for quality assurance. International Journal of Production Economics, 117, 338-359. http://dx.doi.org/10.1016/j.ijpe.2008.11.008
5883a46b7f8c9da00c8b48fd production Articles
Links & Downloads

Production

Share this page
Page Sections