508,249 research outputs found

    Genetic algorithms for the scheduling in additive manufacturing

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    [EN] Genetic Algorithms (GAs) are introduced to tackle the packing problem. The scheduling in Additive Manufacturing (AM) is also dealt with to set up a managed market, called “Lonja3D”. This will enable to determine an alternative tool through the combinatorial auctions, wherein the customers will be able to purchase the products at the best prices from the manufacturers. Moreover, the manufacturers will be able to optimize the production capacity and to decrease the operating costs in each case.This research has been partially financed by the project: “Lonja de Impresión 3D para la Industria 4.0 y la Empresa Digital (LONJA3D)” funded by the Regional Government of Castile and Leon and the European Regional Development Fund (ERDF, FEDER) with grant VA049P17Castillo-Rivera, S.; De Antón, J.; Del Olmo, R.; Pajares, J.; López-Paredes, A. (2020). Genetic algorithms for the scheduling in additive manufacturing. International Journal of Production Management and Engineering. 8(2):59-63. https://doi.org/10.4995/ijpme.2020.12173OJS596382Ahsan, A., Habib, A., Khoda, B. (2015). Resource based process planning for additive manufacturing. Computer-Aided Design, 69, 112-125. https://doi.org/10.1016/j.cad.2015.03.006Araújo, L., Özcan, E., Atkin, J., Baumers, M., Tuck, C., Hague, R. (2015). Toward better build volume packing in additive manufacturing: classification of existing problems and benchmarks. 26th Annual International Solid Freeform Fabrication Symposium - an Additive Manufacturing Conference, 401-410.Berman, B. (2012). 3-D printing: The new industrial revolution. Business Horizons, 55: 155-162. https://doi.org/10.1016/j.bushor.2011.11.003Canellidis, V., Dedoussis, V., Mantzouratos, N., Sofianopoulou, S. (2006). Preprocessing methodology for optimizing stereolithography apparatus build performance. Computers in Industry, 57, 424-436. https://doi.org/10.1016/j.compind.2006.02.004Chergui, A., Hadj-Hamoub, K., Vignata, F. (2018). Production scheduling and nesting in additive manufacturing. Computers & Industrial Engineering, 126, 292-301. https://doi.org/10.1016/j.cie.2018.09.048Demirel, E., Özelkan, E.C., Lim, C. (2018). Aggregate planning with flexibility requirements profile. International Journal of Production Economics, 202, 45-58. https://doi.org/10.1016/j.ijpe.2018.05.001Fera, M., Fruggiero, F., Lambiase, A., Macchiaroli, R., Todisco, V. (2018). A modified genetic algorithm for time and cost optimization of an additive manufacturing single-machine scheduling. International Journal of Industrial Engineering Computations, 9, 423-438. https://doi.org/10.5267/j.ijiec.2018.1.001Hopper, E., Turton, B. (1997). Application of genetic algorithms to packing problems - A Review. Proceedings of the 2nd Online World Conference on Soft Computing in Engineering Design and Manufacturing, Springer Verlag, London, 279-288. https://doi.org/10.1007/978-1-4471-0427-8_30Ikonen, I., Biles, W.E., Kumar, A., Wissel, J.C., Ragade, R.K. (1997). A genetic algorithm for packing three-dimensional non-convex objects having cavities and holes. ICGA, 591-598.Kim, K.H., Egbelu, P.J. (1999). Scheduling in a production environment with multiple process plans per job. International Journal of Production Research, 37, 2725-2753. https://doi.org/10.1080/002075499190491Lawrynowicz, A. (2011). Genetic algorithms for solving scheduling problems in manufacturing systems. Foundations of Management, 3(2), 7-26. https://doi.org/10.2478/v10238-012-0039-2Li, Q., Kucukkoc, I., Zhang, D. (2017). Production planning in additive manufacturing and 3D printing. Computers and Operations Research, 83, 157-172. https://doi.org/10.1016/j.cor.2017.01.013Milošević, M., Lukić, D., Đurđev, M., Vukman, J., Antić, A. (2016). Genetic Algorithms in Integrated Process Planning and Scheduling-A State of The Art Review. Proceedings in Manufacturing Systems, 11(2), 83-88.Pour, M.A., Zanardini, M., Bacchetti, A., Zanoni, S. (2016). Additive manufacturing impacts on productions and logistics systems. IFAC, 49(12), 1679-1684. https://doi.org/10.1016/j.ifacol.2016.07.822Wilhelm, W.E., Shin, H.M. (1985). Effectiveness of Alternate Operations in a Flexible Manufacturing System. International Journal of Production Research, 23(1), 65-79. https://doi.org/10.1080/00207548508904691Xirouchakis, P., Kiritsis, D., Persson, J.G. (1998). A Petri net Technique for Process Planning Cost Estimation. Annals of the CIRP, 47(1), 427-430. https://doi.org/10.1016/S0007-8506(07)62867-4Zhang, Y., Bernard, A., Gupta, R.K., Harik, R. (2014). Evaluating the design for additive manufacturing: a process planning perspective. Procedia CIRP, 21, 144-150. https://doi.org/10.1016/j.procir.2014.03.17

    Cell Formation Heuristic Procedure Considering Production Data

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    [EN] Manufacturing cell formation is one of foremost, and critical aspect of any manufacturing cell design problem. A large number of cell formation methods are developed and still counting. Consideration of production data in cell formation makes these methods more complex and tedious. In this paper an attempt has been made to develop a simple, easy to understand and implement cell formation procedure, having the capability to handle production data viz. operation sequence, production volume, and inter-cell movement cost simultaneously. The results obtained from proposed procedures are in tune with some highly complex methods, which validates the performance of proposed procedure. To demonstrate its ability to handle other production parameters with little modifications, a modification for consideration to part processing cost in addition to above mentioned production data is developed and explained. Towards the end the procedure to handle alternate process plans in conjugation with production data by the proposed cell formation procedure is also discussed.Kumar, S.; Sharma, RK. (2014). Cell Formation Heuristic Procedure Considering Production Data. International Journal of Production Management and Engineering. 2(2):75-84. doi:10.4995/ijpme.2014.2078SWORD758422Ahi, A., Aryanezhad, M. B., Ashtiani, B., & Makui, A. (2009). A novel approach to determine cell formation, intracellular machine layout and cell layout in the CMS problem based on TOPSIS method. Computers & Operations Research, 36(5), 1478-1496. doi:10.1016/j.cor.2008.02.012Arkat, J., Hosseinabadi Farahani, M., & Hosseini, L. (2011). Integrating cell formation with cellular layout and operations scheduling. The International Journal of Advanced Manufacturing Technology, 61(5-8), 637-647. doi:10.1007/s00170-011-3733-4Beaulieu, A., Ait-Kadi, D., & Gharbi, A. (1993). Heuristic for Flexible Machine Selection Problems. Journal of Decision Systems, 2(3-4), 241-253. doi:10.1080/12460125.1993.10511583Beaulieu, A., Gharbi, A., & Ait-Kadi. (1997). An algorithm for the cell formation and the machine selection problems in the design of a cellular manufacturing system. International Journal of Production Research, 35(7), 1857-1874. doi:10.1080/002075497194958Boutsinas, B. (2013). Machine-part cell formation using biclustering. European Journal of Operational Research, 230(3), 563-572. doi:10.1016/j.ejor.2013.05.007Chow, W. S., and Hawaleshka, O., (1992), An efficient algorithm for solving the machine chaining problem in cellular manufacturing, Computers ind. Engng., Vol. 22, No. 1, 95-100.CHU, C.-H., & TSAI, M. (1990). A comparison of three array-based clustering techniques for manufacturing cell formation. International Journal of Production Research, 28(8), 1417-1433. doi:10.1080/00207549008942802Nair, G. J., & Narendran, T. T. (1998). CASE: A clustering algorithm for cell formation with sequence data. International Journal of Production Research, 36(1), 157-180. doi:10.1080/002075498193985Jie Lian, Chen Guang Liu, Wen Juan Li, Steve Evans, Yong Yin, (2013), Formation of independent manufacturing cells with the consideration of multiple identical machines, International journal of production research, Kim, C. O.,Baek, J. G., Baek, J. K., (2004), A two-phase heuristic algorithm for cell formation problems considering alternative part routes and machine sequences, International Journal of Production Research, 42:18, 3911-3927,Krushinsky, D., & Goldengorin, B. (2012). An exact model for cell formation in group technology. Computational Management Science, 9(3), 323-338. doi:10.1007/s10287-012-0146-2Kumar, L. (2008). Part-machine group formation with operation sequence, time and production volume. International Journal of Simulation Modelling, 7(4), 198-209. doi:10.2507/ijsimm07(4)4.113Lokesh, K., & Jain, P. K. (2010). Concurrently part-machine groups formation with important production data. International Journal of Simulation Modelling, 9(1), 5-16. doi:10.2507/ijsimm09(1)1.133Miltenburg, J., & Zhang, W. (1991). A comparative evaluation of nine well-known algorithms for solving the cell formation problem in group technology. Journal of Operations Management, 10(1), 44-72. doi:10.1016/0272-6963(91)90035-vMukattash, A. M., Adil, M. B., & Tahboub, K. K. (2002). Heuristic approaches for part assignment in cell formation. Computers & Industrial Engineering, 42(2-4), 329-341. doi:10.1016/s0360-8352(02)00020-7Mahesh, O., & Srinivasan, G. (2002). Incremental cell formation considering alternative machines. International Journal of Production Research, 40(14), 3291-3310. doi:10.1080/00207540210146189Sudhakara Pandian, R., & Mahapatra, S. S. (2009). Manufacturing cell formation with production data using neural networks. Computers & Industrial Engineering, 56(4), 1340-1347. doi:10.1016/j.cie.2008.08.003Papaioannou, G., & Wilson, J. M. (2010). The evolution of cell formation problem methodologies based on recent studies (1997–2008): Review and directions for future research. European Journal of Operational Research, 206(3), 509-521. doi:10.1016/j.ejor.2009.10.020Sarker, B. R., (1996), The resemblance coefficients in group technology: a survey and comparative study of relational metrics, Computers ind. Engng., Vol. 30, No. 1, 103-116.Seifoddini, H., (1998), Comparison between single linkage and average linkage clustering techniques in forming machine cells", Computers & industrial engineering 15(14), 210-216.SHAFER, S. M., & MEREDITH, J. R. (1990). A comparison of selected manufacturing cell formation techniques. International Journal of Production Research, 28(4), 661-673. doi:10.1080/00207549008942747VENUGOPAL, V., & NARENDRAN, T. T. (1994). Machine-cell formation through neural network models. International Journal of Production Research, 32(9), 2105-2116. doi:10.1080/00207549408957061Won, Y., & Lee, K. C. (2001). Group technology cell formation considering operation sequences and production volumes. International Journal of Production Research, 39(13), 2755-2768. doi:10.1080/00207540010005060Yasuda *, K., Hu, L., & Yin, Y. (2005). A grouping genetic algorithm for the multi-objective cell formation problem. International Journal of Production Research, 43(4), 829-853. doi:10.1080/00207540512331311859Yin, Y., & Yasuda, K. (2005). Similarity coefficient methods applied to the cell formation problem: a comparative investigation. Computers & Industrial Engineering, 48(3), 471-489. doi:10.1016/j.cie.2003.01.001Yin, Y., & Yasuda, K. (2006). Similarity coefficient methods applied to the cell formation problem: A taxonomy and review. International Journal of Production Economics, 101(2), 329-352. doi:10.1016/j.ijpe.2005.01.01

    Inferring export orientation from corporate websites

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    This is an author's accepted manuscript of an article published in: “Applied Economics Letters"; Volume 21, Issue 7, 2014; copyright Taylor & Francis; available online at: http://dx.doi.org/10.1080/13504851.2013.872752The purpose of this article is to infer indicators about the export orientation of firms from the analysis of their corporate websites. Using a dataset of manufacturing firms, two logistic regressions were performed and compared: one considering some firm structural variables, and another considering some web-based variables. Results showed that the website features are good predictors of the export orientation of firms, performing as well as the classic economic variables.Blázquez Soriano, MD.; Doménech I De Soria, J. (2014). Inferring export orientation from corporate websites. Applied Economics Letters. 21(7):509-512. doi:10.1080/13504851.2013.872752S509512217Bonaccorsi, A. (1992). On the Relationship Between Firm Size and Export Intensity. Journal of International Business Studies, 23(4), 605-635. doi:10.1057/palgrave.jibs.8490280DA, Z., ENGELBERG, J., & GAO, P. (2011). In Search of Attention. The Journal of Finance, 66(5), 1461-1499. doi:10.1111/j.1540-6261.2011.01679.xDzielinski, M. (2012). Measuring economic uncertainty and its impact on the stock market. Finance Research Letters, 9(3), 167-175. doi:10.1016/j.frl.2011.10.003Freund, C. L., & Weinhold, D. (2004). The effect of the Internet on international trade. Journal of International Economics, 62(1), 171-189. doi:10.1016/s0022-1996(03)00059-xGirma, S., Greenaway, avid, & Kneller, R. (2004). Does Exporting Increase Productivity? A Microeconometric Analysis of Matched Firms. Review of International Economics, 12(5), 855-866. doi:10.1111/j.1467-9396.2004.00486.xLee, J., & Morrison, A. M. (2010). A comparative study of web site performance. Journal of Hospitality and Tourism Technology, 1(1), 50-67. doi:10.1108/17579881011023016Murphy, J., & Scharl, A. (2007). An investigation of global versus local online branding. International Marketing Review, 24(3), 297-312. doi:10.1108/02651330710755302Nassimbeni, G. (2001). Technology, innovation capacity, and the export attitude of small manufacturing firms: a logit/tobit model. Research Policy, 30(2), 245-262. doi:10.1016/s0048-7333(99)00114-6Preis, T., Reith, D., & Stanley, H. E. (2010). Complex dynamics of our economic life on different scales: insights from search engine query data. Philosophical Transactions of the Royal Society A: Mathematical, Physical and Engineering Sciences, 368(1933), 5707-5719. doi:10.1098/rsta.2010.0284Spence, M. M. (2003). Small Business Economics, 20(1), 83-103. doi:10.1023/a:1020200621988Varian, H. R. (2010). Computer Mediated Transactions. American Economic Review, 100(2), 1-10. doi:10.1257/aer.100.2.1Wholey, J. S., & Hatry, H. P. (1992). The Case for Performance Monitoring. Public Administration Review, 52(6), 604. doi:10.2307/97717

    Comparison of Different Parameters to Evaluate Delamination in Edge Trimming of Basalt Fiber Reinforced Plastics (BFRP)

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    [EN] Delamination is one of the main problems that occur when machining fiber-reinforced composite materials. In this work, Types I and II of delamination are studied separately in edge trimming of basalt fiber reinforced plastic (BFRP). For this purpose, one-dimensional and area delamination parameters are defined. One-dimensional parameters (Wa and Wb) allow to know average fibers length while the analysis of area delamination parameters (Sd) allow to evaluate delamination density. To study delamination, different tests are carried out modifying cutting parameters (cutting speed, feed per tooth and depth of cut) and material characteristics (fiber volume fraction and fiber orientation). Laminates with a lower fiber volume fraction do not present delamination. Attending to one-dimensional parameters it can be concluded that Type II delamination is more important than Type I and that a high depth of cut generates higher values of delamination parameters. An analysis of variance (ANOVA) is performed to study area parameters. Although delamination has a random nature, for each depth of cut, more influence variables in area delamination are firstly, feed per tooth and secondly, cutting speed.This research was funded by Government of Spain, grant number PID2019-108807RB-I00.Navarro-Mas, M.; Meseguer, M.; Lluch-Cerezo, J.; García Manrique, JA. (2020). Comparison of Different Parameters to Evaluate Delamination in Edge Trimming of Basalt Fiber Reinforced Plastics (BFRP). Materials. 13(23):1-17. https://doi.org/10.3390/ma13235326S1171323Lopresto, V., Caggiano, A., & Teti, R. (2016). High Performance Cutting of Fibre Reinforced Plastic Composite Materials. Procedia CIRP, 46, 71-82. doi:10.1016/j.procir.2016.05.079Ozkan, D., Panjan, P., Gok, M. S., & Karaoglanli, A. C. (2020). Experimental Study on Tool Wear and Delamination in Milling CFRPs with TiAlN- and TiN-Coated Tools. Coatings, 10(7), 623. doi:10.3390/coatings10070623Nguyen-Dinh, N., Bouvet, C., & Zitoune, R. (2019). Influence of machining damage generated during trimming of CFRP composite on the compressive strength. Journal of Composite Materials, 54(11), 1413-1430. doi:10.1177/0021998319883335Razfar, M. R., & Zadeh, M. R. Z. (2009). Optimum damage and surface roughness prediction in end milling glass fibre-reinforced plastics, using neural network and genetic algorithm. Proceedings of the Institution of Mechanical Engineers, Part B: Journal of Engineering Manufacture, 223(6), 653-664. doi:10.1243/09544054jem1409Neeli, N., Jenarthanan, M. P., & Dileep Kumar, G. (2018). Multi-response optimization for machining GFRP composites using GRA and DFA. Multidiscipline Modeling in Materials and Structures, 14(3), 482-496. doi:10.1108/mmms-08-2017-0092Azmi, A. I., Lin, R. J. T., & Bhattacharyya, D. (2012). Machinability study of glass fibre-reinforced polymer composites during end milling. The International Journal of Advanced Manufacturing Technology, 64(1-4), 247-261. doi:10.1007/s00170-012-4006-6Jenarthanan, M. P., & Jeyapaul, R. (2018). Optimisation of machining parameters on milling of GFRP composites by desirability function analysis using Taguchi method. International Journal of Engineering, Science and Technology, 5(4), 22-36. doi:10.4314/ijest.v5i4.3Sreenivasulu, R. (2013). Optimization of Surface Roughness and Delamination Damage of GFRP Composite Material in End Milling Using Taguchi Design Method and Artificial Neural Network. Procedia Engineering, 64, 785-794. doi:10.1016/j.proeng.2013.09.154He, Y., Qing, H., Zhang, S., Wang, D., & Zhu, S. (2017). The cutting force and defect analysis in milling of carbon fiber-reinforced polymer (CFRP) composite. The International Journal of Advanced Manufacturing Technology, 93(5-8), 1829-1842. doi:10.1007/s00170-017-0613-6Raj, P. P., & Perumal, A. E. (2010). Taguchi Analysis of surface roughness and delamination associated with various cemented carbide K10 end mills in milling of GFRP. Journal of Engineering Science and Technology Review, 3(1), 58-64. doi:10.25103/jestr.031.11Hintze, W., Hartmann, D., & Schütte, C. (2011). Occurrence and propagation of delamination during the machining of carbon fibre reinforced plastics (CFRPs) – An experimental study. Composites Science and Technology, 71(15), 1719-1726. doi:10.1016/j.compscitech.2011.08.002Wang, F., Yin, J., Ma, J., Jia, Z., Yang, F., & Niu, B. (2017). Effects of cutting edge radius and fiber cutting angle on the cutting-induced surface damage in machining of unidirectional CFRP composite laminates. The International Journal of Advanced Manufacturing Technology, 91(9-12), 3107-3120. doi:10.1007/s00170-017-0023-9Li, M., Huang, M., Jiang, X., Kuo, C., & Yang, X. (2018). Study on burr occurrence and surface integrity during slot milling of multidirectional and plain woven CFRPs. The International Journal of Advanced Manufacturing Technology, 97(1-4), 163-173. doi:10.1007/s00170-018-1937-6Sheikh-Ahmad, J. Y., Dhuttargaon, M., & Cheraghi, H. (2017). New tool life criterion for delamination free milling of CFRP. The International Journal of Advanced Manufacturing Technology, 92(5-8), 2131-2143. doi:10.1007/s00170-017-0240-2Szwajka, K., & Trzepieciński, T. (2016). Effect of tool material on tool wear and delamination during machining of particleboard. Journal of Wood Science, 62(4), 305-315. doi:10.1007/s10086-016-1555-6Wang, F., Zhang, B., Jia, Z., Zhao, X., & Wang, Q. (2019). Structural optimization method of multitooth cutter for surface damages suppression in edge trimming of Carbon Fiber Reinforced Plastics. Journal of Manufacturing Processes, 46, 204-213. doi:10.1016/j.jmapro.2019.09.013Masek, P., Zeman, P., Kolar, P., & Holesovsky, F. (2018). Edge trimming of C/PPS plates. The International Journal of Advanced Manufacturing Technology, 101(1-4), 157-170. doi:10.1007/s00170-018-2857-1Dhand, V., Mittal, G., Rhee, K. Y., Park, S.-J., & Hui, D. (2015). A short review on basalt fiber reinforced polymer composites. Composites Part B: Engineering, 73, 166-180. doi:10.1016/j.compositesb.2014.12.011Navarro-Mas, M., García-Manrique, J., Meseguer, M., Ordeig, I., & Sánchez, A. (2018). Delamination Study in Edge Trimming of Basalt Fiber Reinforced Plastics (BFRP). Materials, 11(8), 1418. doi:10.3390/ma1108141

    A systematic literature review of Total Quality Management (TQM) implementation in the organization

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    [EN] In today’s market situation and complex business environment, organization must be able to deliver the customer’s requirement and the expectations which are critical to the satisfaction such as high product quality, faster delivery and competitive cost. Organization need to apply a comprehensive concept and method on managing those requirements. The concept of Total Quality Management (TQM) is considered as one of a popular concept used to manage the quality of product and services comprehensively. This research is to observe is this concept and method still relevant to be use and effectively improved the business performance as well as customer satisfaction. It is a systematic literature review to the literatures from many industry sectors that were collected and reviewed in detail. The result show that this concept is still being used by many organizations around the world and its successfully help the organization to improve their competitiveness, business growth and the sustainability as well as increase employee’s morale.This article was completed thanks to the financial support from the university of Mercu Buana, Jakarta-Indonesia. It also completed with the purpose and motivation of the authors to have an innovate research thinking as well as the contribution to the future researcher.Permana, A.; Purba, H.; Rizkiyah, N. (2021). A systematic literature review of Total Quality Management (TQM) implementation in the organization. International Journal of Production Management and Engineering. 9(1):25-36. https://doi.org/10.4995/ijpme.2021.13765OJS253691Alanazi, M.H. (2020). The mediating role of primary TQM factors and strategy in the relationship between supportive TQM factors and organisational results: An empirical assessment using the MBNQA model. Cogent Business and Management, 7(1). https://doi.org/10.1080/23311975.2020.1771074Antunes, M.G., Mucharreira, P.R., Justino, M. do R.T., & Quirós, J.T. (2018). Total Quality Management Implementation in Portuguese Higher Education Institutions. Proceedings MDPI, 2(21), 1342. https://doi.org/10.3390/proceedings2211342Arifin, J. (2016). Penguatan Manajemen Syariah Melalui Total Quality Managementbagi Pelaku Lembaga Keuangan Syariah Di Kota Semarang. Jurnal At-Taqaddum, Volume 8, Nomor 2, November 2016, 8(2), 180. https://doi.org/10.21580/at.v8i2.1170Balasubramanian, M. (2016). Total Quality Management [TQM] in the Healthcare Industry - Challenges, Barriers and Implementation Developing a Framework for TQM Implementation in a Healthcare Setup. Science Journal of Public Health, 4(4), 271. https://doi.org/10.11648/j.sjph.20160404.11Benzaquen, J., Carlos, M., Norero, G., Armas, H., & Pacheco, H. (2019). Quality in private health companies in Peru: The relation of QMS & ISO 9000 principles on TQM factor. International Journal of Healthcare Management, 0(0), 1-9. https://doi.org/10.1080/20479700.2019.1644472Bigliardi, B., & Galati, F. (2014). The implementation of TQM in R&D environments. Journal of Technology Management and Innovation, 9(2), 157-171. https://doi.org/10.4067/S0718-27242014000200012Bunglowala, A., & Asthana, N. (2016). A Total Quality Management Approach in Teaching and Learning Process. International Journal of Management (IJM), 7(5), 223-227. http://www.iaeme.com/MasterAdmin/uploadfolder/IJM_07_05_021/IJM_07_05_021.pdfBusu, M. (2019). Applications of TQM Processes to Increase the Management Performance of Enterprises in the Romanian Renewable Energy Sector. Processes MDPI. https://doi.org/10.3390/pr7100685Dahlgaard, J.J., Kristensen, K., & Kanji, G.K. (2002). Fundamentals of Total Quality Management: Process analysis and improvement Jens. Original illustrations © Taylor & Francis 2002. https://doi.org/10.4324/9780203930021Dewi, H.P., Lumbanraja, P., & Matondang, R. (2015). Implementation of Total Quality Management and Interpersonal Communication in Achieving Student Satisfaction through Service Quality at Yayasan Pendidikan Islam, Miftahussalam, Medan. International Journal of Research and Review, 2(6), 343-347. http://www.gkpublication.in/IJRR_Vol.2_Issue6_June2015/IJRR0066.pdfEltawy, N., & Gallear, D. (2017). Leanness and agility: A comparative theoretical view. Industrial Management and Data Systems, 117(1), 149-165. https://doi.org/10.1108/IMDS-01-2016-0032Fitriani, F. (2019). Persiapan Total Quality Management (Tqm). Adaara: Jurnal Manajemen Pendidikan Islam, 9(2), 908-919. https://doi.org/10.35673/ajmpi.v9i2.426Garcia-Alcaraz, J.L., Flor-Montalvo, F.J., Avelar-Sosa, L., Sánchez-Ramírez, C., & Jiménez-Macías, E. (2019). Human resource abilities and skills in TQM for sustainable enterprises. Sustainability MDPI, 11(22), 6488. https://doi.org/10.3390/su11226488George, S., & Weimerskirch, A. (1998). Total quality management: Strategies and techniques proven at todays' most successful companies (Second ed.). John Wiley & Sons, Inc.Green, F.B. (2006). Six-sigma and the revival of TQM. Total Quality Management and Business Excellence, 17(10), 1281-1286. https://doi.org/10.1080/14783360600753711Gómez-López, R., Serrano-Bedia, A.M., & López-Fernández, M.C. (2016). Motivations for implementing TQM through the EFQM model in Spain: an empirical investigation. Total Quality Management and Business Excellence, 27(11-12), 1224-1245. https://doi.org/10.1080/14783363.2015.1068688Haffar, M., Al-Karaghouli, W., & Ghoneim, A. (2013). An analysis of the influence of organisational culture on TQM implementation in an era of global marketing: The case of Syrian manufacturing organisations. International Journal of Productivity and Quality Management, 11(1), 96-115. https://doi.org/10.1504/IJPQM.2013.050570Hasan, K., Islam, M.S., Shams, A.T., & Gupta, H. (2018). Total Quality Management (TQM): Implementation in Primary Education System of Bangladesh. International Journal of Research in Industrial Engineering, 7(3), 370-380. https://doi.org/10.22105/riej.2018.128170.1041Houston, D. (2007). TQM and higher education: A critical systems perspective on fitness for purpose. Quality in Higher Education, 13(1), 3-17. https://doi.org/10.1080/13538320701272672Kaname, O. (2003). Handbook for TQM and QCC Vol 1. In Handbook (Vol. 1). Kantardjieva, M. (2015). The Relationship between Total Quality Management (TQM) and Strategic Management. Journal of Economics, Business and Management, 3(5), 537-541. https://doi.org/10.7763/JOEBM.2015.V3.242Kim, G.-S. (2016). Effect of Total Quality Management on Customer Satisfaction. International Journal of Engineering Sciences & Research Technology, 5(6), 507-514. https://doi.org/10.5281/zenodo.55618Kiruthiga, K. (2016). Major factors affecting the execution of total quality management in the construction industry in India. Journal of Chemical and Pharmaceutical Sciences, 9(2), E135-E140.Kumar, S., & Shanmuganathan, J. (2019). A structural relationship between TQM practices and organizational performance with reference to selected auto component manufacturing companies. International Journal of Management, 10(5). https://doi.org/10.34218/IJM.10.5.2019/009Kumar, U., Kumar, V., de Grosbois, D., & Choisne, F. (2009). Continuous improvement of performance measurement by TQM adopters. Total Quality Management & Business Excellence, 20(6), 603-616. https://doi.org/10.1080/14783360902924242Kuo, C. (2016). Effects of Total Quality Management Implementation and Supply Chain Management Capability on Customer Capital. The Journal of Global Business Management, 12(2), 47-60.Lawrence, J.J., & McCollough, M.A. (2004). Implementing Total Quality Management in the Classroom by Means of Student Satisfaction Guarantees. Total Quality Management and Business Excellence, 15(2), 235-254. https://doi.org/10.1080/1478336032000149063Mensah, J.O., Copuroglu, G., & Fening, F.A. (2012). Total Quality Management in Ghana: Critical Success Factors and Model for Implementation of a Quality Revolution. Journal of African Business, 13(2), 123-133. https://doi.org/10.1080/15228916.2012.693444Mercy, O., & Taiye, T.B. (2015). Strategic Imperatives of Total Quality Management and Customer Satisfaction in Organizational Sustainability. International Journal of Academic Research in Business and Social Sciences, 5(4), 1-22. https://doi.org/10.6007/IJARBSS/v5-i4/1538Mitreva, E., Cvetkovik, D., Filiposki, O., Taskov, N., & Gjorshevski, H. (2016). The Effects of Total Quality Management Practices on Performance within a Company for Frozen Food in the Republic of Macedonia. TEM Journal, 5(3), 339-346. https://doi.org/10.18421/TEM53-14Morath, C., & Doluschitz, R. (2009). Total Quality Management in the food industry - Current situation and potential in Germany. Applied Studies In Agribusiness And Commerce, 3(3-4), 83-87. https://doi.org/10.19041/APSTRACT/2009/3-4/18Musenze, I.A., & Thomas, M.S. (2020). Development and validation of a total quality management model for Uganda's local governments. Cogent Business and Management, 7(1), 1-22. https://doi.org/10.1080/23311975.2020.1767996Neyestani, B., & Juanzon, J.B.P. (2016). Developing an Appropriate Performance Measurement Framework for Total Quality Management (TQM) in Construction and Other Industries. IRA-International Journal of Technology & Engineering (ISSN 2455-4480), 5(2), 32. https://doi.org/10.21013/jte.v5.n2.p2Ngambi, M.T., & Nkemkiafu, A.G. (2015). The Impact of Total Quality Management on Firm's Organizational Performance Marcel. American Journal of Management, 15(4), 57-76.Nicolaou, N., & Kentas, G. (2017). Total Quality Management Implementation Failure Reasons in Healthcare Sector. Journal of Health Science 5 (2017) 110-113, 5(2), 110-113. https://doi.org/10.17265/2328-7136/2017.02.007Nugroho, T.W., & Nurcahyo, R. (2018). Analysis of Total Quality Management (TQM) implementation in small medium industries. Proceedings of the International Conference on Industrial Engineering and Operations Management, 2018(Jul), 607-618.Oakland, J.S. (2003). Total quality management - Text with cases. In Butterworth-Heinemann (Third Edit). Butterworth-Heinemann.Phan, A.C., Nguyen, H.T., Nguyen, H.A., & Matsui, Y. (2019). Effect of total quality management practices and jit production practices on flexibility performance: Empirical evidence from international manufacturing plants. MDPI Sustainability (Switzerland), 11(11). https://doi.org/10.3390/su11113093Prajogo, D.I., & Brown, A. (2004). The Relationship between TQM Practices and Quality Performance and the Role of Formal TQM Programs: An Australian Empirical Study. Quality Management Journal, 11(4), 31-42. https://doi.org/10.1080/10686967.2004.11919131Ramlawati, & Putra, A.H.P.K. (2018). Total Quality Management as the Key of the Company to Gain the Competitiveness, Performance Achievement and Consumer Satisfaction. International Review of Management and Marketing, 8(5), 60-69.Rogers, R.E. (2013). Implementation of Total Quality Management A Comprehensive Training Program. 1996 by The Haworth Press, Inc. All rights reserved.Sabet, E., Adams, E., & Yazdani, B. (2014). Quality management in heavy duty manufacturing industry: TQM vs. Six Sigma. Total Quality Management and Business Excellence, 27(1-2), 215-225. https://doi.org/10.1080/14783363.2014.972626Sader, S., Husti, I., & Daróczi, M. (2017). Suggested Indicators To Measure the Impact of Industry 4.0 on Total Quality Management. International Scientific Journal: Industry 4.0, 2(6), 298-301. https://stumejournals.com/journals/i4/2017/6/298/pdfSadikoglu, E., & Olcay, H. (2014). The Effects of Total Quality Management Practices on Performance and the Reasons of and the Barriers to TQM Practices in Turkey. Laboratory Management Information Systems: Current Requirements and Future Perspectives, 2014, 996-1027. https://doi.org/10.1155/2014/537605Sainis, G., Haritos, G., Kriemadis, T., & Fowler, M. (2017). The quality journey for Greek SMEs and their financial performance. Production and Manufacturing Research, 5(1), 306-327. https://doi.org/10.1080/21693277.2017.1374891Santos, A.C. de S.G. dos, Carvalho, L.M., Souza, C.F. de, Reis, A. da C., & Freitag, A.E.B. (2019). Total Quality Management: the case of an electricity distribution company. Brazilian Journal of Operations & Production Management, 16(1), 53-65. https://doi.org/10.14488/BJOPM.2019.v16.n1.a5Sari, & Firdaus, A. (2018). The Impact of Total Quality Management Implementation on Small and Medium Manufacturing Companies. Esensi: Jurnal Bisnis Dan Manajemen, 8(1), 67-78. https://doi.org/10.15408/ess.v8i1.5852Sila, I., & Walczak, S. (2017). Universal versus contextual effects on TQM: a triangulation study using neural networks. Production Planning and Control, 28(5), 367-386. https://doi.org/10.1080/09537287.2017.1296598Sivalai, T., & Rojniruttikul, N. (2018). Determinants of the state railway of Thailand's (SRT) total quality management process: SEM analysis. Journal of International Studies, 11(2). https://doi.org/10.14254/2071-8330.2018/11-2/9Small, E.P., Ayyash, L., & Hamouri, K. Al. (2017). Benchmarking Performance of TQM Principals in Electrical Subcontracting in Dubai: A Case Study. Procedia Engineering, 196(June), 622-629. https://doi.org/10.1016/j.proeng.2017.08.050Sousa-Mendes, G.H. de, Gomes-Salgado, E., & Moro-Ferrari, B.E. (2016). Prioritization of TQM practices in Brazilian medical device SMEs using Analytical Hierarchy Process (AHP) Glauco. DYNA (Colombia), 83(197), 195-203. https://doi.org/10.15446/dyna.v83n197.52205Steiber, A., & Alänge, S. (2013). Do TQM principles need to change? Learning from a comparison to Google Inc. Total Quality Management and Business Excellence, 24(1-2), 48-61. https://doi.org/10.1080/14783363.2012.733256Suarez-Barraza, M.F., & Ablanedo-Rosas, J.H. (2014). Total quality management principles: Implementation experience from Mexican organisations. Total Quality Management and Business Excellence, 25(5-6), 546-560. https://doi.org/10.1080/14783363.2013.867606Sukardi, R.A. (2016). Pengaruh Total Quality Management (TQM) Terhadap Kepuasan Pelanggan Pada Matahari Department Store di Plaza Mulia Samarinda. EJournal Administrasi Bisnis, 4(3), 758-772.Sukdeo, N., Pretorius, J.H., & Vermeulen, A. (2017). The role of Total Quality Management (TQM) practices on improving organisational performance in manufacturing and service organisations. Proceedings of the International Conference on Industrial Engineering and Operations Management, 2017(OCT), 1133-1152.Sutrisno, T.F.C.W. (2019). Relationship between Total Quality Management element, operational performance and organizational performance in food production SMEs. Jurnal Aplikasi Manajemen, 17(2), 285-294. https://doi.org/10.21776/ub.jam.2019.017.02.11Sweis, R., Ismaeil, A., Obeidat, B., & Kanaan, R.K. (2019). Reviewing the Literature on Total Quality Management and Organizational Performance. Journal of Business & Management (COES&RJ-JBM), 7(3), 192-215. https://doi.org/10.25255/jbm.2019.7.3.192.215Talib, F., & Rahman, Z. (2015). Identification and prioritization of barriers to total quality management implementation in service industry: An analytic hierarchy process approach. TQM Journal, 27(5), 591-615. https://doi.org/10.1108/TQM-11-2013-0122Tervonen, P., Pahkala, N., & Haapasalo, H. (2009). Development of TQM in steel manufacturers' production. Ibima Business Review, 1-3, 52-59.Tesfaye, G., & Kitaw, D. (2017). A TQM and JIT Integrated Continuous Improvement Model for Organizational Success: An Innovative Framework. Journal of Optimization in Industrial Engineering, 22, 15-23. https://doi.org/10.22094/joie.2017.265Vukomanovic, M., Radujkovic, M., & Nahod, M.M. (2014). EFQM excellence model as the TQM model of the construction industry of southeastern Europe. Journal of Civil Engineering and Management, 20(1), 70-81. https://doi.org/10.3846/13923730.2013.843582Yang, C.O., & Tsai, M.C. (2014). 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    Evaluation of different heat transfer conditions on an automotive turbocharger

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    This paper presents a combination of theoretical and experimental investigations for determining the main heat fluxes within a turbocharger. These investigations consider several engine speeds and loads as well as different methods of conduction, convection, and radiation heat transfer on the turbocharger. A one-dimensional heat transfer model of the turbocharger has been developed in combination with simulation of a turbocharged engine that includes the heat transfer of the turbocharger. Both the heat transfer model and the simulation were validated against experimental measurements. Various methods were compared for calculating heat transfer from the external surfaces of the turbocharger, and one new method was suggested. The effects of different heat transfer conditions were studied on the heat fluxes of the turbocharger using experimental techniques. The different heat transfer conditions on the turbocharger created dissimilar temperature gradients across the turbocharger. The results show that changing the convection heat transfer condition around the turbocharger affects the heat fluxes more noticeably than changing the radiation and conduction heat transfer conditions. Moreover, the internal heat transfers from the turbine to the bearing housing and from the bearing housing to the compressor are significant, but there is an order of magnitude difference between these heat transfer rates.The Swedish Energy Agency and KTH Royal Institute of Technology sponsored this work within the Competence Centre for Gas Exchange (CCGEx).Aghaali, H.; Angström, H.; Serrano Cruz, JR. (2015). Evaluation of different heat transfer conditions on an automotive turbocharger. International Journal of Engine Research. 16(2):137-151. doi:10.1177/1468087414524755S137151162Romagnoli, A., & Martinez-Botas, R. (2012). Heat transfer analysis in a turbocharger turbine: An experimental and computational evaluation. Applied Thermal Engineering, 38, 58-77. doi:10.1016/j.applthermaleng.2011.12.022Romagnoli, A., & Martinez-Botas, R. (2009). Heat Transfer on a Turbocharger Under Constant Load Points. Volume 5: Microturbines and Small Turbomachinery; Oil and Gas Applications. doi:10.1115/gt2009-59618Baines, N., Wygant, K. D., & Dris, A. (2010). The Analysis of Heat Transfer in Automotive Turbochargers. Journal of Engineering for Gas Turbines and Power, 132(4). doi:10.1115/1.3204586Serrano, J. R., Olmeda, P., Páez, A., & Vidal, F. (2010). An experimental procedure to determine heat transfer properties of turbochargers. Measurement Science and Technology, 21(3), 035109. doi:10.1088/0957-0233/21/3/035109Bohn, D., Heuer, T., & Kusterer, K. (2005). Conjugate Flow and Heat Transfer Investigation of a Turbo Charger. Journal of Engineering for Gas Turbines and Power, 127(3), 663-669. doi:10.1115/1.1839919Galindo, J., Luján, J. M., Serrano, J. R., Dolz, V., & Guilain, S. (2006). Description of a heat transfer model suitable to calculate transient processes of turbocharged diesel engines with one-dimensional gas-dynamic codes. Applied Thermal Engineering, 26(1), 66-76. doi:10.1016/j.applthermaleng.2005.04.010Sirakov, B., & Casey, M. (2012). Evaluation of Heat Transfer Effects on Turbocharger Performance. Journal of Turbomachinery, 135(2). doi:10.1115/1.4006608Serrano, J., Olmeda, P., Arnau, F., Reyes-Belmonte, M., & Lefebvre, A. (2013). Importance of Heat Transfer Phenomena in Small Turbochargers for Passenger Car Applications. SAE International Journal of Engines, 6(2), 716-728. doi:10.4271/2013-01-0576Larsson, P.-I., Westin, F., Andersen, J., Vetter, J., & Zumeta, A. (2009). Efficient turbo charger testing. MTZ worldwide, 70(7-8), 16-21. doi:10.1007/bf03226965Aghaali, H., & Ångström, H.-E. (2012). Turbocharged SI-Engine Simulation With Cold and Hot-Measured Turbocharger Performance Maps. Volume 5: Manufacturing Materials and Metallurgy; Marine; Microturbines and Small Turbomachinery; Supercritical CO2 Power Cycles. doi:10.1115/gt2012-68758Leufven, O., & Eriksson, L. (2012). Investigation of compressor correction quantities for automotive applications. International Journal of Engine Research, 13(6), 588-606. doi:10.1177/146808741243901

    Design and simulation of a resorbable bone fixation plate made by additive manufacturing for femoral mid-SHAFT fractures

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    [EN] Finite element method has been employed to establish the feasibility of a fixation plate made of PLA by additive manufacturing for femoral shaft fractures. For this purpose, Von Mises stress and the pressure contact between bones had been analysed. The proposed design has been compared with an actual titanium fixation plate as a point of reference.J. Ivorra-Martinez is funded with a Formación de Profesorado Universitario (FPU) grant from the Spanish Government (Ministerio de Ciencia, Innovación y Universidades), with reference FPU19/01759.Ivorra Martínez, J.; Sellés Cantó, MÁ.; Sánchez Caballero, S.; Boronat Vitoria, T. (2021). Design and simulation of a resorbable bone fixation plate made by additive manufacturing for femoral mid-SHAFT fractures. Journal of Applied Research in Technology & Engineering. 2(1):11-16. https://doi.org/10.4995/jarte.2021.14712OJS111621Alizadeh-Osgouei, M., Li, Y., Wen, C. (2019). A comprehensive review of biodegradable synthetic polymerceramic composites and their manufacture for biomedical applications. Bioactive materials, 4(1), 22-36. https://doi.org/10.1016/j.bioactmat.2018.11.003Arabnejad, S., Johnston, B., Tanzer, M., Pasini, D. (2017). Fully porous 3D printed titanium femoral stem toreduce stress-shielding following total hip arthroplasty. Journal of Orthopaedic Research, 35(8), 1774-1783.https://doi.org/10.1002/jor.23445Elkins, J., Marsh, J.L., Lujan, T., Peindl, R., Kellam, J., Anderson, D D., & Lack, W. (2016). Motion predicts clinical callus formation: construct-specific finite element analysis of supracondylar femoral fractures. The Journal of bone and joint surgery. American volume, 98(4), 276. https://doi.org/10.2106/JBJS.O.00684Geetha, M., Singh, A.K., Asokamani, R., Gogia, A.K. (2009). Ti based biomaterials, the ultimate choice for orthopaedic implants-a review. Progress in materials science, 54(3), 397-425. https://doi.org/10.1016/j.pmatsci.2008.06.004George, D., Allena, R., Remond, Y. (2017). Mechanobiological stimuli for bone remodeling: mechanical energy, cell nutriments and mobility. Computer Methods in Biomechanics and Biomedical Engineering, 20(sup1), S91-S92, https://doi.org/10.1080/10255842.2017.1382876Guastaldi, F., Martini, A., Rocha, E., Hochuli-Vieira, E., Guastaldi, A. (2019). Ti-15Mo Alloy Decreases the Stress Concentration in Mandibular Angle Fracture Internal Fixation Hardware. Journal of Maxillofacial and Oral Surgery, 19, 314-320. https://doi.org/10.1007/s12663-019-01251-8Hayes, J., Richards, R. (2010). The use of titanium and stainless steel in fracture fixation. Expert review of medical devices, 7(6), 843-853. https://doi.org/10.1586/erd.10.53Heimbach, B., Grassie, K., Shaw, M.T., Olson, J.R., Wei, M. (2017). Effect of hydroxyapatite concentration on highmodulus composite for biodegradable bone-fixation devices. Journal of Biomedical Materials Research Part B: Applied Biomaterials, 105(7), 1963-1971. https://doi.org/10.1002/jbm.b.33713Jahagirdar, R., Scammell, B.E. (2009). Principles of fracture healing and disorders of bone union. Surgery (Oxford), 27(2), 63-69. https://doi.org/10.1016/j.mpsur.2008.12.011Kanno, T., Sukegawa, S., Furuki, Y., Nariai, Y., Sekine, J. (2018). Overview of innovative advances in bioresorbable plate systems for oral and maxillofacial surgery. Japanese Dental Science Review, 54(3), 127-138. https://doi.org/10.1016/j.jdsr.2018.03.003Kim, H.J., Chang, S.H., Jung, H.J. (2012). The simulation of tissue differentiation at a fracture gap using a mechanoregulation theory dealing with deviatoric strains in the presence of a composite bone plate. Composites Part B: Engineering, 43(3), 978-987. https://doi.org/10.1016/j.compositesb.2011.09.011Klein, K.F., Hu, J., Reed, M.P., Hoff, C.N., Rupp, J.D. (2015). Development and validation of statistical models of femur geometry for use with parametric finite element models. Annals of biomedical engineering, 43(10), 2503-2514. https://doi.org/10.1007/s10439-015-1307-6Li, J., Li, Z., Ye, L., Zhao, X., Coates, P., Caton-Rose, F. (2017). Structure and biocompatibility improvement mechanism of highly oriented poly (lactic acid) produced by solid die drawing. European Polymer Journal, 97, 68-76. https://doi.org/10.1016/j.eurpolymj.2017.09.038Li, J., Qin, L., Yang, K., Ma, Z., Wang, Y., Cheng, L., Zhao, D. (2020). Materials evolution of bone plates for internal fixation of bone fractures: A review. Journal of Materials Science & Technology, 36, 190-208. https://doi.org/10.1016/j.jmst.2019.07.024Li, J., Yin, P., Zhang, L., Chen, H., Tang, P. (2019). Medial anatomical buttress plate in treating displaced femoral neck fracture a finite element analysis. Injury, 50(11), 1895-1900. https://doi.org/10.1016/j.injury.2019.08.024Liu, B., Zhang, S., Zhang, J., Xu, Z., Chen, Y., Liu, S., Yang, L. (2019). A personalized preoperative modeling system for internal fixation plates in long bone fracture surgery-A straightforward way from CT images to plate model. The International Journal of Medical Robotics and Computer Assisted Surgery, 15(5), e2029. https://doi.org/10.1002/rcs.2029McClellan, R.T. (2013). The variable angle hip fracture nail relative to the Gamma 3: A finite element analysis illustrating the same stiffness and fatigue characteristics. Advances in orthopedics, 2013. https://doi.org/10.1155/2013/143801Murr, L.E. (2016). Frontiers of 3D printing/additive manufacturing: from human organs to aircraft fabrication. Journal of Materials Science & Technology, 32(10), 987-995. https://doi.org/10.1016/j.jmst.2016.08.011Narayanan, G., Vernekar, V.N., Kuyinu, E.L., Laurencin, C.T. (2016). Poly (lactic acid)-based biomaterials for orthopaedic regenerative engineering. Advanced drug delivery reviews, 107, 247-276. https://doi.org/10.1016/j.addr.2016.04.015Nurettin, D., Burak, B. (2018). Feasibility of carbon-fiber-reinforced polymer fixation plates for treatment of atrophic mandibular fracture: A finite element method. Journal of Cranio-Maxillofacial Surgery, 46(12), 2182-2189. https://doi.org/10.1016/j.jcms.2018.09.030Parthasarathy, J. (2015). 14 Additive Manufacturing of Medical Devices. Additive Manufacturing: Innovations, Advances, and Applications, 369.Ridzwan, M., Shuib, S., Hassan, A., Shokri, A., Ibrahim, M. (2006). Optimization in implant topology to reduce stress shielding problem. Journal of Applied Sciences, 6(13), 2768-2773. https://doi.org/10.3923/jas.2006.2768.2773Sariali, E., Mouttet, A., Pasquier, G., Durante, E. (2009). Three-dimensional hip anatomy in osteoarthritis: analysis of the femoral offset. The Journal of arthroplasty, 24(6), 990-997. https://doi.org/10.1016/j.arth.2008.04.031Singh, D., Singh, R., Boparai, K.S. (2018). Development and surface improvement of FDM pattern based investment casting of biomedical implants: A state of art review. Journal of Manufacturing Processes, 31, 80-95. https://doi.org/10.1016/j.jmapro.2017.10.026Spiridon, I., Tanase, C.E. (2018). Design, characterization and preliminary biological evaluation of new lignin-PLA biocomposites. International journal of biological macromolecules, 114, 855-863. https://doi.org/10.1016/j.ijbiomac.2018.03.140Tang, G., Liu, S.L., Wang, D.M., Wei, G.F., Wang, C.T. (2013). Finite element analysis in femoral fixation with TA3 titanium compressioll plate. In Advanced Materials Research, 647, 16-19. Trans Tech Publications Ltd. https://doi.org/10.4028/www.scientific.net/AMR.647.16Tymrak, B., Kreiger, M., Pearce, J.M. (2014). Mechanical properties of components fabricated with open-source 3-D printers under realistic environmental conditions. Materials & Design, 58, 242-246. https://doi.org/10.1016/j.matdes.2014.02.038Wang, A.Y., Peng, J., Sun, M.X., Sui, X., Wang, X., Tian, Y., Lu, S.B. (2006). Biomechanical comparison of different structural bone grafting in femoral heads' defects of weight-bearing region. Journal of Medical Biomechanics, 4.Wang, J., Ma, J.X., Lu, B., Bai, H.H., Wang, Y., Ma, X.L. (2020). Comparative finite element analysis of three implants fixing stable and unstable subtrochanteric femoral fractures: Proximal Femoral Nail Antirotation (PFNA), Proximal Femoral Locking Plate (PFLP), and Reverse Less Invasive Stabilization System (LISS). Orthopaedics & Traumatology: Surgery & Research, 106(1), 95-101. https://doi.org/10.1016/j.otsr.2019.04.027Wang, X., Xu, S., Zhou, S., Xu, W., Leary, M., Choong, P., Xie, Y.M. (2016). Topological design and additive manufacturing of porous metals for bone scaffolds and orthopaedic implants: A review. Biomaterials, 83, 127-141. https://doi.org/10.1016/j.biomaterials.2016.01.012Wu, C., Zheng, K., Fang, J., Steven, G.P., Li, Q. (2020). Time-dependent topology optimization of bone plates considering bone remodeling. Computer Methods in Applied Mechanics and Engineering, 359, 112702. https://doi.org/10.1016/j.cma.2019.112702Wu, K.J., Li, S.H., Yeh, K.T., Chen, H., Lee, R.P., Yu, T.C., Wang, J.H. (2019). The risk factors of nonunion after intramedullary nailing fixation of femur shaft fracture in middle age patients. Medicine, 98(29). https://doi.org/10.1097/MD.0000000000016559Wu, X., Wang, Z., Li, H., Li, Y., Wang, H., Tian, W. (2019). Biomechanical evaluation of osteoporotic fracture: Metal fixation versus absorbable fixation in Sawbones models. Injury, 50(7), 1272-1276. https://doi.org/10.1016/j.injury.2019.05.023Zhao, X., Niinomi, M., Nakai, M., Hieda, J., Ishimoto, T., Nakano, T. (2012). Optimization of Cr content of metastable β-type Ti-Cr alloys with changeable Young's modulus for spinal fixation applications. Acta biomaterialia, 8(6), 2392-2400. https://doi.org/10.1016/j.actbio.2012.02.01

    Identifying and classifying attributes of packaging for customer satisfaction-A Kano Model Approach

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    [EN] The packaging industry in India is predicted to grow at 18% annually. In recent years Packaging becomes a potential marketing tool. The marketer should design the packaging of high quality from customer perspective.  As the research in the area of packaging is very few, study of quality attributes of Packaging is the need of the hour and inevitable. An empirical research was conducted by applying Kano Model. The researcher is interested to find out the perception of the customers on 22 quality attributes of packaging. 500 respondents which were selected randomly were asked about their experience of packing on everyday commodities through a well-structured questionnaire.  The classification of attribute as must-be quality, one-dimensional quality, attractive quality, indifferent quality and reverse quality was done by three methods. Marketer should make a note of it and prioritise the attributes for customer satisfaction.Dash, SK. (2021). Identifying and classifying attributes of packaging for customer satisfaction-A Kano Model Approach. International Journal of Production Management and Engineering. 9(1):57-64. https://doi.org/10.4995/ijpme.2021.13683OJS576491Bakhitar, A.,Hannan, A., Basit, A., Ahmad, J.(2015). Prioritization of value based services of software by using AHP and fuzzy KANO model. International Conference on Computational and Social Sciences, 8, 25- 27.Basfirinci, C., Mitra, A. (2015). A cross cultural investigation of airlines service quality through integration of Servqual and the Kano model. Journal of Air Transport Management, 42(1), 239-48. https://doi.org/10.1016/j.jairtraman.2014.11.005Berger, C., Blauth, R., Boger, D., Bolster, C., Burchill, G., DuMouchel, W., Pouliot, F., Richter, R., Rubinoff, A., Shen, D., Timko, M., Walden, D. (1993). Kano's methods for understanding customer-defined quality. The Center for Quality of Management Journal, 2(4), 2-36.Brown, G.H. (1950). Measuring consumer attitudes towards products. Journal of Marketing, 14(5), 691-98. https://doi.org/10.1177/002224295001400505Chaudha, A., Jain, R., Singh, A.R., Mishra, P.K. (2011). Integration of Kano's Model into Quality Function Deployment (QFD). Journal Advice Manufacture Technology, 53, 689-698. https://doi.org/10.1007/s00170-010-2867-0Cole, R.E. (2001). From continuous improvement to continuous innovation. Quality Management Journal, 8(4), 7-21. https://doi.org/10.1080/10686967.2001.11918977Dash, S.K. (2019). Application of Kano Model in Identifying Attributes. A Case Study on School Bus Services. International Journal of Management Studies, 6(1), 31-37. https://doi.org/10.18843/ijms/v6i1(3)/03Dziuba, S.T., Śron, B. (2014). FAM-FMC system as an alternative element of the software used in a grain and flour milling enterprise. Production Engineering Archives, 4(3),29-31. https://doi.org/10.30657/pea.2014.04.08Ernzer, M., Kopp, K.(2003). Application of KANO method to life cycle design. IEEE Proceedings of Eco Design: Third International Symposium on Environmentally Conscious De-sign and Inverse Manufacturing, Tokyo Japan, December 8-11, 383-389. https://doi.org/10.1109/ECODIM.2003.1322697Feigenbaum, A.V. (1991).Total Quality Control. McGraw-Hill. Fundin, A., Nilsson, L. (2003). Using Kano's theory of attractive quality to better understand customer satisfaction with e-services. Asian Journal on Quality, 4(2), 32-49. https://doi.org/10.1108/15982688200300018Friman, M., Edvardsson, B. (2003). A content analysis of complaints and compliments. Managing Service Quality, 13(1), 20-26. https://doi.org/10.1108/09604520310456681Garvin, D.A. (1987). Competing on the eight dimensions of quality. Harvard Business Review, 65(6), 101-109.Hanan, M., Karp, P. (1989). Customer satisfaction, how to maximise, measure and market your company's "ultimate product". AMACOM.Herzberg, F., Bernard, M., Snyderman, B.B. (1959). The Motivation to Work. John Wiley and Sons.Hoch, S.J., Ha, Y.W. (1986). Consumer learning: advertising and the ambiguity of product experience. Journal of Consumer Research, 13, 221-33.https://doi.org/10.1086/209062Johnson, M.D., Nilsson, L. (2003). The Importance of Reliability and Customization from Goods to Services. Quality Management Journal, 10(1), 8-19. https://doi.org/10.1080/10686967.2003.11919049Kano, N., Seraku, N., Takahashi, F., Tsuji, S. (1984). Attractive Quality and Must-Be Quality. Journal of the Japanese Society for Quality Control, 41, 39-48.Kapalle, P.K, Lehmann, D.R. (1995). The effects of advertised and observed quality on expectations about new product quality. Journal of Marketing Research, 32(8), 280-90. https://doi.org/10.1177/002224379503200304Lee, M.C., Newcomb, J.F. (1997). Applying the Kano methodology to meet customer requirements: NASA's microgravity science program. Quality Management Journal, 4(3), 95-110. https://doi.org/10.1080/10686967.1997.11918805Löfgren, M. (2005). Winning at the first and second moments of truth: An exploratory study. Journal of Service Theory and Practice, 15(1), 102-15. https://doi.org/10.1108/09604520510575290Löfgren, M., Witell, L. (2005). Kano's Theory of Attractive Quality and Packaging. Quality Management Journal, 12(3), 7-20. https://doi.org/10.1080/10686967.2005.11919257Matzler, K., Hinterhuber, H.H., Bailom, F., Sauerwein, E. (1996). How to delight your customers. Journal of Product & Brand Management, 5(2), 6-18. https://doi.org/10.1108/10610429610119469Miarka, D., Żukowska, J., Siwek, A., Nowacka,A., Nowak, D. (2015). Microbial hazards reduction during creamy cream cheese production. Production Engineering Archives, 6(1), 39-44. https://doi.org/10.30657/pea.2015.06.10Nelson, P. (1970), Information and consumer behaviour. Journal of Political Economy, 78, 311-29. https://doi.org/10.1086/259630Nilsson-Witell, L, Fundin, A. (2005). Dynamics of service attributes: a test of Kano's theory of attractive quality. International Journal of Service Industry Management, 16(2), 152-168. https://doi.org/10.1108/09564230510592289Parasuraman, A. (1997). Reflections on gaining competitive advantage through customer value. Academy of Marketing Science Journal, 25(2), 154-61. https://doi.org/10.1007/BF02894351Parasuraman, A., Colby, C.L. (2001). Techno-Ready Marketing. Free Press.Qiting, P., Uno, N., Kubota, Y. (2013). Kano Model Analysis of Customer Needs and Satisfaction at the Shanghai Disneyland. In Proceedings of the 5th Intl Congress of the Intl Association of Societies of Design Research, Tokyo, Japan. http://design-cu.jp/iasdr2013/papers/1835-1b.pdf Accessed on January 2021.Sauerwein, E., Bailom, F., Matzler, K., Hinterhuber, H.H. (1996). The Kano Model: How to delight your Customers. Volume I of the IX. International Working Seminar on Production Economics, Innsbruck/Igls/Austria, February 19-23 1996, pp. 313-327. https://is.muni. cz/el/econ/podzim2009/MPH_MAR2/um/9899067/THE_KANO_MODEL_-_HOW_TO_DELIGHT_YOUR_CUSTOMERS.pdfShewhart, W.A. (1931). Economic Control of Quality of Manufactured Product. D. Van Nostrand Company, Inc.Underwood, R.L., Klein, N.M. (2002). Packaging as Brand Communication: Effects of Product Pictures on Consumer Responses to the Package and Brand. Journal of Marketing Theory and Practice, 10(4), 58-68. https://doi.org/10.1080/10696679.2002.11501926Underwood, R.L. Klein, N.M., Burke, R.R. (2001). Packaging communication: attentional effects of product imagery. Journal of Product & Brand Management, 10(7), 403-22. https://doi.org/10.1108/10610420110410531Watson, G.H. (2003), "Customer focus and competitiveness", in Stephens, K.S. (Ed.), Six Sigma and Related Studies in the Quality Disciplines, ASQ Quality Press, Milwaukee, WI.Williams, D. (2020). The future of the packaging industry in India. Packaging Gateway. https://packaging-gateway.com/features/futurepackaging-industry-in-india Accessed on January 2021.Williams,H., Wikström,F., Löfgren.M. (2008). A life cycle perspective on environmental effects of customer focused packaging development." Journal of Cleaner Production, 16(7), 853-859. https://doi.org/10.1016/j.jclepro.2007.05.006Woodruff, R.B. (1997). Customer value: the next source for competitive advantage. Journal of Academy of Marketing Science, 25(2), 139- 53. https://doi.org/10.1007/BF02894350Zeithaml, V.A. (1988). Consumer perceptions of price, quality, and value: a means-end model and synthesis of evidence. Journal of Marketing, 52, 2-22. https://doi.org/10.1177/00222429880520030

    Numerical analysis of the influence of micro-voids on fretting fatigue crack initiation lifetime

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    [EN] In this paper, the influence of the heterogeneity in the predicted crack initiation lifetime under fretting fatigue conditions is analysed for a regular and a random distribution of micro-voids. A critical plane analysis with two multiaxial damage criteria is performed to assess the crack initiation lifetime. The predicted initiation lifetime in the heterogeneous material is compared with the results obtained in the homogeneous case. The numerical results show that the heterogeneity has a noticeable influence on the predicted initiation lifetime. Furthermore, the numerical model suggests that a crack may firstly initiate at the upper edge of the micro-voids located close to the contact edge, leading to a mean reduction of the predicted crack initiation lifetime. However, in some cases, the introduction of micro-voids reduces the stress intensity at the contact edge and thus decreasing the predicted crack initiation lifetime.The authors gratefully acknowledge the financial support given by the Spanish Ministry of Economy and Competitiveness and the FEDER program through the projects DPI2017-89197-C2-1-R, DPI2017-89197-C2-2-R and the FPI subprogram with the reference BES-2015-072070. The support of the Generalitat Valenciana, Programme PROMETEO 2016/007, is also acknowledged.r The last author would like to acknowledge the financial support of the Research Foundation-Flanders (FWO), The Luxembourg National Research Fund (FNR) and Slovenian Research Agency (ARRS) in the framework of the FWO Lead Agency project: G018916N 'Multi-analysis of fretting fatigue using physical and virtual experiments'.Infante-García, D.; Giner Maravilla, E.; Miguélez, MH.; Wahab, MA. (2019). Numerical analysis of the influence of micro-voids on fretting fatigue crack initiation lifetime. Tribology International. 135:121-129. https://doi.org/10.1016/j.triboint.2019.02.032S121129135Hills, D. A., & Nowell, D. (2014). Mechanics of fretting fatigue—Oxford’s contribution. Tribology International, 76, 1-5. doi:10.1016/j.triboint.2013.09.015Hojjati-Talemi, R., Wahab, M. A., Giner, E., & Sabsabi, M. (2013). Numerical Estimation of Fretting Fatigue Lifetime Using Damage and Fracture Mechanics. Tribology Letters, 52(1), 11-25. doi:10.1007/s11249-013-0189-8Nowell, D., Dini, D., & Hills, D. A. (2006). Recent developments in the understanding of fretting fatigue. Engineering Fracture Mechanics, 73(2), 207-222. doi:10.1016/j.engfracmech.2005.01.013Amargier, R., Fouvry, S., Chambon, L., Schwob, C., & Poupon, C. (2010). Stress gradient effect on crack initiation in fretting using a multiaxial fatigue framework. International Journal of Fatigue, 32(12), 1904-1912. doi:10.1016/j.ijfatigue.2010.06.004PROUDHON, H., FOUVRY, S., & BUFFIERE, J. (2005). A fretting crack initiation prediction taking into account the surface roughness and the crack nucleation process volume. International Journal of Fatigue, 27(5), 569-579. doi:10.1016/j.ijfatigue.2004.09.001Pereira, K., & Abdel Wahab, M. (2017). Fretting fatigue crack propagation lifetime prediction in cylindrical contact using an extended MTS criterion for non-proportional loading. Tribology International, 115, 525-534. doi:10.1016/j.triboint.2017.06.026Hojjati-Talemi, R., Abdel Wahab, M., De Pauw, J., & De Baets, P. (2014). Prediction of fretting fatigue crack initiation and propagation lifetime for cylindrical contact configuration. Tribology International, 76, 73-91. doi:10.1016/j.triboint.2014.02.017Noraphaiphipaksa, N., Manonukul, A., & Kanchanomai, C. (2017). Fretting Fatigue with Cylindrical-On-Flat Contact: Crack Nucleation, Crack Path and Fatigue Life. Materials, 10(2), 155. doi:10.3390/ma10020155NAVARRO, C., MUNOZ, S., & DOMINGUEZ, J. (2008). On the use of multiaxial fatigue criteria for fretting fatigue life assessment. International Journal of Fatigue, 30(1), 32-44. doi:10.1016/j.ijfatigue.2007.02.018Bhatti, N. A., & Abdel Wahab, M. (2017). A numerical investigation on critical plane orientation and initiation lifetimes in fretting fatigue under out of phase loading conditions. Tribology International, 115, 307-318. doi:10.1016/j.triboint.2017.05.036Sabsabi, M., Giner, E., & Fuenmayor, F. J. (2011). Experimental fatigue testing of a fretting complete contact and numerical life correlation using X-FEM. International Journal of Fatigue, 33(6), 811-822. doi:10.1016/j.ijfatigue.2010.12.012Szolwinski, M. P., & Farris, T. N. (1998). Observation, analysis and prediction of fretting fatigue in 2024-T351 aluminum alloy. Wear, 221(1), 24-36. doi:10.1016/s0043-1648(98)00264-6Gong, H., Rafi, K., Gu, H., Starr, T., & Stucker, B. (2014). Analysis of defect generation in Ti–6Al–4V parts made using powder bed fusion additive manufacturing processes. Additive Manufacturing, 1-4, 87-98. doi:10.1016/j.addma.2014.08.002RAJASEKARAN, B., GANESHSUNDARARAMAN, S., JOSHI, S., & SUNDARARAJAN, G. (2009). Effect of grinding on plain fatigue and fretting fatigue behaviour of detonation gun sprayed Cu–Ni–In coating on Al–Mg–Si alloy. International Journal of Fatigue, 31(4), 791-796. doi:10.1016/j.ijfatigue.2008.03.003Chan, L. C., Lu, X. Z., & Yu, K. M. (2015). Multiscale approach with RSM for stress–strain behaviour prediction of micro-void-considered metal alloy. Materials & Design, 83, 129-137. doi:10.1016/j.matdes.2015.05.064Bhatti, N. A., & Abdel Wahab, M. (2018). Fretting fatigue crack nucleation: A review. Tribology International, 121, 121-138. doi:10.1016/j.triboint.2018.01.029Marco, M., Infante-García, D., Díaz-Álvarez, J., & Giner, E. (2019). Relevant factors affecting the direction of crack propagation in complete contact problems under fretting fatigue. Tribology International, 131, 343-352. doi:10.1016/j.triboint.2018.10.048Muñoz, S., Navarro, C., & Domínguez, J. (2007). Application of fracture mechanics to estimate fretting fatigue endurance curves. Engineering Fracture Mechanics, 74(14), 2168-2186. doi:10.1016/j.engfracmech.2006.10.010Giner, E., Sabsabi, M., Ródenas, J. J., & Javier Fuenmayor, F. (2014). Direction of crack propagation in a complete contact fretting-fatigue problem. International Journal of Fatigue, 58, 172-180. doi:10.1016/j.ijfatigue.2013.03.001Kumar, D., Biswas, R., Poh, L. H., & Wahab, M. A. (2017). Fretting fatigue stress analysis in heterogeneous material using direct numerical simulations in solid mechanics. Tribology International, 109, 124-132. doi:10.1016/j.triboint.2016.12.033Mayer, H., Papakyriacou, M., Zettl, B., & Stanzl-Tschegg, S. . (2003). Influence of porosity on the fatigue limit of die cast magnesium and aluminium alloys. International Journal of Fatigue, 25(3), 245-256. doi:10.1016/s0142-1123(02)00054-3Taylor, D. (2008). The theory of critical distances. Engineering Fracture Mechanics, 75(7), 1696-1705. doi:10.1016/j.engfracmech.2007.04.007Araújo, J. (2002). The effect of rapidly varying contact stress fields on fretting fatigue. International Journal of Fatigue, 24(7), 763-775. doi:10.1016/s0142-1123(01)00191-8McDiarmid, D. L. (1991). A GENERAL CRITERION FOR HIGH CYCLE MULTIAXIAL FATIGUE FAILURE. Fatigue & Fracture of Engineering Materials and Structures, 14(4), 429-453. doi:10.1111/j.1460-2695.1991.tb00673.xSocie, D. (1987). Multiaxial Fatigue Damage Models. Journal of Engineering Materials and Technology, 109(4), 293-298. doi:10.1115/1.3225980Gates, N., & Fatemi, A. (2016). Multiaxial variable amplitude fatigue life analysis including notch effects. International Journal of Fatigue, 91, 337-351. doi:10.1016/j.ijfatigue.2015.12.011El Haddad, M. H., Dowling, N. E., Topper, T. H., & Smith, K. N. (1980). J integral applications for short fatigue cracks at notches. International Journal of Fracture, 16(1), 15-30. doi:10.1007/bf00042383Kim, J., Gao, X., & Srivatsan, T. S. (2004). Modeling of void growth in ductile solids: effects of stress triaxiality and initial porosity. Engineering Fracture Mechanics, 71(3), 379-400. doi:10.1016/s0013-7944(03)00114-0Fatemi, A., & Socie, D. F. (1988). A CRITICAL PLANE APPROACH TO MULTIAXIAL FATIGUE DAMAGE INCLUDING OUT-OF-PHASE LOADING. Fatigue & Fracture of Engineering Materials and Structures, 11(3), 149-165. doi:10.1111/j.1460-2695.1988.tb01169.xLykins, C. (2001). Combined experimental–numerical investigation of fretting fatigue crack initiation. International Journal of Fatigue, 23(8), 703-711. doi:10.1016/s0142-1123(01)00029-

    Improving Distributed Decision Making in Inventory Management: A Combined ABC-AHP Approach Supported by Teamwork

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    [EN] The need of organizations to ensure service levels that impact on customer satisfaction has required the design of collaborative processes among stakeholders involved in inventory decision making. The increase of quantity and variety of items, on the one hand, and demand and customer expectations, on the other hand, are transformed into a greater complexity in inventory management, requiring effective communication and agreements between the leaders of the logistics processes. Traditionally, decision making in inventory management was based on approaches conditioned only by cost or sales volume. These approaches must be overcome by others that consider multiple criteria, involving several areas of the companies and taking into account the opinions of the stakeholders involved in these decisions. Inventory management becomes part of a complex system that involves stakeholders from different areas of the company, where each agent has limited information and where the cooperation between such agents is key for the system's performance. In this paper, a distributed inventory control approach was used with the decisions allowing communication between the stakeholders and with a multicriteria group decision-making perspective. This work proposes a methodology that combines the analysis of the value chain and the AHP technique, in order to improve communication and the performance of the areas related to inventory management decision making. This methodology uses the areas of the value chain as a theoretical framework to identify the criteria necessary for the application of the AHP multicriteria group decision-making technique. These criteria were defined as indicators that measure the performance of the areas of the value chain related to inventory management and were used to classify ABC inventory of the products according to these selected criteria. Therefore, the methodology allows us to solve inventory management DDM based on multicriteria ABC classification and was validated in a Colombian company belonging to the graphic arts sector.Pérez Vergara, IG.; Arias Sánchez, JA.; Poveda Bautista, R.; Diego-Mas, JA. (2020). Improving Distributed Decision Making in Inventory Management: A Combined ABC-AHP Approach Supported by Teamwork. Complexity. 2020:1-13. https://doi.org/10.1155/2020/6758108S1132020Poveda-Bautista, R., Baptista, D. C., & García-Melón, M. (2012). Setting competitiveness indicators using BSC and ANP. International Journal of Production Research, 50(17), 4738-4752. doi:10.1080/00207543.2012.657964Castro Zuluaga, C. A., Velez Gallego, M. C., & Catro Urrego, J. A. (2011). Clasificación ABC Multicriterio: Tipos de Criterios y efectos en la asignación de pesos. ITECKNE, 8(2). doi:10.15332/iteckne.v8i2.35Morash, E. A., & Clinton, S. R. (1998). Supply Chain Integration: Customer Value through Collaborative Closeness versus Operational Excellence. Journal of Marketing Theory and Practice, 6(4), 104-120. doi:10.1080/10696679.1998.11501814Fabbe-Costes, N. (2015). Évaluer la création de valeurdu Supply Chain Management. Logistique & Management, 23(4), 41-50. doi:10.1080/12507970.2015.11758621Flores, B. E., & Clay Whybark, D. (1986). Multiple Criteria ABC Analysis. International Journal of Operations & Production Management, 6(3), 38-46. doi:10.1108/eb054765Partovi, F. Y., & Burton, J. (1993). Using the Analytic Hierarchy Process for ABC Analysis. International Journal of Operations & Production Management, 13(9), 29-44. doi:10.1108/01443579310043619Balaji, K., & Kumar, V. S. S. (2014). Multicriteria Inventory ABC Classification in an Automobile Rubber Components Manufacturing Industry. Procedia CIRP, 17, 463-468. doi:10.1016/j.procir.2014.02.044Ramanathan, R. (2006). ABC inventory classification with multiple-criteria using weighted linear optimization. Computers & Operations Research, 33(3), 695-700. doi:10.1016/j.cor.2004.07.014Van Kampen, T. J., Akkerman, R., & Pieter van Donk, D. (2012). SKU classification: a literature review and conceptual framework. International Journal of Operations & Production Management, 32(7), 850-876. doi:10.1108/01443571211250112Flores, B. E., Olson, D. L., & Dorai, V. K. (1992). Management of multicriteria inventory classification. Mathematical and Computer Modelling, 16(12), 71-82. doi:10.1016/0895-7177(92)90021-cGajpal, P. P., Ganesh, L. S., & Rajendran, C. (1994). Criticality analysis of spare parts using the analytic hierarchy process. International Journal of Production Economics, 35(1-3), 293-297. doi:10.1016/0925-5273(94)90095-7Scala, N. M., Rajgopal, J., & Needy, K. L. (2014). Managing Nuclear Spare Parts Inventories: A Data Driven Methodology. IEEE Transactions on Engineering Management, 61(1), 28-37. doi:10.1109/tem.2013.2283170Hadad, Y., & Keren, B. (2013). ABC inventory classification via linear discriminant analysis and ranking methods. International Journal of Logistics Systems and Management, 14(4), 387. doi:10.1504/ijlsm.2013.052744Altay Guvenir, H., & Erel, E. (1998). Multicriteria inventory classification using a genetic algorithm. European Journal of Operational Research, 105(1), 29-37. doi:10.1016/s0377-2217(97)00039-8Rezaei, J., & Dowlatshahi, S. (2010). A rule-based multi-criteria approach to inventory classification. International Journal of Production Research, 48(23), 7107-7126. doi:10.1080/00207540903348361Hatefi, S. M., Torabi, S. A., & Bagheri, P. (2013). Multi-criteria ABC inventory classification with mixed quantitative and qualitative criteria. International Journal of Production Research, 52(3), 776-786. doi:10.1080/00207543.2013.838328Ishizaka, A., Pearman, C., & Nemery, P. (2012). AHPSort: an AHP-based method for sorting problems. International Journal of Production Research, 50(17), 4767-4784. doi:10.1080/00207543.2012.657966Yu, M.-C. (2011). Multi-criteria ABC analysis using artificial-intelligence-based classification techniques. Expert Systems with Applications, 38(4), 3416-3421. doi:10.1016/j.eswa.2010.08.127Tsai, C.-Y., & Yeh, S.-W. (2008). A multiple objective particle swarm optimization approach for inventory classification. International Journal of Production Economics, 114(2), 656-666. doi:10.1016/j.ijpe.2008.02.017Aydin Keskin, G., & Ozkan, C. (2013). Multiple Criteria ABC Analysis with FCM Clustering. Journal of Industrial Engineering, 2013, 1-7. doi:10.1155/2013/827274Lolli, F., Ishizaka, A., & Gamberini, R. (2014). New AHP-based approaches for multi-criteria inventory classification. International Journal of Production Economics, 156, 62-74. doi:10.1016/j.ijpe.2014.05.015Raja, A. M. L., Ai, T. J., & Astanti, R. D. (2016). A Clustering Classification of Spare Parts for Improving Inventory Policies. IOP Conference Series: Materials Science and Engineering, 114, 012075. doi:10.1088/1757-899x/114/1/012075Zowid, F. M., Babai, M. Z., Douissa, M. R., & Ducq, Y. (2019). Multi-criteria inventory ABC classification using Gaussian Mixture Model. IFAC-PapersOnLine, 52(13), 1925-1930. doi:10.1016/j.ifacol.2019.11.484Babai, M. Z., Ladhari, T., & Lajili, I. (2014). On the inventory performance of multi-criteria classification methods: empirical investigation. International Journal of Production Research, 53(1), 279-290. doi:10.1080/00207543.2014.952791Schneeweiss, C. (2003). Distributed decision making––a unified approach. European Journal of Operational Research, 150(2), 237-252. doi:10.1016/s0377-2217(02)00501-5Saaty, T. L. (2008). Decision making with the analytic hierarchy process. International Journal of Services Sciences, 1(1), 83. doi:10.1504/ijssci.2008.017590Cakir, O., & Canbolat, M. S. (2008). A web-based decision support system for multi-criteria inventory classification using fuzzy AHP methodology. Expert Systems with Applications, 35(3), 1367-1378. doi:10.1016/j.eswa.2007.08.041Liu, J., Liao, X., Zhao, W., & Yang, N. (2016). A classification approach based on the outranking model for multiple criteria ABC analysis. Omega, 61, 19-34. doi:10.1016/j.omega.2015.07.004Douissa, M. R., & Jabeur, K. (2016). A New Model for Multi-criteria ABC Inventory Classification: PROAFTN Method. Procedia Computer Science, 96, 550-559. doi:10.1016/j.procs.2016.08.233Lolli, F., Balugani, E., Ishizaka, A., Gamberini, R., Rimini, B., & Regattieri, A. (2018). 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