Qualitative analysis about best practices and project management tools in intralogistics
DOI:
https://doi.org/10.5377/nrc.v37i01.18330Keywords:
Project Management, Risk Management, Earned Value, SimulationAbstract
Project management in automotive manufacturing is crucial due to the dynamism in updating operating models and high investment in the supply chain and logistics. This article presents a systematic literature review of 134 articles (2011-2023) from four relevant databases (IEEE, ScienceDirect, Scopus, Taylor & Francis) with the purpose of exploring the best practices in project management applied in intralogistics activities. Analyzing aspects such as country, management methods and techniques, solution levels in internal logistics projects, business line, among other items. The findings will identify opportunities that contribute to academic indicators and the generation of proposals in the automotive industry in Mexico, focused on the fulfillment of projects and management according to their context.
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References
A. Fink. (2005). Conducting research literature reviews: from the Internet to paper. 2nd Ed. Thousand Oaks, Calif.: Sage Publications.
Ahmad, R., Masse, C., Jituri, S., Doucette, J., & Mertiny, P. (2018). Alberta Learning Factory for training reconfigurable assembly process value stream mapping. Procedia Manufacturing, 23, 237–242.
Alvanchi, A., Baniassadi, F., Shahsavari, M., & Kashani, H. (2021). Improving materials logistics plan in road construction projects using discrete event simulation. Engineering, Construction and Architectural Management, 28(10), 3144–3163.
Ashraf, M., & Ali, I. (2023). Evaluation of project completion time prediction accuracy in a disrupted blockchain-enabled project-based supply chain. International Journal of Systems Science: Operations & Logistics, 10(1).
Buenrostro, A. M. (2021). COVID-19: el gran desafío para la logística en la industria. In Ciencia Amateur.
Chance, G., Ghobrial, A., McAreavey, K., Lemaignan, S., Pipe, T., & Eder, K. (2022). On Determinism of Game Engines Used for Simulation-Based Autonomous Vehicle Verification. IEEE Transactions on Intelligent Transportation Systems, 23(11), 20538–20552.
Clarivate. (2023). The Emerging Sources Citation Index (ESCI).
da Silva, N. A., Abreu, J. L., Orsolin Klingenberg, C., Antunes Junior, J. A. V., & Lacerda, D. P. (2022). Industry 4.0 and micro and small enterprises: systematic literature review and analysis. Production & Manufacturing Research, 10(1), 696–726.
Dao, B., Kermanshachi, S., Shane, J., Anderson, S., & Damnjanovic, I. (2022). Developing a logistic regression model to measure project complexity. Architectural Engineering and Design Management, 18(3), 226–240.
Deniyage, C. J., & Palliyaguru, R. (2019). Conceptual framework for effective implementation of ‘project management institute’s standard for earned value management’ in Sri Lanka. Proceedings of the 8th World Construction Symposium, 189–199.
Despeisse, M., Chari, A., González Chávez, C. A., Monteiro, H., Machado, C. G., & Johansson, B. (2022). A systematic review of empirical studies on green manufacturing: eight propositions and a research framework for digitalized sustainable manufacturing. Production & Manufacturing Research, 10(1), 727–759.
ELSEVIER. (2023). Scopus Sources. Scopus: Comprehensive, multidisciplinary, trusted abstract and citation database
Goh, C. S., Su, F., & Rowlinson, S. (2023). Exploring Economic Impacts of Sustainable Construction Projects on Stakeholders: The Role of Integrated Project Delivery. Journal of Legal Affairs and Dispute Resolution in Engineering and Construction, 15(3).
Gurmu, A. T., & Ongkowijoyo, C. S. (2020). Predicting Construction Labor Productivity Based on Implementation Levels of Human Resource Management Practices. Journal of Construction Engineering and Management, 146(3).
Harnegie, M. P. (2013). SciVerse Science Direct. Journal of the Medical Library Association: JMLA, 101(2), 165–165.
Quitian-Tellez, H. A. (2018). Grado de Madurez en la Gestión de Proyectos de la Empresa de Logística Open Market de Bogotá D.C. Universidad Piloto de Colombia Especialización en Gerencia de Proyectos.
Ithaka. (2023). Taylor & Francis, Ltd. JSTOR.
Jairo R. Montoya-Torres, & Diego A. Ortiz-Vargas. (2013). Collaboration and information sharing in dyadic supply chains: A literature review over the period 2000–2012. Estud. Gerenciales, 30, 343–354.
Kumar, P., Haleem, A., Qamar, F., & Khan, U. (2018). Analysis of maiden modal shift in coal transportation supply chain using SAP-LAP technique. International Journal of Logistics Systems and Management, 30(4), 458.
Küpper, C., Rösch, J., & Winkler, H. (2022). Use of real time localization systems (RTLS) in the automotive production and the prospects of 5G – A literature review. Production & Manufacturing Research, 10(1), 840–874.
Lecanda Meschede, I., Colmenar Santos, M. P., Parrado Prieto, J. Á., & Pérez Goyanes, C. (2023). IEEE Xplore: Presentación. Biblioteca de La Universidad de Valladolid /Biblioguías.
Li, J., Gu, X., Zhang, Y., & Zhou, X. (2022). Distributed Flexible Job-Shop Scheduling Problem Based on Hybrid Chemical Reaction Optimization Algorithm. Complex System Modeling and Simulation, 2(2), 156–173.
López-Joy, T., Gómez-Acosta, M. I., Neira-Mugercia, A. N., Acevedo-Suárez, J. A., Peña-García, C., & Acevedo-Urquiaga, A. J. (2020). Medicines Value Chain Management Level in Cuban Health System. Ingenieria y Universidad, 24(1).
M. M. Crossan, & M. Apaydin. (2010). A Multi-Dimensional Framework of Organizational Innovation: A Systematic Review of the Literature. J. Manag. Stud. No. 6, 47, 1154–1191.
Qiao, Y., Labi, S., & Fricker, J. D. (2021). Does highway project bundling policy affect bidding competition? Insights from a mixed ordinal logistic model. Transportation Research Part A: Policy and Practice, 145, 228–242.
Santos, J. I., Pereda, M., Ahedo, V., & Galán, J. M. (2023). Explainable machine learning for project management control. Computers & Industrial Engineering, 180, 109261.
Somasundaram R. (2023, October 15). Scopus vs Web of Science: Which is Better? ILovePhD.
Sony, M. (2020). Pros and cons of implementing Industry 4.0 for the organizations: a review and synthesis of evidence. Production & Manufacturing Research, 8 (1), 244–272.
Sony, M., & Mekoth, N. (2022). Employee adaptability skills for Industry 4.0 success: a road map. Production & Manufacturing Research, 10(1), 24–41. https://doi.org/10.1080/21693277.2022.2035281
Suguna, M., Shah, B., Raj, S. K., & Suresh, M. (2022). A study on the influential factors of the last mile delivery projects during Covid-19 era. Operations Management Research, 15(1–2), 399–412.
Sun, W. (2014). Logistics Cost Optimization in Total Life Cycle of Power Grid Engineering Project Using Improved Ant Colony Algorithm. Journal of Information and Computational Science, 11(5), 1411–1418.
Taye, G. D., & Feleke, Y. A. (2022). Prediction of failures in the project management knowledge areas using a machine learning approach for software companies. Applied Sciences, 4(6), 165.
Thunberg, M., & Fredriksson, A. (2023). A model for visualizing cost shifts when introducing construction logistics setups. Construction Innovation, 23(4), 757–774.
Trab, S., Bajic, E., Zouinkhi, A., Thomas, A., Abdelkrim, M. N., Chekir, H., & Ltaief, R. H. (2017). A communicating object’s approach for smart logistics and safety issues in warehouses. Concurrent Engineering, 25(1), 53–67.
Varela, L., Putnik, G., & Romero, F. (2022). The concept of collaborative engineering: a systematic literature review. Production & Manufacturing Research, 10(1), 784–839.
Ying, F. J., O’Sullivan, M., & Adan, I. (2021). Simulation of vehicle movements for planning construction logistics centers. Construction Innovation, 21(4), 608–624.
Zhao, F., Di, S., Cao, J., Tang, J., & Jonrinaldi. (2021). A Novel Cooperative Multi-Stage Hyper-Heuristic for Combination Optimization Problems. Complex System Modeling and Simulation, 1(2), 91–108.
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