Redesigning of Industrial Warehouse Layout Using CADD
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Abstract
They take a look at changes in seeking out the most appropriate application of warehouse layout patterns using an extended AutoCAD simulation model. preliminary data changed into won based totally on the financial and overall performance of foremost heavy components providers. both primary and secondary data assets have been processed and analyzed at some point which calculated the ratio of the proportion of location for each type of product class based on sales productiveness and the percentage effects can be applied with CADD simulation (pc Aided layout and Drafting) by using the use of software program software AutoCAD and SketchUp to make clear in viewing pix in three-dimensional form. After the reapply layout is implemented in the utility, the organization can use shade codes and numeric / letter codes to make it smooth in grouping classes of goods. The outcomes indicate that properly-prepared and technology-based warehouse operations brought full-size and giant growth to both efficiency and sales in a selected post-pandemic.
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Annas, M., & Humairoh, H. (2022). Redesigning of Industrial Warehouse Layout Using CADD. Dinasti International Journal of Management Science, 4(1), 57-69. https://doi.org/10.31933/dijms.v4i1.1403
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References
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Al-Hyari, K. A., Abu Zaid, M. K., Arabeyyat, O. S., Al-Qwasmeh, L., & Haffar, M. (2019). The applications of Kaizen methods in project settings: applied study in Jordan. The TQM Journal, 31(5), 831–849. https://doi.org/10.1108/TQM-03-2019-0078
Altinisik, A., & Yildirim, U. (2020). Failure prediction in electrical connector assembly: a case in the automotive assembly process. Assembly Automation, 40(6), 881–893. https://doi.org/10.1108/AA-06-2020-0077
Bhat, S., Gijo, E. V, Rego, A. M., & Bhat, V. S. (2021). Lean Six Sigma competitiveness for micro, small and medium enterprises (MSME): action research in the Indian context. The TQM Journal, 33(2), 379–406. https://doi.org/10.1108/TQM-04-2020-0079
Bhatnagar, A., Vrat, P., & Shankar, R. (2019). Multi-criteria clustering analytics for agro-based perishables in cold-chain. Journal of Advances in Management Research, 16(4), 563–593. https://doi.org/10.1108/JAMR-10-2018-0093
Buddas, H. (2014). A bottleneck analysis in the IFRC supply chain. Journal of Humanitarian Logistics and Supply Chain Management, 4(2), 222–244. https://doi.org/10.1108/JHLSCM-10-2013-0036
Chugani, N., Kumar, V., Garza-Reyes, J. A., Rocha-Lona, L., & Upadhyay, A. (2017). Investigating the green impact of Lean, Six Sigma, and Lean Six Sigma. International Journal of Lean Six Sigma, 8(1), 7–32. https://doi.org/10.1108/IJLSS-11-2015-0043
Durmusoglu, Z. D. U. (2018). A TOPSIS-based approach for sustainable layout design: activity relation chart evaluation. Kybernetes, 47(10), 2012–2024. https://doi.org/10.1108/K-02-2018-0056
Fern, J. T., & Almeria, U. De. (2022). Dependence and resource commitment as antecedents of supply chain integration. 28(8), 23–47. https://doi.org/10.1108/BPMJ-09-2021-0602
Forslund, H., Björklund, M., & Ülgen, V. S. (2022). Challenges in extending sustainability across a transport supply chain. 7(February 2021), 1–16. https://doi.org/10.1108/SCM-06-2020-0285
Hemalattha, S., & Vidjeapriya, R. (2021). Developing an integrated framework for optimization of spatial requirements of construction equipment. Built Environment Project and Asset Management, 11(5), 903–917. https://doi.org/10.1108/BEPAM-07-2020-0126
Jansson, C. (2022). Can green producers achieve strong profitability without engaging in high-risk activities ? 60(13), 92–104. https://doi.org/10.1108/MD-08-2021-1090
Kauppi, K., & Luzzini, D. (2022). Measuring institutional pressures in a supply chain context : scale development and testing. 7, 79–107. https://doi.org/10.1108/SCM-04-2021-0169
Lee, S. M., & Ebrahimpour, M. (1984). Just‐In‐Time Production System: Some Requirements for Implementation. International Journal of Operations & Production Management, 4(4), 3–15. https://doi.org/10.1108/eb054721
Mitra Debnath, R. (2019). Enhancing customer satisfaction using Kaizen: a case study of Imperial Tobacco Company (ITC). Journal of Advances in Management Research, 16(3), 277–293. https://doi.org/10.1108/JAMR-01-2018-0009
Muganyi, P., Madanhire, I., & Mbohwa, C. (2019). Business survival and market performance through Lean Six Sigma in the chemical manufacturing industry. International Journal of Lean Six Sigma, 10(2), 566–600. https://doi.org/10.1108/IJLSS-06-2017-0064
Naeemah, A. J., & Wong, K. Y. (2021). Selection methods of lean management tools: a review. International Journal of Productivity and Performance Management, ahead-of-print(ahead-of-print). https://doi.org/10.1108/IJPPM-04-2021-0198
Narula, S., Puppala, H., Kumar, A., Luthra, S., Dwivedy, M., Prakash, S., & Talwar, V. (2022). Are Industry 4.0 technologies enablers of lean? Evidence from manufacturing industries. International Journal of Lean Six Sigma, ahead-of-print(ahead-of-print). https://doi.org/10.1108/IJLSS-04-2021-0085
Patel, A. S., & Patel, K. M. (2021). A critical review of literature on Lean Six Sigma methodology. International Journal of Lean Six Sigma, 12(3), 627–674. https://doi.org/10.1108/IJLSS-04-2020-0043
Purushothaman, M. B., Seadon, J., & Moore, D. (2022). A relationship between bias, lean tools, and waste. International Journal of Lean Six Sigma, 13(4), 897–936. https://doi.org/10.1108/IJLSS-03-2021-0045
Raval, S. J., Kant, R., & Shankar, R. (2018). Revealing research trends and themes in Lean Six Sigma: from 2000 to 2016. International Journal of Lean Six Sigma, 9(3), 399–443. https://doi.org/10.1108/IJLSS-03-2017-0021
Vamsi Krishna Jasti, N., & Kodali, R. (2014). A literature review of empirical research methodology in lean manufacturing. International Journal of Operations & Production Management, 34(8), 1080–1122. https://doi.org/10.1108/IJOPM-04-2012-0169