Ota, O. U. and Obiukwu, O. O. and Okafor, B. E. and Ekpechi, D. A. (2023) Lean Optimization of Batch Production in an Aluminium Company. Asian Journal of Current Research, 8 (4). pp. 62-81. ISSN 2456-804X
Full text not available from this repository.Abstract
This work investigates the optimization of a batch type of production and operational management in an aluminium company using a lean manufacturing system. The operation and production system of the case study company runs in various sectors, which led to waste in the system, hindering the company's ability to meet customer demand. Through operational data analysis and questionnaires, the team identified the types of waste generated by the case study company. Lean manufacturing techniques such as eight deadly wastes, Heijunka, takt time, 5S approach, quality tool management, value stream mapping, Kaizen, Kaban, Gemba, and top and bottom-level involvement were employed to manage the waste. The findings reveal defects in inventory, transportation, waiting times, and untapped ideas of employees, all of which significantly impact the company's performance. This allows for daily production of small batches of aluminium alloys (AA3001, AA3105, and AA3110) without issues, supported by the principle of pull production. Additionally, the application of Takt time results in a significant reduction of production time, leading to improved efficiency. The study also highlights the high interaction effect of transportation, defects, and inventory wastes on various production lines, such as the bogie fitting line paint line, and anti-intrusion. Among the lean manufacturing tools, Kaban, standard work, and 5S are identified as the most frequently used. The research findings provide valuable insights for manufacturing industry leaders to spot the performance gaps and enhance the application of lean manufacturing practices.
Item Type: | Article |
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Subjects: | Eurolib Press > Multidisciplinary |
Depositing User: | Managing Editor |
Date Deposited: | 27 Nov 2023 08:13 |
Last Modified: | 27 Nov 2023 08:13 |
URI: | http://info.submit4journal.com/id/eprint/3163 |