Bottleneck identification in a tyre manufacturing plant using simulation analysis and productivity improvement. (2018)

• Record Type: Journal Article
• Authors: Krishnan, Srijit; Dev, A. Sarang; Suresh, Rahul; Sumesh, A.; Rameshkumar, K.
• Is Part Of: Materials today. Volume 5:Number 11(2018)Part 3
• Page Start: 24720
• Page End: 24730
• Publication Date: 2018
• Subjects: Manufacturing system Simulation, Discrete Event Simulation -- Cycle Time Reduction -- Bottleneck Analysis -- Throughput Analysis -- Pareto Analysis -- Cause-Effect Diagram; Materials science -- Congresses -- Periodicals; 620.1
• DOI: 10.1016/j.matpr.2018.10.270
• Languages: English
• ISSNs: 2214-7853

Abstract

Abstract: It is vital to improve productivity with cutting edge technology for any manufacturing or service industry. Quality with quantity helps a company to stay in competition. Technology has developed greatly to meet the customers' demand. The elimination of waste with increased productivity leading to hike in profit should be the target of the manufacturing sector. The tyre manufacturing company in which the study was carried out requires reduction in non-value added activities, bottlenecks and processing time to increase productivity. The paper presents the current process simulation undergone in a tyre manufacturing plant. The simulation study found that the actual figures produced in the plant matched the 1170 units per day throughput. The simulation reveals the calendering process as the bottleneck present in the plant. The Pareto analysis used confirms the bottleneck simulation analysis result. Root causes for problems were identified using 5 why analysis and the cause-effect diagram. Solutions were suggested to reduce process times viz the bottleneck experimented, which show an increase in throughput of the tyre manufacturing plant. The bottleneck can be eliminated by modifying the calendering machine to increase productivity by 15.81%. The breakeven time for installation costing 3.5crores will be for 88 days. By going with an automated temperature measuring system, the total productivity can be increased by 18.8% from the existing scenario.