A case study of line balancing using largest candidate rule algorithm in a manufacturing industry

Assembly lines are the most important components of mass production systems. The unequal workload among workstations of assembly line increases work in progress (WIP) inventory and waiting time of manpower and machines. The prime objective of any line balancing technique is to distribute tasks evenly over the workstations to minimize the idle time and bottlenecks. This paper focuses on line balancing of a manufacturing industry assembling Pix Cassette Panels using Largest Candidate Rule (LCR). At the beginning of the study line efficiency, balance delays and cycle time of the existing assembly line were found as 48.96 %, 51.04 %, and 120 minutes respectively. The line remained idle for more than 50 % of total time mainly because of inappropriate assignment of tasks on workstations across the assembly line. It was also noted that the assembly line was running for an average of 90 hours as overtime in a month to fulfill the required demand. However, the average number of panels assembled in a month was only 74 against 100 monthly average demand. The line efficiency increased by applying LCR method from 48.96 % to 97.3 %. The cycle time and number of workstations have been rationalized. LCR method improved the overall capability of the line dramatically. The designed line has the capability to assemble 100 panels per month without any overtime with lesser number of labors and machines. Additional to other benefits, the designed assembly line will save around PKR 400,000 as labor and operating costs per month.