Lean manufacturing implementation using value stream mapping at excavator manufacturing company

The shop floor of each industry has several stations, working interdependent to carried out specified tasks, as per the schedule define to meet the production rate. The breakdown of machine, shortage of inventory, unavailability of tools causes delay to meet the demand. The excess inventory at workstation catches rust requires regrinding, fatigue to operator due to unnecessary movement, improper design of pallet, incorrect location of clamps are some of example consumes time at workstation and slower production rate. The fabrication line of global boom has considered for improvement and to increase production rate to satisfy the customer demand. This fabrication line is able to produce 12 global booms per day. This rate of production is inadequate to satisfy actual customer demand of 15 global booms per day. The efficiency of fabrication line has proposed to increases to meet actual demand. Value stream mapping is the only lean tool suggested in literatures, to eliminate Muda, bottlenecks across production line. The value stream mapping uses current state map to record current state of production line before implementation of techniques. The current state map plotted for globe boom fabrication line has identified several problems. The higher setup at welding station of center section due to improper clamping of center section, excess inventory at foot boss a center boss tacking station catches rust and requires regrinds, underutilized press station due to no provision of fixture are some of the problems identified across fabrication line. The lean implementation, kaizen are employed to solve above problems and future state map recorded. The lean implementation eliminates excessive inventory, reduces total cycle time and total setup time at various station. The future state map shows reduction of 156 min from value added activities which synchronously reduces 430 min of non-value added activities. This contributes reduction of 586 min from production lead time. (C) 2019 Elsevier Ltd. All rights reserved.