Abstract:
The competitive environment in the automotive industry demands low cost as a
strategic advantage. In addition, the Kenyan automotive industry has experienced
steady growth over the last five years thus creating demand that is higher than supply.
Consequently, each vehicle assembler is looking for ways to reduce the cost of
manufacturing and at the same time to increase output in order to match supply with
demand. Therefore, the purpose of this research is to develop a model for improving
productivity of the vehicle assembler in order to provide a cost advantage and increase
output to meet the demand levels.
This thesis seeks to improve productivity by providing an empirical method to evaluate
a production system and determine its capacity and constrains. In order to gain the in
depth information required for modelling, a case study methodology was utilized. Key
steps to achieve the thesis objectives were to develop a simulation model of the case
assembly plant, simulate the model, optimize the model through experimentation and
finally use the simulation results to derive strategies for improving productivity of the
process. Lean manufacturing tools were applied to develop the improvement strategies.
Arena® software was used to develop the simulation because of its ease of learning,
minimal cost of ownership, analysis capabilities and its inbuilt statistical facilities.
A simulation model with complete process analysis was developed and run under
different operating scenarios to identify optimal conditions that yield highest output.
The optimal scenario led to a 110% improvement in productivity in the simulation. The
strategies for improving the process were derived for the case study plant to implement
adopted from lean manufacturing techniques. The contribution of this research to theory
was to provide the link between simulation and lean manufacturing techniques that is
vital for implementing the optimal simulation attributes at the shop floor. The
contribution of this research to the case study plant was enormous in terms of output
and capacity. The case study plant implemented some of the recommendations of this
research and realized a 60% increase in actual daily production average.
