Abstract:
The development of the industrial age has seen a remarkable growth which has led to
competition not of products but of the supply chains. A related problem such
organisations face is the difficulty in identifying the most appropriate way of managing
the operation in a cost effective and efficient for the organisation as a whole. The better
way to solve such kinds of problems, is the use of Operations Research (OR) techniques.
The purpose of this project is to use statistical techniques to solve operational problems
and further optimise the model. Here an operational environment is used to apply this
learning with the intension of gaining benefits in terms of cost savings and service
improvement. \
Here two operating models (model A and model B) were studied in detail study, its pros
and cons as well as problems that may arise were identified. Since the model needed to
be cost effective, the main cost elements were identified and their impacts were
quantified base on the past information and finally forecast figures were estimated.
Based on all the key parameters, the final impacts ofthe models were derived along with
the optimum inventory model and the feasibility ofthe model is also evaluated.
Finally, the outcomes were evaluated for all the cost elements using the actual data of
the two models and the best model has been concluded to be Model B since it is cost
effective by 6.5% and also service oriented. At this point, deviations of cost due to
inefficiencies in the operation were also identified where the main cause is due to poor
inventory management. Therefore, could conclude that proper inventory management is
essential in order to optimise model B and for it to be feasible.
The inefficiencies were proposed to be solved as future projects. The difficulties faced
during the study and limitations are also been discussed.
provided such as identifying a better location to relocate
an optimum distribution network
Finally, recommendations
the Regional DC (Distribution Centre) and to develop
are
to reduce the distribution cost
