SIMULATION OF A LOADING, UNLOADING AND WAREHOUSING SYSTEM TO REDUCE THE WAITING TIMES: A STUDY ON THE SRI LANKAN APPAREL SECTOR

Abstract

A shift in the direction of sustainability has become the way forward for all industries. Thus a sustainable supply chain management within a manufacturing organization plays a vital role in the organizations’ journey toward sustainability. Loading, unloading and warehousing are critically involved with production and dispatch products. The reduction in cycle times of the processes and minimization of waiting times play vital importance in the manufacturing process. Also, the usage of technological advancements in the enhancement of a system performance has become a corporate routine that has proved to be efficacious in the endeavours. Therefore, the study intended to provide solutions for the bottlenecks existing in the loading, unloading and warehousing system of a leading apparel manufacturer in Sri Lanka using simulations. This system included three loading and unloading bays. First and the second bays were entirely dedicated for the unloading process. The third bay was dedicated for the loading process of the finished products after the eighth hour of a 12 hour working day. The process ran simultaneously allowing hefty waiting times in the unloading process as priority was given for the loading systems. The study observed arrival and service times of each container and its batch. Thus the inter-arrival times were calculated. The observation was conducted for three consecutive weeks. The system was identified to have two possible alternatives in optimizing the efficiency in the processes. They were to add another bay dedicated for the loading process and add more resources such as a forklift to the third bay to quicken the process. Using Rockwell ARENA both alternatives were simulated to obtain the performance statistics including the waiting times and number waiting for service. The waiting times have shown 57.5, 79.6 and 90.2 percent of reductions respectively in bay one, two and three for the latter of the alternatives. Though both processes reduced waiting times of the batches, adding resources for the process is conveniently determined as the optimum of the alternatives based on the reduction in the waiting times and the spatial capacity. The study observed that simulation studies enable the modelling of the reality to avoid futile changes in the systems.