Short shelf life food manufacturers very often face capacity problems at the end of the production line. The area designated to perform the cold store function is often a legacy from the past, and has to cope with bulk product, order picking and load marshalling in a very confined, dynamic, rapidly changing, make to order environment with tight deadlines.
The main historic problem is the number of product lines required to be made daily with all the ensuing product, label and pack format changes leading to excessive stoppage time, which eats into the machine time availability. Long batch production is not possible due to the lack of storage space and the number of products required to be available when order picking in such a confined area.
This age old problem has in some cases been addressed by investment in fewer, modern, highly automated production units with larger ‘fit for purpose’ storage areas.
However a related variant of the old problem has emerged for a different reason.
More vehicles are travelling further to service the customer base, while at the same time the high speed packing lines now employed mean that more finished products are available in the cold store earlier, conversely the vehicles are back later as they have further to travel.
Refrigerated trailers are themselves a scarce resource and are not always available when required to relieve the pressure as they are out making deliveries, and thus the cold storage area is prone to congestion resulting in the worst case scenario – production line stoppages.
The usual way of circumnavigating the problem is the use of ‘stand trailers’ which act as temporary storage, however these are over and above what is actually required to deliver the product, and it is always contentious as to whether they are included in the distribution or factory budgets.
Model Logic has developed a simulation tool which gives a minute by minute measure of product availability and an overview of the activities of production, bulk product out-feed, temporary storage, picking of product lines, marshalling and loading out to vehicles over a full seven day planning horizon.
The resultant usage of floor space, manpower, and handling equipment are all recorded dynamically.
This enables better understanding of the operational dynamics, and allowing ‘off line’ measurement of the impact on product availability and service levels by varying input parameters such as production sequencing, packing line allocation and resource scheduling.
The model has been used for project in the short shelf life food processing industry as well as in the pharmaceutical industry.