Responsive Demand Management in Food Industries to Minimise Waste

Start - Finish:

2002-2005

Research Conducted by:

Robert Darlington

Keywords:

Food Industry, System Simulation, Production Scheduling, Supply Chain Management, Waste Minimisation, Sustainable Production

Industrial collaborators:

Aims & Objectives:

To minimise and ideally eliminate the waste generated by overproduction to meet forecasted demand through the development of a novel framework which aims to reduce the make-span and improve the reaction time by:

• Utilising contemporary techniques and tools such as value stream mapping and simulation models

• Generating a two phase production planning approach based on both static and dynamic production scheduling techniques

• Adopting latest advancements offered through e-manufacture for Supply Chain Management

Brief Description

The food and drink companies form a major part of manufacturing industry in the UK, the business requirements of which have changed dramatically over the last 15 years. During this period such industries have faced significant pressures to diversify their product ranges, resulting from increased product flavours, sizes, packaging and the desire of supermarket multiples to have their own brand name products, often with specific recipes. These pressures have introduced new challenges in the form of shorter lead times, smaller batch sizes, frequent changeovers, greater stock turnover rate, and highlighted the ever increasing needs for such companies to be totally responsive to their customer demands.

Demand for food products varies across the industry. Some foods have a fairly steady, easily predictable demand pattern, meaning that the consumer demand for the product can be met accurately, without wasteful overproduction, or disappointing consumers by not meeting their needs. Other products, for example prepared sandwiches, display highly volatile demand, for which there may be considerable wastage when demand is over-predicted or consumer dissatisfaction when stock-outs occur. Retailers may attempt to smooth large fluctuations by managing the demand, for example by running various promotional activities to maintain demand for products at a steadier level. The demand management efforts for products are merely an attempt to compensate for the external driving conditions such as weather conditions, holiday seasons and sporting events which contribute to the demand in highly volatile sectors.
 

The food and drink companies form a major part of manufacturing industry in the UK, the business requirements of which have changed dramatically over the last 15 years. During this period such industries have faced significant pressures to diversify their product ranges, resulting from increased product flavours, sizes, packaging and the desire of supermarket multiples to have their own brand name products, often with specific recipes. These pressures have introduced new challenges in the form of shorter lead times, smaller batch sizes, frequent changeovers, greater stock turnover rate, and highlighted the ever increasing needs for such companies to be totally responsive to their customer demands.

Traditionally operational planning within the food and drink industry has been based on a predictive make-to-stock approach, which utilised a number of forecasts for various product demands as a basis for production levels. However in recent years there has been greater pressure to adopt a more reactive make-to-order approach, similar to that adopted by the discrete parts manufacturing companies in the engineering sector. The implementation of such reactive customer order driven systems has proved to be more feasible in the engineering sector as typically the make span of products is less than the overall required lead time. However in the food and drink applications there is greater complexity where the make span of products often represents a significantly longer time period than the lead time required by the customer. This means that the production processes must be started before the exact levels of customer demands are known. In addition, further complexities are caused by a volatile pattern of customer orders due to seasonal promotions/marketing activities, high speed and high volume production, and a limited shelf life of raw material and finished goods.

This research is investigating the generation of novel solutions for the reduction of makespans and the improvement of reaction times through the utilisation of recent advancements in the areas of simulation, real time production scheduling, e-supply chain and Supply Chain Management.