Development and evaluation of product delivery strategies for demand-driven production-distribution systems

In many business sectors, fast customer order deliveries are crucial both for the businesses’ and the customers’ viability. To accomplish this, finished products need to be stocked close to the consumers at the expense of higher inventory holding, obsolescence and operating costs in the distribution centres. All of these issues can risk business profitability. Many have embraced demand-driven production and distribution control as a strategy for reducing finished goods inventory. However, little consideration was given to effectuate this concept wherever postponement leads to long lead times which conflicts with indispensable quick and reliable supply of customer demands. Therefore, the aim of this research was to develop new product delivery strategies for demand-driven production-distribution chains that did not compromise on customer service. An approach was proposed which involved partial shipments and express deliveries as enablers for postponed order fulfilment. This delivery strategy splits large order volumes into smaller batch sizes that are fulfilled from variable customer order decoupling points. This concept considered careful lot sizing and delivery scheduling for obviating a delay or interruption of buyers’ consumption cycles. For this purpose, this research developed a generic and adaptable multi-agent simulation-optimisation methodology that used object-oriented programming to calculate feasible batch sizes for each customer order depending on the current supply capacities. The method simulates the corresponding production and logistics processes within realistic multi- level, multi-echelon multi-product systems and was able to capture the details associated with the consequential complexity. This allowed for an in-depth exploration of the resulting key performances. By using a heuristic solver engine, which iteratively simulated various strategy parameters, such as economic batch sizes and delivery speeds, the most suitable delivery splitting and postponement policies for each supplied product were found. The result was an optimal trade-off between supply chain cost factors which achieved minimal cost for vendors and buyers. The utility of the methodology was demonstrated on two industry cases; a pharmaceutical company and a conglomerate company. For each example an optimal partial delivery-enabled postponement policy was determined that had the potential to improve the companies’ profitability through the more efficient use of their inventories