# Supplier Replacement Model in a One-Level Assembly System under Lead-Time Uncertainty
## 7 Discussion  
A key problem with much literature on replenishment policy for assembly systems under uncertainty of lead times is that research has tended to focus on reducing the costs related to uncertainty rather than establishing a suppliers selection strategy in order to negotiate purchase prices and uncertainty costs. All previous research concentrates on ordering policies by optimizing order quantities [3; 34; 35; 36; 39; 40; 41; 42], order release dates and planned lead times [14; 15; 16; 17; 18; 22; 23].  
This study is the first investigation that aimed at highlighting the usefulness of considering supplier selection/replacement strategies to negotiate purchase prices and delivery delays for OLAS and multi-period replenishment planning. It provides the basis for a new way to consider not only the probability distributions of lead-times of suppliers but also their prices, Thus, the present findings might help to optimize not only replenishment policy, but also purchasing policy. For a given unit, it is now possible to model several alternative suppliers with alternative pricing and lead-time uncertainties, and evaluate their impacts on the total cost. The proposed model has the potential to be applied to ATO environments [19; 20; 22] and to CTO environments [23], for example, if components and semi-finished products are bought abroad and shipped from various locations. The proposed approach could possibly enable decision makers to select suppliers and plan the order release dates based on planned lead times and purchasing policies predefined by suppliers.  
In our view, these results constitute an excellent initial step toward including the selection of suppliers in replenishment policy. Please note that with Industry 4.0 technologies the selection of suppliers and negotiation of conditions will move from the strategic and offline approach to real time online negotiations. Thus, the importance of such models will increase.  
Despite our research showing the importance of optimizing purchasing policies, we are aware that it may have several limitations. The first is that the model is only valid when the demand is known and constant. This hypothesis is considered because, at the moment, it is difficult to express the dependence between periods and levels when the demand is completely dynamic. Research into solving this problem is already in progress. Second, the mathematical formulation needs to be extended in order to study complex structures such as BOMs with several levels. Our future work will concentrate on this limitation. Techniques, that are developed in [22; 57; 58] in order to model multi-level structures and in [59] in the field of project planning, will be investigated. Third, the current study has only examined the uncertainty of lead times. Consequently, we neglected other types of uncertainty such as demand and quality. Further work needs to be carried out to investigate more than one source of uncertainty. The development of more complex models with several stochastic parameters to study more complex structures will be an on-going challenge for future years.