Optimal supplier development contract extensions despite flexibility requirements of industry 4.0

Original Equipment Manufacturers (OEM) face procurement costs of raw materials and com ponents of more than half of the manufacturers’ total profit. Therefore, OEMs depend on their suppliers, and the supplier’s performance has a noticeable effect on many product as pects, such as cost, quality, and on-time delivery. Consequently, OEMs place increasing concentration on a more efficient supply chain utilizing supplier development. Like other types of investments, investment in supplier development contains the risk whether it pays off the proposed revenue or not. Therefore OEMs need to be aware of the profitability of their supplier development investments in advance. Regarding this topic, many researchers conducted quantitive and qualitative supplier development studies. They tried to address different aspects of this concept, like supplier development outcomes, applications, or its importance. They provided in-depth knowledge of suppler development investment in both theory and practice. The presented studies considered supplier development in a static mar ket situation. Additionally, they did not offer any suggestions toward the profitability of
supplier development regarding the period of investment in a dynamic market.
In this thesis, we take some steps forward from the previous studies. We study multi OEM scenarios consisting of two OEMs and one supplier (a so-called multi-OEM scenario in this study) that enable us to consider the relationship between OEMs who tend to invest in the same supplier. Studying a multi-OEM scenario enables us to simulate more realistic settings. In this regard, by applying game theory, we assume four types of relationships be tween OEMs that are fully cooperative, collaborative (simultaneous and sequential decision making), and non-cooperative. Moreover, in a multi-OEM scenario, we consider the effect of trust between OEMs. We implement Model Predictive Control (MPC) to evaluate the profit of OEMs investment over time. MPC is a well-established method for dynamic sys tems and recently received great attention in supply chain management. MPC implements a series of control aspects to provide decision-makers an optimal option over a moving horizon to minimize the deviations from the proposed goals. Using MPC, we take the dynamics of
the market into account. We considred two use-cases to gain real-world data to investigate supplier development investment for OEMs in dynamic and static market situations. We se lected the Samsung smartphone S-series as a short life cycle product and the Mercedes Benz A-class as a middle life cycle product. We obtained the data of these two use-cases from the database of Germany’s Federal Office for Statistics.
The results of this study reveal that supplier development is considerably profitable in
total. Furthermore, the results show that supplier development is an efficient tool to reduce OEM’s product price by mitigating the production cost, ending with customer satisfaction. Even a small investment in suppliers causes profit compared to the scenario where no sup plier development is implemented. Higher investments still result in an increased profit. Moreover, our experiment on OEMs’ different relationships shows that OEMs tend to invest for more extended periods rather than the other scenarios in a fully cooperative scenario. Also, in a full cooperative scenario, the OEMs gain the advantage of faster and higher pro duction cost reduction. The non-cooperative scenario results indicate that OEMs look after shorter investment periods while the investment is not paying off. Thus, OEMs should cut off the investment in the development of the supplier in shorter periods. Furthermore, our study considering dynamic market conditions shows that supplier development results in higher or at least close-to-equal profits for most of the proposed scenarios. Overall, the results show that considering the market dynamics depends on the planned period of the overall supplier development program. For short programs, the static assumptions cause better revenues since the optimizer issues investments quickly at the beginning of the project. Finally, the results reveal that the OEMs’ orientation to either make the trust or focus on optimizing their
favorable revenue influences the overall outcome. Assuming a balanced trust level leads to the highest level of revenue, both for the individual OEMs and overall for involved parties.