Integration and Coordination in After-sales Service Logistics
Sajjad Rahimi-Ghahroodi is a PhD student in the Department Industrial Engineering and Business Information Systems (IEBIS). His supervisor is prof.dr. W.H.M. Zijm from the Faculty of Behavioural, Management and Social sciences (BMS).
Maintenance and after-sales service logistics are important disciplines that have received considerable attention both in practice and in the scientific literature. This attention is related to the often high investments associated with capital-intensive assets in technically advanced business environments. The uninterrupted availability of these assets is generally crucial for a company's operations. An operational failure resulting in downtime is highly undesirable and may lead to significant losses for the asset owner. Moreover, after-sales and maintenance services constitute a significant part of the income of many Original Equipment Manufacturers (OEMs); it is not uncommon that service-related revenues even exceed those of the sales of original products and equipment.
Different maintenance services such as inspections and preventive maintenance activities are executed with the goal to maximize the availability of these expensive systems. However, unavoidable failures may still happen, which means that, in addition to preventive maintenance and services, repair actions (corrective maintenance) are necessary. Because of the focus on the up-time of systems, often a “repair-by-replacement” policy is adopted, i.e. upon detection of what parts are malfunctioning, these parts are removed and replaced by ready-to-use spare parts. In this case, spare parts, service engineers and tools are the main resources for executing the repair actions and their availability has a major impact on overall system downtime.
In the first part of this dissertation, we consider a single local service provider (LSP) maintaining a group of assets based on a service level agreement with the customer (asset owner). These assets are subject to random failures and the service provider is responsible for carrying out the repair of the failing assets. This corrective maintenance is executed by replacement of the failed part with a ready-to-use spare part. Since failures and hence the demand for repairs are not known in advance, and the replenishment of the spare parts through an external channel usually takes a long time, the service provider needs to stock a sufficient number of spare parts to meet the target service level. He also needs to have a team of specialist service engineers available to replace the malfunctioning parts.
In the models developed and analyzed in the first part, the LSP may follow one of two service policy options. He can fully rely on himself in providing the resources and satisfying the repair calls by following a “full backlogging policy”. In this policy, spare parts are stocked in sufficient quantities and engineers are employed, while in the case the requested spare parts or a service engineer is not immediately available, the repair call is backlogged until both resources become available again. As an alternative, the service provider may keep less local resources and in case of a spare parts stock out, revert to an emergency supplier with ample capacity of spare parts and service engineers to respond to a repair call. However, when upon a request the appropriate part is in stock but no service engineer is immediately available, a backlogging policy is followed. This policy is called the “partial backlogging policy”. In both problems, the service level is formulated as the maximum accepted average waiting time, measured over all repair calls. Waiting times are caused by either the queueing for service engineers or the lead time needed for a regular spare part replenishment (full backlogging) or an emergency shipment (partial backlogging).
In the second part of this dissertation, we broaden our scope and consider a two-echelon after-sales service model with a local service provider (LSP) and an emergency supplier. We assume that the LSP and the supplier are independent and that they are interested in maximizing their individual profit and determine their decision variables accordingly. An important question then concerns the type of contract made between the LSP and the emergency supplier. In particular, we study Stackelberg and cooperative games between the local service provider and the emergency supplier.
We consider a price-only Stackelberg game model in which no negotiation or cooperation between the players takes place. In this contract, the emergency supplier is the principal and she first decides on the contract terms. It is known that, if the supplier charges a too high price in case of an emergency shipment, the LSP declines the supplier's offer and will use the full backlogging policy instead. Therefore, the emergency supplier needs to carefully evaluate the position of the LSP before offering a contract. It is shown that the LSP can propose both revenue-sharing and cost-sharing contracts to the supplier as a cooperation tool, leading to better contracts in a win-win situation.
Furthermore, we study the same problem, but in a more practical scenario, namely, the case of asymmetric information on the asset's reliability. We assume that both players have full information on each other's cost factors, however, the supplier does not have full information on the failure rate of the assets. In this case, we investigate different contracts and mechanism, e.g. a menu of revenue-sharing contracts, which the supplier can use to tackle the lack of perfect information.