Integration and coordination in after-sales service logistics

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 and revenues associated with capital-intensive assets in technically advanced business environments. Different maintenance services such as inspections and preventive maintenance activities are executed with the goal to maximize the availability of these expensive assets. However, unavoidable failures may still happen, which means that, in addition to preventive maintenance and services, repair actions (corrective maintenance) are necessary. Spare parts, service engineers and tools are typically the main resources for executing the repair actions and their availability has a major impact on overall system downtime. In this dissertation, we analyze a multi-resource after-sales service supply chain consisting of a service provider and an emergency supplier. The service provider is contractually responsible for the timely repair of some randomly failing capital intensive assets. To execute a repair, the service provider needs both service engineers and spare parts to replace the malfunctioning parts. In case of spare parts stock out, the service provider can either wait for the regular replenishment of parts or decide to hand over the entire repair call to an emergency supplier. For the latter case, a contract between the service provider and the emergency supplier is necessary to specify the compensation. In the first part of this dissertation, we focus on the optimal integrated planning of spare parts and engineers, considering an asset availability constraint. We evaluate the system performance using Markov chain analysis and queueing models, and employ different optimization algorithms to jointly determine the optimal capacity of the resources. This integrated planning results in considerable cost savings compared to the separate planning of spare parts and engineers. In the second part, we investigate the best contract the supplier can offer to the service provider. Furthermore, we propose different coordinated contracts to achieve optimal revenues for both partners in this after-sales service supply chain, under both full and asymmetric information scenarios. Cooperative games, the dominance of one party over the other (Stackelberg game), and information sharing aspects are the tools included in the second part of this dissertation

Zijm Consortium: Engineering a Sustainable Supply Chain System

In this paper we address one of the current major research areas of the Zijm consortium; engineering sustainable supply chain systems by transforming traditionally linear practices to circular systems. We illustrate this field of research with a case consisting of a network of three firms Willem (W), Hendrik (H), and Maria (M)} and show how the practice of application-oriented state of the art technology transformed their linear relation to the circular Zijm consortium. The work shows that through inspiration and knowledge transfer in the versatile picturesque Twente Region, a group of future generation researchers are shaped

Multi-resource emergency supply contracts with asymmetric information in the after-sales services

In this paper, we investigate the contract design in a multi-resource service supply chain between a first line service provider and an emergency supplier under information asymmetry. The service provider is contractually responsible for the timely repair of the assets that fail, under a given service level agreement with the asset owner. To execute a repair, the service provider needs both engineers and spare parts to replace malfunctioning parts. In case of a spare parts stock out, the service provider can either wait for the regular replenishment of parts from the central depot or decide to hand over the entire call to an emergency supplier. For the latter case, a contract between the service provider and the supplier is necessary that specifies how the emergency supplier is compensated by the service provider. Particularly, we investigate what is the best contract the supplier can offer when information on asset reliability only resides with the service provider but remains hidden for the emergency supplier (information asymmetry). In the first type of contracts, the supplier charges the service provider a price, specified in a so-called price-only contract, for each time he takes over a call. As an alternative, we study the so-called revenue-sharing contracts in which the supplier receives a fraction of the service provider’s annual revenue and in return agrees to charge a lower price per call. In addition to the standard (single) revenue-sharing contract, we study the implementation of a menu of revenue-sharing contracts. We show that finding a menu of revenue-sharing contracts is not always possible and, if possible, does not necessarily give a higher profit to the supplier than a single revenue-sharing contract. In an extensive numerical experiment, we show that the combination of the single and the menu of revenue-sharing contracts results in, on average, less than 5% loss of the supplier profit under perfect (symmetric) information. Additionally, we find that, while having private information on the assets’ failure rates increases the service provider profit, the increase is insignificant, resulting in an additional profit of only 0.06% on average. Finally, we observe that the supplier can increase his profit, on average, up to 14% if he incites the LSP by means of a side-payment mechanism to share his private information

Joint optimization of spare parts inventory and service engineers staffing with full backlogging

We consider the integrated planning of spare parts and service engineers that are needed for serving a group of systems. These systems are subject to different failure types, and for each failure, a service engineer with the necessary spare part has to be assigned to repair the system. The service provider follows a backlogging policy with part reservations. That is, a repair request is backlogged if one of the required resources is not immediately available upon demand. Moreover, a spare part is reserved if the requested spare part is in stock but no service engineer is immediately available. The spare parts are typically slow-movers and are managed according to a base-stock policy. The objective is to jointly determine the stock levels and the number of service engineers to minimize the total service costs subject to a constraint on the expected total waiting times of the repair calls. For the evaluation of a given setting, we present an exact method (computationally feasible for small problems) and an accurate approximation. For the joint optimization, we present a greedy heuristic that efficiently produces close-to-optimal results. We test how the heuristic performs compared to the optimal solution and the separate optimization of spare parts and service engineers in an extensive numerical study. In a case study with 93 types of spare parts, we show that the solution of the greedy algorithm is always within 2% of the optimal solution and is up to 20% better than a separated optimization approach encountered in practice

Emergency supply contracts for a service provider with limited local resources

We study a problem faced by a service provider, who is responsible for the repair of a group of assets subject to random failures. In case of a failure, both an engineer and a spare part of the right kind need to be available to carry out the repair. A limited number of engineers are employed while also stocks of the various spare parts are limited. In case any resource (engineer or spare part) is not immediately available, the service provider may follow a full backlogging policy. Alternatively, in case of spare parts stock out, he has the option to revert to an emergency supplier with ample capacity of resources. We present an original model to analyze the problem dynamics between this service provider and the emergency supplier. Especially, we determine the optimal emergency shipment cost and the optimal multi-resource level of the service provider. To this end, we propose a computationally efficient algorithm to find the Stackelberg equilibrium. Furthermore, we design revenue and cost-sharing cooperative contracts between these players which always result in coordination. Finally, we examine the risk of uncertainties in these contracts and find the optimal contract parameters by considering the utility functions of the players