دانلود رایگان مقاله بهینه سازی قراردادهای تعمیر و نگهداری با مکانیزم تئوری طراحی

abstract

This paper presents a novel approach for designing and optimizing maintenance service contracts through the application of mechanism design theory. When offering a contract to its customer, the maintenance service provider seeks to specify contract terms – such as price, service features and incentives – that maximize the provider’s profit, satisfy customer needs, allocate risks effectively and mitigate moral hazards. Optimal contract design has to account for asymmetric information and uncertainties associated with customer characteristics and behaviors. We illustrate our mechanism design approach by applying it to the contract design challenge of a gas turbine manufacturer, which also provides maintenance services for its aircraft engines. In our solution approach, we compute an optimal set of contracts. The entire set is presented to the customer and is designed such that the customer will accept one of the contract alternatives without negotiations. In addition to eliminating the costs and delays associated with negotiations, this approach also reveals the customer’s private information to the service provider, which the provider can use to its benefit in maintenance management and future contract renewals. Furthermore, we design and incorporate win–win incentive mechanisms into the contracts, which reward the customer for actions that reduce maintenance costs. We present a deterministic and a stochastic mechanism design model, the latter accounting for uncertainties associated with customer actions, engine performance, and maintenance costs during the contract execution phase.

6. Conclusion

We applied mechanism design theory to the problem of designing service maintenance contracts. In particular, we discussed maintenance service contracts in the gas turbine industry and provided real word based examples. We formulated the maintenance service contract problem as a two-stage sequential optimization problem using mechanism design principles, and presented a modeling and solution approach for a deterministic and a stochastic case. We first analyzed the deterministic case, where customer actions and future outcomes are predictable, followed by a stochastic extension, which accounted for uncertainties in these variables. In both cases, an optimal contract set is computed, which is offered in its entirety to the customer. We provided a numerical example for the deterministic and the stochastic case that illustrated our modeling and solution approach. The mathematical formulation and resulting solutions satisfy the key concepts of mechanism design theory, which are the revelation principle, incentive compatibility and implementability. Offering a specifically designed menu of contract alternatives ensures that in choosing its most preferred contract, the customer reveals its private information (revelation principle). This information can be used by the contract provider to better plan for and manage maintenance efforts. The information can also be used in future contract negotiations and helps to mitigate the adverse selection problem. The contracts include incentives that align the interests of contract provider and customer and thereby minimizes the problems associated with moral hazards (incentive compatibility). As the analysis of the stochastic model showed, these incentives mitigate, but do not fully eliminate (as in the deterministic case), the moral hazard problem. The actions by the customer are in response to future outcomes, which are uncertain at the time of contracting. Similarly, compliant actions by the customer merely increase, but do not guarantee, the chance of receiving an incentive. Maintenance events and cost, which are the basis for determining the incentives, are favorably influenced by compliant customer actions, but a degree of uncertainty remains. Still, incentive compatible contracts create win–wins for customer and contract provider, i.e., the expected profit increase for the contracts provider and the expected cost savings for the customer are positive. Lastly, the optimal contract set meets the provider’s objective of profit maximization and ensures that negotiations can be avoided (implementability). The objective function of the optimization problem maximizes the expected profit over the various possible agent characteristics (types). In the constraints, a minimum reservation value condition for the customer ensures that at least one contract in the contract set is acceptable.