Third-party repair stores are a common option if you drop or break your smartphone, but Apple is reportedly not a fan of these alternative repair options. Apple is one of several high-profile companies that have been lobbying against a New York state bill that would make it easier to independent stores and users to repair devices. According to Motherboard, the Fair Repair Act would have companies sell replacement parts and tools to everyone, bans software locks that would limit repairs and, in some cases, have companies provide repair guides publicly. However, Apple and other companies have come out aggressively against the proposed legislation. Along with Apple, other companies who have lobbied against the Fair Repair Act include Toyota, Caterpillar and Verizon.
Recent work has raised the challenge of efficient automated troubleshooting in domains where repairing a set of components in a single repair action is cheaper than repairing each of them separately. This corresponds to cases where there is a non-negligible overhead to initiating a repair action and to testing the system after a repair action. In this work we propose several algorithms for choosing which batch of components to repair, so as to minimize the overall repair costs. Experimentally, we show the benefit of these algorithms over repairing components one at a time.
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We address a dynamic repair shop scheduling problem in the context of military aircraft fleet management where the goal is to maintain a full complement of aircraft over the long-term. A number of flights, each with a requirement for a specific number and type of aircraft, are already scheduled over a long horizon. We need to assign aircraft to flights and schedule repair activities while considering the flights requirements, repair capacity, and aircraft failures. The number of aircraft awaiting repair dynamically changes over time due to failures and it is therefore necessary to rebuild the repair schedule online. To solve the problem, we view the dynamic repair shop as successive static repair scheduling sub-problems over shorter time periods. We propose a complete approach based on the logic-based Benders decomposition to solve the static sub-problems, and design different rescheduling policies to schedule the dynamic repair shop. Computational experiments demonstrate that the Benders model is able to find and prove optimal solutions on average four times faster than a mixed integer programming model. The rescheduling approach having both aspects of scheduling over a longer horizon and quickly adjusting the schedule increases aircraft available in the long term by 10% compared to the approaches having either one of the aspects alone.