问题描述：
英语翻译
In this dissertation we study spare parts inventory control for stocks needed to facilitate corrective maintenance.The main question under study is which parts to put on stock in which location in which quantity.Such decisions are taken at a tactical planning level.Although there is a number of alternative formulations,we focus on one that is most applicable in situations where service is provided by another party than the owner of the equipment.In these situations,with regard to the corrective maintenance the customer (owner of the equipment) and the service provider agree upon a certain expected performance level in a contract,the service level agreement.
Performance requirements in the service level agreement typically specify constraints on the (expected) system availability,i.e.,constraints on the availability of the equipment at the customer.Either a minimum required (expected) up-time of machines,or
directly related measures are used.Given these system availability constraints,the service provider aims to minimize its total cost.
The time that a machine is down,can be split up into different parts:time to obtain the required spare part,time needed by the engineer to travel to the customer,and time needed to repair the machine.Often,the maximum down-time that follows from the system availability constraints is divided over the different time components.Both the logistics department and the engineers get a separate target,derived from the maximum down-time.Along this principle,system availability constraints are directly translatable into constraints on aggregate waiting time for spare parts,i.e.,constraints on the (expected) waiting time for an arbitrary request for a spare part delivery.Given the aggregate waiting time constraints,the logistics department of the service provider aims to minimize its (expected) spare parts provisioning cost,being cost for holding inventory and transportation cost.
In our research we worked with ASML.This original equipment manufacturer (OEM) acts as service provider to its customers and has to meet tight constraints on the system availability,agreed upon in the service level agreements with its customers.
Derived from these system availability constraints,aggregate mean waiting times are set as target for the service logistics department.
There exists a relation between the optimization model described above,containing a service level constraint,and a cost model formulation,without such a constraint.Under certain conditions,the latter constitutes the Lagrangian relaxation of the former.In the latter,besides inventory holding and transportation cost,penalty cost is taken into account for disservice,e.g.,for stock-out.This relation is described in Van Houtum and Zijm (2000).
In this dissertation we study spare parts inventory control for stocks needed to facilitate corrective maintenance.The main question under study is which parts to put on stock in which location in which quantity.Such decisions are taken at a tactical planning level.Although there is a number of alternative formulations,we focus on one that is most applicable in situations where service is provided by another party than the owner of the equipment.In these situations,with regard to the corrective maintenance the customer (owner of the equipment) and the service provider agree upon a certain expected performance level in a contract,the service level agreement.
Performance requirements in the service level agreement typically specify constraints on the (expected) system availability,i.e.,constraints on the availability of the equipment at the customer.Either a minimum required (expected) up-time of machines,or
directly related measures are used.Given these system availability constraints,the service provider aims to minimize its total cost.
The time that a machine is down,can be split up into different parts:time to obtain the required spare part,time needed by the engineer to travel to the customer,and time needed to repair the machine.Often,the maximum down-time that follows from the system availability constraints is divided over the different time components.Both the logistics department and the engineers get a separate target,derived from the maximum down-time.Along this principle,system availability constraints are directly translatable into constraints on aggregate waiting time for spare parts,i.e.,constraints on the (expected) waiting time for an arbitrary request for a spare part delivery.Given the aggregate waiting time constraints,the logistics department of the service provider aims to minimize its (expected) spare parts provisioning cost,being cost for holding inventory and transportation cost.
In our research we worked with ASML.This original equipment manufacturer (OEM) acts as service provider to its customers and has to meet tight constraints on the system availability,agreed upon in the service level agreements with its customers.
Derived from these system availability constraints,aggregate mean waiting times are set as target for the service logistics department.
There exists a relation between the optimization model described above,containing a service level constraint,and a cost model formulation,without such a constraint.Under certain conditions,the latter constitutes the Lagrangian relaxation of the former.In the latter,besides inventory holding and transportation cost,penalty cost is taken into account for disservice,e.g.,for stock-out.This relation is described in Van Houtum and Zijm (2000).
问题解答：
我来补答展开全文阅读