《系统工程》课程教学资源（英文文献）Simulation modeling of customized product family decision points and logistics

Simulation modeling of customized productfamily decision points and logisticsAbstract: Long lead time customized products generally require product specificdecisions from customers throughout different phases of the production system. Inaddition to the system integration plan, logistics plans also depend on thecustomization decisions. In order to have statistically predictable performance basedon the roles and influence of all participants across different domains of production.systems, a simulation modelingmethod is employed to address some of thepossibleoutcomes.The production system in this research contains partners across differentcontinents, different manufacturing segments and with a very complex logisticssystem. Customer decision points and the individual production starting times fordifferent interim, products have significant impacts on the productivity of the overallsystem. In other words, customization decisions can be made throughout theproduction process, but the timing of the decisions has a significant impact onproductivity. Additionally, since the production system has widely varying startingtimes for different interim products, each supplier is at a different point on itsimprovement (learning) curve as the production system, operates. Other challenges inmodeling this system are associated with the speed of customized processimprovements,customer preferred configurations,logistics,andproduction ratemanagement.This paper will address research into and findings from a simulationmodel of this integrated production system for customized products with specificconsideration of these elements:customer product customization decision points,supplier related event management, component transportation logistics among keypartners, the framework for simulation modeling,and improvement curve impactsamong partners in the production system. (9 refers.)Controlled terms: Computersimulation Decision making Industrial management Statistical methods Uncontrolledterms: Customerdecision points-Mass customization

Simulation modeling of customized product family decision points and logistics Abstract: Long lead time customized products generally require product specific decisions from customers throughout different phases of the production system. In addition to the system integration plan, logistics plans also depend on the customization decisions. In order to have statistically predictable performance based on the roles and influence of all participants across different domains of production, systems, a simulation modeling method is employed to address some of the possible outcomes. The production system in this research contains partners across different continents, different manufacturing segments and with a very complex logistics system. Customer decision points and the individual production starting times for different interim, products have significant impacts on the productivity of the overall system. In other words, customization decisions can be made throughout the production process, but the timing of the decisions has a significant impact on productivity. Additionally, since the production system has widely varying starting times for different interim products, each supplier is at a different point on its improvement (learning) curve as the production system, operates. Other challenges in modeling this system are associated with the speed of customized process improvements, customer preferred configurations, logistics, and production rate management. This paper will address research into and findings from a simulation model of this integrated production system for customized products with specific consideration of these elements: customer product customization decision points, supplier related event management, component transportation logistics among key partners, the framework for simulation modeling, and improvement curve impacts among partners in the production system. (9 refers.)Controlled terms: Computer simulation Decision making Industrial management Statistical methods Uncontrolled terms: Customer decision points -Mass customization