USING MONTE-CARLO SIMULATION TO MEASURE THE BUSINESS-RELEVANT IMPACT OF PLANNING UNCERTAINTY ON FIELD SERVICE DELIVERY

摘要

Today, delivery of industrial maintenance services is planned under uncertainty, as, for example, the true task duration is unknown. Thus, providers rely on estimates at the stage of planning. During operations, the true task duration becomes known which results in a schedule update. This work evaluates the effects of information uncertainty on business-relevant performance indicators in industrial maintenance. We present a simulation model to reflect the evolution of information and the schedule revision during operations. Within a simulation experiment, we measure the business-relevant impact of different uncertainty levels on operations. Indeed, the findings of our research confirm the common understanding that reduced uncertainty at the stage of planning has a positive effect on service delivery. However, our research also shows that in order to achieve business-relevant impact in service delivery quality, the reduction of uncertainty at the stage of planning needs to reach a certain threshold.