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Optimal Server Sharing Decisions in Field Services

Undergraduate #101
Discipline: Technology and Engineering
Subcategory: Civil/Mechanical/Manufacturing Engineering

Christoph Sieberer-Kefer - Savannah State University


The success of companies producing complex equipment such as machines in medical electronics, telecommunications and information technology, industrial automation, building controls, high voltage power equipment, and office products is directly impacted by the quality of after-sales support. Included in after-sales support is the installation, maintenance, and repair of equipment at the customers’ site, which is referred to as field service. Demand for equipment service consists of both planned and unplanned activities. Under the planned activities category, installing, upgrading and preventatively maintaining equipment play a major role. Unplanned activities include repairing nonfunctioning equipment. Machine downtime is usually of uncertain duration and decreases a customer’s productivity and at the same time the cost of machine downtime could be very high. Customer satisfaction relies on the prompt and effective reduction of machine downtime by field services.
The uncertainty of arrival calls for service and the time to complete a service leads to an inability to have the required field service resources available when necessary. Furthermore, it leads to long customer waiting times. When customers have service level agreements, repair should be completed within a specified (guaranteed) time. From queueing theory, we know that providing a low system delay requires low utilization of servers which leads to high service cost. When you have multiple servers, each serving a heterogeneous customer group, the uncertainty in demand and service time leads to greater server workload imbalance. One option is to share servers between territories when necessary. Customer waiting time across different customer groups and server work load across different server groups could be balanced if approached correctly. In other words, a busy server is helped by a not-so busy server to clear the work-backlog and provide timely help.
We consider a field service support system where servers are responsible to service equipment in a given territory. Since response time (defined as the time between equipment failure and a repairperson arriving at the equipment location) is a key performance measure, providing an acceptable response time is very essential. The decision to redeploy a server depends on the tradeoff between the cost of redeploying a server and the benefit obtained by reduced delay. Objective of this study is to investigate the impact of redeploying servers between territories and find an optimal server sharing policy so as to minimize the sum of service cost and customer delay cost.

Funder Acknowledgement(s): National Science Foundation

Faculty Advisor: Suman Niranjan, niranjas@savannahstate.edu

Role: As part of Dr. Niranjan's research team, I was helping with the literature review and the research design. Furthermore, I will be involved in conducting simulations pertaining to our objectives and interpreting and presenting the results.

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This material is based upon work supported by the National Science Foundation (NSF) under Grant No. DUE-1930047. Any opinions, findings, interpretations, conclusions or recommendations expressed in this material are those of its authors and do not represent the views of the AAAS Board of Directors, the Council of AAAS, AAAS’ membership or the National Science Foundation.

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