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Determining staffing levels for a product inspection process

University of British Columbia

A company seeks a methodology to determine staff levels for its product inspection system. This company produces a type of product that requires 100% inspection before being shipped. The system is a complex tandem queue with machines or operators working in parallel at each station and having dynamic interaction between the inspection rates at two of the stations. The products to be inspected arrive at the inspection system stochastically, with the volume fluctuating considerably with time. However, the expected volume is partially predictable by time of day. If congestion occurs in the system, new products will not be able to enter and receive inspection. To ensure a reliable inspection system where the probability of system congestion is nearly zero, it is desired to determine the minimum staffing level required for different product volumes to avoid system congestions. In this thesis, we investigate the staffing problem in two ways. First, we develop a simulation model for the inspection system. The simulation model is used for scenario and sensitivity analyses to calculate the service rate of the inspection system for various staffing levels and then to determine the minimum number of staff required to ensure system reliability for a range of product volumes. Next, we apply queuing theory to the staffing analysis, and show that the staffing levels determined by the queuing theory approximation are close to the simulation results. The actual company and the nature of the products involved must remain confidential. Similarly, all data in this thesis have been scaled by an arbitrary number. However, the critical topology of the queuing system, the nature and demands of the problem and the methodology of their solution are easily portable to other environments.

Thesis/Dissertation

application/pdf

2009-11-17

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http://hdl.handle.net/2429/15164

Business Administration

University of British Columbia

UBCV

DSpace