Faculty Publications, Working Papers
| RMU Research #: | 14754 |
| Title: | Use of Bayesian Probabilities to Identify and Improve Distribution Center Error Rates |
| Author/PI: | Derya A Jacobs; Paul Kauffmann, Abel Fernandez |
| Date(s): | 09/01/2002 |
| Category: | Engineering |
| Type: | Journal Paper |
| Description: | Performance of each link in the supply chain is critical for overall system results and no link is more important than the distribution system since error or inefficiency at this point cannot be corrected and will impact customer satisfaction. This paper describes a study that identified error rates and developed a quality control tool to improve the performance of a regional distribution center. Using Bayes law of conditional probability, line item error rates were found to vary according to the number of cases ordered. This insight led to development of a two tier system of complementary control charts to monitor and support order shipment accuracy. This paper demonstrates the usefulness of statistical quality systems in supply chain management and provides practical approaches to quality system development. The paper was published in the "Production and Inventory Management Journal", Vol.43, No. 1, pp. 231-238. |
| Document: | Not Available, Please Contact Author |