The optimisation of Daimlerchrysler's SAP-MRP system through systems analysis, design, and simulation

[摘要] ENGLISH ABSTRACT: This report presents the findings of a study that started as an evaluation of the possible implementationof the Options Inventory Management Model (OIMM), developed by van Wijck and Bekker [4], atDaimlerChrysler South Africa (DCSA). The OIMM System was developed as a possible alternative to theSAP-MRP System to ensure a high Customer Service Level, with the lowest possible inventory level,under the 10 Day Option Freeze Environment.DCSA indicated that although the OIMM System may be an ideal solution, in terms of optimising PlantInventory levels whilst maximising Customer Service Levels, the practical problems associated with thepossible implementation of this system would outweigh the associated benefits. This being the case, adirective was given to investigate the SAP-MRP System's ability to provide a high Customer ServiceLevel under the 10 Day Option Freeze Environment and not to pursue the OIMM implementation option.The objectives of this directive were to evaluate and establish the performance capabilities of the SAPMRPSystem under the 10 Day Option Freeze Environment as well as develop a system to aid in thecustomisation of the system.Design of Experiments (DOE) was utilised to plan the evaluation procedure and to ensure that aconsistent approach was followed. The DOE generated huge amounts of output data that representedthe Usage Category Behaviour Characteristics of the SAP-MRP System. Regression Analysis wasutilised to investigate this data.A part-by-part analysis was avoided and the analysis approach followed presented results that could beapplied to almost the entire range of parts, excluding bulk parts, at DCSA. The results showed thatCoverage Profile alone could be used as a proactive inventory management tool to ensure maximumCustomer Service Level.The Regression Analysis revealed that various combinations of Safety Time, Minimum, and TargetCoverage resulted in similar or equal Avg. Plant Inventories, Avg. Number of Orders, and Avg. OrderSizes. These findings were used to develop a Decision Support Tool that could be used by DCSA whenevaluating the resultant changes caused by the proposed changes in the aforementioned InputParameters.

[发布机构] Stellenbosch University