Beslutsstöd för att integrera ekonomistyrning och produktionssystem samt analysera CCC-effekter

Decision support for integration of economic control and production systems and CCC analysis

Goals/targets: The aircraft engine business is characterized by its need for cash in a time where money is increasingly hard to acquire. It has been shown that unfavorable linkages between control parameters used for economical follow-ups and production control significantly can result in inefficient use of resources, resulting in large amounts of capital tied up in production material (~high CCC). It is therefore urgent to increase the understanding of parameters for economical monitoring and control, and their suitability as measures of production performance (including product cost), in companies within the aircraft engine business. The project therefore aims to deduce and show how different choices of control parameters influence capital and cost. Different parameters and how they relate to concepts as lean, throughput accounting, and Volvo Production System (VPS), will be investigated. The aim of the project is to use these analyses to identify suitable measures for monitoring and control, which will offer means to make economically more sound production decisions. Result and effects To acquire improved understanding of the economical impact of different decisions concerning the production and production development. This ability will improve the ability to make economically sound production decisions. New measures to monitor and control the production will also be developed. Implementation of these findings is expected to lead to reductions of tied-up capital (reduced CCC), increased productivity and reduced product cost. Planning and implementing The project starts with a literature review and a mapping of the actual conditions at Volvo Aero. From this input are relevant problems formulated and their effects described. An analysis is then performed and based on the results are models developed. These are validated and tested, and further developed. Actual cases are continuously used to validate models and methods.