Production system virus analysis tool (PSVA) - problems identification and analysis framework - case study

Background: Identification and analysis of problems occurring i n complex machine-building company production systems is a very crucial stage in the process of i mproving these systems. Effective production systems nowadays are a key to the success for this type of companies. Material and methods: On the basis of production system problem identifi cation and analysis tools known from the subject literature (among others ASIS model, Ishika va (fishbone) diagrams, impact wheels, current real ity tree, risk assessment mapping tools (FMEA), cause and effect diagrams) the authors of this paper proposed their a uthor's identification and analysis framework of problems occurring in machine-building enterprise production systems. The pr oposed tool is a specific hybrid of solutions known from the literat ure. The model has been developed and verified in a running business conditions. Results: Author's tool has been successfully used within the frames of a project aimed at improving the product ion system of one of the Polish biggest machine buildin g's sector manufacturer. Problem identification and analysis framework of production systems in machine-building companies developed within this project has been called Product ion System Virus Analysis (PSVA) for the reason of results presentat ion specific character. In this paper basic assumpt ions and methodology of the tool developed by the Authors have been included. Additionally, in the practical part the Authors present an example of PSVA adoption for problem identification and analysis in the production system of one of the Polish bi ggest machines building company. Conclusions: Every organization needs to use a proper combinatio n and selection tools, methodologies and techniques for identification and analysis of their own proble ms on the path to implementation of improvements. The authors experience show that the appropriate tool: able to identifying core problems, indirect causes and symptoms, signi ficantly improve the efficiency of long-term process of rebuilding produ ction and logistics systems.