On Reduction of Production Disturbances in Manufacturing Systems Based on Discrete-Event Simulation

Abstract: Improved efficiency in manufacturing systems to achieve increased output and thus reduced production disturbances is a vital area. DES (Discrete-Event Simulation) can visualize and study the dynamic issues related to total efficiency in manufacturing systems. A methodology for production disturbance reduction is presented. Increased performance of manufacturing systems means not only enhanced value for the company but in the long run for the society as a whole. Manufacturing companies are the basis of a country which many other activities rely on. Different production improvement techniques, for example TPS (Toyota Production System), have been shown to smoothe production flows and raise overall quality. Implementation of production disturbance reduction ideas must be conducted according to all basic rules of manufacturing. Contemporary production improvement techniques based on supply chains between different suppliers and limited products in stock make it necessary to focus on production disturbance reduction. The presented methodology is based on three main stages: (1) planning and data gathering, (2) analysis and implementation, and (3) continuous improvement. The planning stage includes project plan, goal and objectives of the study, definition of production disturbances, gathering of input data and logics and the conceptual model. The analysis and implementation stage comprises DES model translation, verification, validation, and experiments. The experiments are based on alternative tests in production disturbance reduction to increase equipment efficiency. The enhanced results in the model should be verified before they are implemented in the real world. Continuous improvement of the proposed methodology includes improvement in model design, studies of production improvement techniques, training of operators, follow-up of implemented changes, investigations in measurement of production disturbances and key figures. The improvement process is a continuing procedure. A model is seldom so good that it yet can not still be improved. With feedback various variables can be altered and the DES model can be improved in several phases. The potential of the methodology was shown in several case studies. The industrial case studies showed improved performance of 6%, 12%, 14%, 18%, respectively. No larger investments were needed to increase the performance. The suggested methodology may enable in increase of total output in a manufacturing system if it is applied.