A knowledge-based performance measurement system for improving resource utilization

In current manufacturing industry, there are various challenges including short product life cycle, process automation and global competition. It is critical for the manufacturing companies to ensure effective utilization of production assets for overall business success. In order to focus scarce resources on areas that have the greatest impact on productivity, performance evaluation on the resource allocation is necessary to assist companies improving the resource utilization and accomplishing their objectives. In this paper, a knowledge-based performance measurement system (KPMS) is designed to evaluate the resource allocation decisions and provide recommendations to improve the performance and physical asset utilization. The framework of the proposed system, which is constructed by rule-based reasoning, case-based reasoning and a mathematical model, is introduced. By integrating the mathematical model with knowledge rules, performance indicators that are associated with the achievement of company objectives can be determined to quantify the performance of the resource allocation. Moreover, case-based reasoning technique is adopted to evaluate the performance and reuse the experience in past cases to provide recommendations for improvement.