Development and implementation of key performance indicators for aggregate production using dynamic simulation
Artikel i vetenskaplig tidskrift, 2020
Continuous process improvements are needed to maintain and run an industrial operation at a profitable state. An aggregates production plant consists of multiple process operations such as blasting, primary crushing, followed by secondary and tertiary crushing stages with an intermediate screening of products. Each of these processes can be operated with multiple objectives in mind of operators and plant managers. These objectives can be defined by varying terms like generating required throughput of the plant, maintaining equipment’s health, meeting customers’ demands, etc. The use of the term key performance indicators is recurrent in industry to formalise and represent these objectives of operation. Currently, the KPIs defined by the ISO 22400 standards are widespread for continuous improvements in the manufacturing industry and they are viewed as a support tool to measure improvements. The scope of this paper is to calculate relevant KPIs for an aggregates production plant using dynamic simulations. Further, the KPIs are implemented in a three-stage aggregate production plant using both real-time plant data and dynamic process simulation. The KPIs developed are useful for operators and plant managers to make decisions. The results show the relationship and dependencies of various equipment and process KPIs. The dynamic simulation has potential to be used as an exploration tool to identify the opportunities of improvement in aggregates processing using KPIs as a measure. The KPIs presented in the paper are based on ISO 22400 standard and have potential to be extended to similar processing operations such as coarse and fine comminution for minerals processing. Apart from the diagnostics application, the KPIs implemented in the dynamic simulation platform can be used to explore and optimize a crushing plant’s design and operations.