Production performance analysis during operation phase: A case study

Abstract

Production performance analysis plays a significant role in supporting the decision-making process, for managers and engineers dealing with the challenges of the optimization procedure of a system delivery capacity. Operational conditions can influence the production performance of a system drastically, in a short or long term, by affecting the system configuration, reliability, maintainability, maintenance supportability, and functional capacity of its components. Moreover, these impacts can lead to increased business risks and uncertainties. Such a situation demands the successful application of tools and methodologies to minimize the total business risk through an accurate prediction of production performance, addressing the effects of operational conditions. However, there is a lack of practical methodologies, for production performance analysis of systems operating under the time-dependent operational conditions. Hence, the central thrust of this article is to develop a systematic methodology, for the production performance analysis of a system considering the time-dependent operational conditions. In the case study, the results show that the production performance of mining equipment is affected significantly by the operational conditions. These changes occur across the working shifts and due to any changes in the production plan of the mine. The result of the analyses shows that the critical items in the mine is the loader. Hence, in order to increase the production performance of the system, the optimization of the reliability or maintainability of the loader needs to be considered as a priority. Moreover, the wagon drill has a significant excess capacity, which means that, by adding more trucks to the system, the production performance of the system can be improved.

A stochastic Petri Net‐based approach for operational performance estimation of quay cranes

“…It is not as easy as gathering reliability data of offshore structures, because they have community to gather those data for later publication in Offshore Reliability Data (OREDA) book. The data from OREDA book normally being utilized by the researchers 10,30,55 . especially when dealing with failure rate of the equipment.…”

“…The data from OREDA book normally being utilized by the researchers. 10,30,55 especially when dealing with failure rate of the equipment. This paper obtained the data from breakdown reports and maintenance records of the quay cranes from port terminal operator.…”

Resilience analysis: A formulation to model risk factors on complex system resilience

“…The mine’s estimated reserves are about 828 million tons, with an average copper grade of 0.62%. In this mine, mining operations at the mine site are conducted by using dump trucks, loaders, excavators, shovels, bulldozers, and drilling rigs (Qarahasanlou et al 2018 ). The characteristics of the mine’s transportation system are introduced in Table 1 .…”

Sustainable production process: An application of reliability, availability, and maintainability methodologies in automotive manufacturing

“…4,5 To ensure a reliable manufacturing process in short or long terms, a systematic analysis of performance, considering all influencing factors, is required. 6 Performance evaluation plays a substantial role in decision-making process, system optimization procedure and decreasing business risks and uncertainties. 7,8…”

“…4,5 To ensure a reliable manufacturing process in short or long terms, a systematic analysis of performance, considering all influencing factors, is required. 6 Performance evaluation plays a substantial role in decision-making process, system optimization procedure and decreasing business risks and uncertainties. 7,8 In recent decades, the majority of performance evaluation programs such as total productive maintenance (TPM), total quality management (TQM), business continuity management (BCM), business process reengineering (BPR), and so on are proposed to achieve the high productivity and availability in process industries, in particular automotive manufacturing.…”