The article presents research on the relationship between mining and used resources on the example of Gliśno gravel pit. As regards to resources, the following issues were analyzed: employees’ working time, time of running machines, fuel consumption and electricity consumption. The aim of the publication is to examine the dependencies that exist between the analyzed variables. KPI’s (Key Performance Indicators) were calculated for individual resources. The analysis presented in the publication contains data from 2008-2014.
An accurate use of the ability to steer computer efficiency is essential from the database point of view. Effective resource allocation is dependent on the performance indicators gathered from running systems. There must be an appropriate balance between accurate measurements, performance indicators and speed of the reallocation algorithms of the computing resources. The extended measurement of efficiency which the authors propose for applications is: the average number of queries within a time unit for particular groups of users. This paper presents an analysis of using the Workload Manager utility in the AIX 5L operating system to improve the efficiency of applications in the MySQL database environment, and an analysis of methods which allows the use of Workload Manager for steering efficiency dynamically.
Performance measurement system in supply chain management (SCM) has been receiving increasing attention by business organizations as a way to evaluate efficiency in supply chain activities. Assessing the performance of supply chain uncovers the gap between planning and actual performance as to trace the potential problems thus ascertain necessary areas for improvement. This research aims to investigate the application of performance measurement system in SCM as well as exploring its relationship with organization’s performance among Malaysian manufacturing firms. By utilizing the questionnaire method, respondents involved were requested to indicate the extent to which they use a number of 24 selected performance measures that are related to SCM. The results show that the majority of the observed manufacturing firms utilize specific performance measurement tools in evaluating the supply chain performance. The current performance measurement techniques, the Balanced Score Card is adopted by around a quarter of the total responding firms followed by Supply Chain Operations References Model – SCOR, which attracts total users of only a fifth of the total respondents. In particular, performance measures under customer service category recorded the highest number of usage followed by cost-based performance measures and operations management. The results of this investigation also unveil few major points that are important to be highlighted. Firstly, the obtained outcomes of this study bring to light the significant relationships between the utilization of supply chain performance measures under customer service, operations management and organizational performance. In addition, this study discovered a significant correlation between the size of the organization and the extent of use of supply chain performance measures and how these two variables positively correlated. Lastly, the findings also suggested that the performance measures for SCM has been playing a crucial role in enhancing the performance of the organizations and is increasingly operated as the firms grow in size. Based on the brief highlighted points listed above, it is not an exaggeration to say that this research contributes new information to the body of knowledge in performance measurement system in SCM and its associations with organizational performance.
The material presents a real problem inherent in the management of computer systems, namely that of finding the appropriate system settings and thus being able to achieve the expected perfor- mance. The material also presents a prototype which aims to adapt the system in such a way as to achieve the objective, defined as the application efficiency. The prototype uses a resource-oriented mechanism that is built into the OS Workload Manager and is focused on a proposed goal-oriented subsystem based on fuzzy logic, managing resources to make the best use of them, and pursuing translation to the use of system resources, including nondeterministic technology-related factors such as duration of allocation and release of the resources, sharing the resources with the uncapped mode, and the errors of performance measurement.
An original fuzzy team control model is presented in this article. The model is based on a non-traditional combination of classical and contemporary achievements of management and mathematical theories of fuzzy logic and fuzzy sets. In methodological terms, the article also offers a set of tools for measuring and evaluating both team performance and the effectiveness of the team control system in the organization. Fuzzy tools and techniques for decision-making, studying of hidden effects and joint influences, and quantification of evaluations are employed in this set of tools. The suggested fuzzy model contributes to overcoming theoretical deficits on the issues of team control, and the methodology of team control fills a gap in the toolkit of team management. The results from verification of the fuzzy team control model at a small-sized Bulgarian enterprise are also discussed in this article. They indicate that it is possible to develop a fuzzy model for team control, increasing the effectiveness of the team control system in the enterprise.
Rescheduling is a frequently used reactive strategy in order to limit the effects of disruptions on throughput times in multi-stage production processes. However, organizational deficits often cause delays in the information on disruptions, so rescheduling cannot limit disruption effects on throughput times optimally. Our approach strives for an investigation of possible performance improvements in multi-stage production processes enabled by realtime rescheduling in the event of disruptions. We developed a methodology whereby we could measure these possible performance improvements. For this purpose, we created and implemented a simulation model of a multi-stage production process. We defined system parameters and varied factors according to our experiment design, such as information delay, lot sizes and disruption durations. The simulation results were plotted and evaluated using DoE methodology. Dependent on the factor settings, we were able to prove large improvements by real-time rescheduling regarding the absorption of disruption effects in our experiments.