JITA

JITA Journal of Information Technology and Applications

Vol. 1 No. 1 (2011): JITA - APEIRON

Boris Todorović, Miroslav Matić

Model for Managing Software Development Projects by Fixing Some of the Six Project Management Constraints

Original scientific paper

DOI: https://doi.org/10.7251/JIT1101033T

Abstract

This study is focused on the software development process, viewed from perspective of information technology project manager. Main goal of this research is to identify challenges in managing such projects and provide a model for delivering software solutions that satisfies client’s expectations. Project management theory describes six constraints or variables in every project, which project managers can use to better control the project and its outputs. Fixing some of the six project management constraints (scope, cost, time, risks, resources or quality) will allow project manager to focus on most important project aspects, rather than being drawn between all of the variables.This paper is aimed at information technology project managers and portfolio managers, as it describes the practical application of this model on a software development project. Findings of this research support the theory that, by applying good project management practice and focusing on project/business-critical requirements, will enable project managers to complete projects successfully and within tolerance limits. Results show that by identifying key business constraints, project managers can create good balance of six constraints and focus on the most important ones, while allowing other constraints to move between limits imposed by clients and stakeholders.

Keywords: software development, project management, PMBOK, six project constraints, fi xed project constraints, risk management, quality management, project scope management.

Vol. 26 No. 2 (2023): JITA - APEIRON

Igor Shubinsky, Alexey Ozerov

Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures

Original scientific paper

Abstract

The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.

Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators.

Vol. 26 No. 2 (2023): JITA - APEIRON

Igor Shubinsky, Alexey Ozerov

Application of Artificial Intelligence Methods for the Prediction of Hazardous Failures

Original scientific paper

Abstract

The availability of real-time data on the state of railway facilities and the state-of-the art technologies for data collection and analysis allow transition to the fourth generation maintenance. It is based on the prediction of the facility functional safety and dependability and the risk-oriented facility management. The article describes an approach to assessing the risks of hazardous facility failures using the latest digital data processing methods. The implementation of this approach will help set maintenance objectives and contribute to the efficient use of resources and the reduction of railway facility managers’ expenditures.

Keywords: predictive analysis, maintenance, functional safety, Big Data, Data Science, risk indicators.