Smart Project Management Information Systems (SPMIS) for Engineering Projects – Project Performance Monitoring & Reporting

Engineering projects are becoming increasingly complex as projects get larger and as technology improves. Greater competition worldwide has meant that projects are delivered quicker and cheaper. This necessitates sophisticated Project Management Information System (PMIS) technologies to be adopted to improve efficiency and quality on projects. PMIS data and reports can be used to better understand the risk exposure, resource utilisation, profitability, and scheduling of a project. It also informs strategic project decisions and performance monitoring and reporting. Unfortunately, project data is often fragmented and embedded in different systems. This paper investigates several commercially available PMIS, to understand and compare the functionality of these systems. A qualitative study using semi-structured interviews was conducted with purposively selected project systems experts at twelve project-based organisations. Thematic analysis revealed what functions PMIS fulfils, how these systems are integrated and how they facilitate project monitoring and reporting. Moreover, a novel model for the basic architecture of a ‘Smart’ Project Management Information System (SPMIS) is proposed, which would facilitate software integration and intelligence based on identified industry needs and requirements. The model addresses the shortcomings of existing models by combining models and incorporating system intelligence i.e. the automation of certain project management activities

Smart Project Management Information Systems (SPMIS) for Engineering Projects – Project Performance Monitoring & Reporting

Engineering projects are becoming increasingly complex as projects get larger and as technology improves. Greater competition worldwide has meant that projects are delivered quicker and cheaper. This necessitates sophisticated Project Management Information System (PMIS) technologies to be adopted to improve efficiency and quality on projects. PMIS data and reports can be used to better understand the risk exposure, resource utilisation, profitability, and scheduling of a project. It also informs strategic project decisions and performance monitoring and reporting. Unfortunately, project data is often fragmented and embedded in different systems. This paper investigates several commercially available PMIS, to understand and compare the functionality of these systems. A qualitative study using semi-structured interviews was conducted with purposively selected project systems experts at twelve project-based organisations. Thematic analysis revealed what functions PMIS fulfils, how these systems are integrated and how they facilitate project monitoring and reporting. Moreover, a novel model for the basic architecture of a ‘Smart’ Project Management Information System (SPMIS) is proposed, which would facilitate software integration and intelligence based on identified industry needs and requirements. The model addresses the shortcomings of existing models by combining models and incorporating system intelligence i.e. the automation of certain project management activities

A dynamic scheduling model for construction enterprises

The vast majority of researches in the scheduling context focused on finding optimal or near-optimal predictive schedules under different scheduling problem characteristics. In the construction industry, predictive schedules are often produced in advance in order to direct construction operations and to support other planning activities. However, construction projects operate in dynamic environments subject to various real-time events, which usually disrupt the predictive optimal schedules, leading to schedules neither feasible nor optimal. Accordingly, the development of a dynamic scheduling model which can accommodate these real-time events would be of great importance for the successful implementation of construction scheduling systems. This research sought to develop a dynamic scheduling based solution which can be practically used for real time analysis and scheduling of construction projects, in addition to resources optimization for construction enterprises. The literature reviews for scheduling, dynamic scheduling, and optimization showed that despite the numerous researches presented and application performed in the dynamic scheduling field within manufacturing and other industries, there was dearth in dynamic scheduling literature in relation to the construction industry. The research followed two main interacting research paths, a path related to the development of the practical solution, and another path related to the core model development. The aim of the first path (or the proposed practical solution path) was to develop a computer-based dynamic scheduling framework which can be used in practical applications within the construction industry. Following the scheduling literature review, the construction project management community s opinions about the problem under study and the user requirements for the proposed solution were collected from 364 construction project management practitioners from 52 countries via a questionnaire survey and were used to form the basis for the functional specifications of a dynamic scheduling framework. The framework was in the form of a software tool fully integrated with current planning/scheduling practices with all core modelling which can support the integration of the dynamic scheduling processes to the current planning/scheduling process with minimal experience requirement from users about optimization. The second research path, or the dynamic scheduling core model development path, started with the development of a mathematical model based on the scheduling models in literature, with several extensions according to the practical considerations related to the construction industry, as investigated in the questionnaire survey. Scheduling problems are complex from operational research perspective; so, for the proposed solution to be functional in optimizing construction schedules, an optimization algorithm was developed to suit the problem's characteristics and to be used as part of the dynamic scheduling model's core. The developed algorithm contained few contributions to the scheduling context (such as schedule justification heuristics, and rectification to schedule generation schemes), as well as suggested modifications to the formulation and process of the adopted optimization technique (particle swarm optimization) leading to considerable improvement to this techniques outputs with respect to schedules quality. After the completion of the model development path, the first research path was concluded by combining the gathered solution's functional specifications and the developed dynamic scheduling model into a software tool, which was developed to verify & validate the proposed model s functionalities and the overall solution s practicality and scalability. The verification process started with an extensive testing of the model s static functionality using several well recognized scheduling problem sets available in literature, and the results showed that the developed algorithm can be ranked as one of the best state-of-the-art algorithms for solving resource-constrained project scheduling problems. To verify the software tool and the dynamic features of the developed model (or the formulation of data transfers from one optimization stage to the next), a case study was implemented on a construction entity in the Arabian Gulf area, having a mega project under construction, with all aspects to resemble an enterprise structure. The case study results showed that the proposed solution reasonably performed under large scale practical application (where all optimization targets were met in reasonable time) for all designed schedule preparation processes (baseline, progress updates, look-ahead schedules, and what-if schedules). Finally, to confirm and validate the effectiveness and practicality of the proposed solution, the solution's framework and the verification results were presented to field experts, and their opinions were collected through validation forms. The feedbacks received were very positive, where field experts/practitioners confirmed that the proposed solution achieved the main functionalities as designed in the solution s framework, and performed efficiently under the complexity of the applied case study

Construction Productivity Estimation Model Using Artificial Neural Network for Founda-tions Works in Gaza Strip Construction Sites

Estimating the construction labor productivity con-sidering the effect of multiple factors is important for construction planning, scheduling and estimating. In planning and scheduling, it is important to maximize labor productivity and forecast activity durations to achieve lower labor cost and shorter project duration. In estimating, it is important to predict labor costs.The aim of this study is to develop a new technique for estimating labor productivity rate for foundation works in (m3/ day) for building projects in Gaza Strip, through developing a model that is able to help par-ties involved in construction projects (owner, contrac-tors, and others) especially contracting companies to estimating labor productivity rate for foundation works . This model build based on Artificial Neural Networks. In order to build this model, quantitative and qualitative techniques were utilized to identify the significant parameters for estimating labor productivity rate for foundation works. The data used in model development was collected using questioner survey as a tool to collect actual data from contrac-tors for many projects in Gaza Strip. These question-naires provided 111 examples.The ANN model consid-ered 16 significant parameters as independent input variables affected on one dependent output variable “labor productivity rate for foundation works in (m3/ day). Neurosolution software was used to train the models. Many models were built but GFF model was found the best model, which structured from one input layer, included 16 input neurons, and included one hidden layer with 22 neurons. The accuracy perfor-mance of the adopted model recorded 98% where the model performed well and no significant difference was discerned between the estimated output and the actual productivity value.Sensitivity analysis was per-formed using Neurosolution tool to study the influ-ence of adopted factors on labor productivity. The performed sensitivity analysis was in general logically where the “Footings Volume” had the highest influ-ence, while the unexpected result was “Payment de-lay” factor which hadn't any effect on productivity of foundation works

Project Controls and Management Systems : current practice and how it has changed over the past decade

Project Controls and Management System (PCMS) refers to an ecosystem of processes, tools and personnel required for the proper planning and execution of capital projects throughout the different phases of design, procurement, construction and startup. This can be divided into different focus areas (functions) that would include Estimating, Planning, Scheduling, Cost Control, Change Management, Progressing, and Forecasting. Various trends such as globalization, contractor specialization and information technology developments have impacted the way PCMS are implemented and made it the subject of extensive research over the past years to investigate how to best utilize those trends. Replicating the research methodology used in a 2011 report published by the Construction Research Institute (CII), this work aims to investigate the current status of PCMS implementation and how it has changed over the past decade. It was concluded that while the original PCMS principles are still valid, adoption has drastically changed in terms of efficiency for the majority of the functions. The research also identifies areas of potential concerns and provides recommendations for further improvement.Civil, Architectural, and Environmental Engineerin

A study of project planning on Libyan construction projects

Construction projects are regularly faced by scheduling problems causing the projects to finish beyond their predetermined due date; this is a global phenomenon. The main purpose of this study is to consider the problems associated with project planning generally, with specific reference to construction projects in Libya. This study is unique in two respects. First, despite the recent high volume of infrastructure work in the country, there have been few investigations into construction delays in Libya. Secondly, earlier studies have considered the causes or the effects of project delays, whereas the present aim is to evaluate the potential of applying a planning and scheduling technique that is entirely novel in the Libyan context. The paper reports the results of Phase I of this research

AADLib, A Library of Reusable AADL Models

The SAE Architecture Analysis and Design Language is now a well-established language for the description of critical embedded systems, but also cyber-physical ones. A wide range of analysis tools is already available, either as part of the OSATE tool chain, or separate ones. A key missing elements of AADL is a set of reusable building blocks to help learning AADL concepts, but also experiment already existing tool chains on validated real-life examples. In this paper, we present AADLib, a library of reusable model elements. AADLib is build on two pillars: 1/ a set of ready-to- use examples so that practitioners can learn more about the AADL language itself, but also experiment with existing tools. Each example comes with a full description of available analysis and expected results. This helps reducing the learning curve of the language. 2/ a set of reusable model elements that cover typical building blocks of critical systems: processors, networks, devices with a high level of fidelity so that the cost to start a new project is reduced. AADLib is distributed under a Free/Open Source License to further disseminate the AADL language. As such, AADLib provides a convenient way to discover AADL concepts and tool chains, and learn about its features

Adaption of structured analysis design techniques methodology for construction project planning

The construction industry has been heavily criticised by researchers and governmental organisations for its performance especially excessive delay. Ballard and Howell (2003) indicated that only about 50% of the tasks on weekly work plans are completed by the end of the plan week. This is a result of a lack of either effective project planning or effective production control. It therefore seems the traditional approach of planning is insufficient to meet the current demand and complexity of construction projects. This paper proposes to critically evaluate the adaptation of Structured Analysis Design Techniques (SADT) methodology as a tool for project planning. SADT which was further developed into IDEF (Integrated Definition) techniques claims to be a complete methodology to provide the means of understanding complex production systems and aid the implementation of change. The use of this methodology has led to process improvement. The research uses a literature review followed by interviews with academics and practitioners to investigate their knowledge and understanding of SADT (IDEFO). The results of the interviews indicated that SADT (IDEFO) methodology is seldom known and used in the construction industry. However, this study indicates that SADT methodology appears to be an effective project planning tool. This study contributes to the limited project planning techniques in construction industry by exploring the possible adaption of SADT

A Taxonomy of Data Grids for Distributed Data Sharing, Management and Processing

Data Grids have been adopted as the platform for scientific communities that need to share, access, transport, process and manage large data collections distributed worldwide. They combine high-end computing technologies with high-performance networking and wide-area storage management techniques. In this paper, we discuss the key concepts behind Data Grids and compare them with other data sharing and distribution paradigms such as content delivery networks, peer-to-peer networks and distributed databases. We then provide comprehensive taxonomies that cover various aspects of architecture, data transportation, data replication and resource allocation and scheduling. Finally, we map the proposed taxonomy to various Data Grid systems not only to validate the taxonomy but also to identify areas for future exploration. Through this taxonomy, we aim to categorise existing systems to better understand their goals and their methodology. This would help evaluate their applicability for solving similar problems. This taxonomy also provides a "gap analysis" of this area through which researchers can potentially identify new issues for investigation. Finally, we hope that the proposed taxonomy and mapping also helps to provide an easy way for new practitioners to understand this complex area of research.Comment: 46 pages, 16 figures, Technical Repor