Construction Project Management

Building Information Modeling (BIM) tools and workflows have the potential to significantly improve the efficiency of design, construction and operation activities. Numerous BIM deliverables and their respective requirements have been widely discussed by industry stakeholders. This is evidenced by the intensity of online communications surrounding BIM topics and the accelerating availability of noteworthy BIM publications (NBP)s. NBPs are publically-available industry documents incorporating guidelines, protocols and requirements focusing on BIM deliverables and workflows. These publications are the product of various governmental bodies, industry associations, communities of practice and research institutions, intended to facilitate BIM adoption, and realize BIM’s value-adding potential.
A specialized taxonomy is employed to analyze 57 noteworthy BIM publications from across eight countries selected for their active BIM scene. The BIM knowledge content (BKC) taxonomy includes three knowledge content clusters (guides, protocols and mandates) subdivided into 18 knowledge content labels (e.g. report, manual, and contract). Ten of these content labels are used to analyze and compare publications from Australia, Denmark, Finland, the Netherlands, Norway, Singapore, the United Kingdom, and the United States. Preliminary content analysis is then performed which provides insight into the availability and distribution of BIM knowledge within noteworthy BIM publications. The analysis identifies knowledge gaps within publications and highlights opportunities for future research and complementary publication efforts.
This chapter contributes to organizing BIM knowledge as contained within numerous noteworthy BIM publications and – by that - facilitates targeted access to their content. It provides a knowledge repository for construction industry stakeholder’s to utilize during BIM implementation and a research base for investigators seeking to identify and address knowledge gaps across the BIM domain.

Building Information Modelling (BIM) is a set of technologies, processes and policies enabling multiple stakeholders to collaboratively design, construct and operate a facility.
There are numerous challenges attributed to BIM adoption by industry and academia. These represent a number of knowledge gaps each warranting a focused investigation by domain researchers. This study does not isolate a single gap to address but espouses a holistic view of the knowledge problem at hand. It contributes to the discussion a set of conceptual constructs that clarify the knowledge structures underlying the BIM domain. It also introduces a number of practicable knowledge tools to facilitate BIM learning, assessment and performance improvement.
This study is delivered through complementary papers and appendices to answer two primary research questions. The first explores the knowledge structures underlying the BIM domain whilst the second probes how these knowledge structures can be used to facilitate the measurement and improvement of BIM performance across the construction industry.
To address the first question, the study identifies conceptual clusters underlying the BIM domain, develops descriptive taxonomies of these clusters, exposes some of their conceptual relationships, and then delivers a representative BIM framework. The BIM framework is composed of three-axes which represent the main knowledge structures underlying the BIM domain and support the development of functional conceptual models.
To address the second question, BIM framework structures are extended through additional concepts and tools to facilitate BIM performance assessment and development of individuals, organizations and teams. These additional concepts include competency sets, assessment workflows and measurement tools which can be used to assess and improve the BIM performance of industry stakeholders.
In addressing these research questions, a pragmatic approach to research design based on available literature and applicable theories has been adopted. By combining several research strategies, paradigms and methods, this study (1) generates several new conceptual structures (e.g. frameworks, models and taxonomies) which collectively clarify the knowledge structures underlying the BIM domain; and (2) develops a set of workflows and tools that facilitate BIM assessment, learning and performance improvement.
This study delivers an extendable knowledge structure upon which to build a host of BIM performance improvement initiatives and tools. As a set of complementary papers and appendices, the study presents a rich, unified yet multi-layered environment of conceptual constructs and practicable tools; supported by a common framework, a domain ontology and simplified visual representations. Individually, each paper introduces a new framework part or solidifies a previous one. Collectively, the papers form a cohesive knowledge engine that generates assessment systems, learning modules and performance improvement tools.

Mainly, the concept of quality control is applying a system of routine technical activities to measure and control activities. In this publication you will find two main tracks of discussion, the quality control procedures in construction field, and also you will find its procedures in project management field in scale of planning, execution, and control. Also you will find a brief about types of sources of specifications. Also the methodology of six sigma which is mainly used to optimize the quality of production.

An initial step towards a prescriptive theory (a set of concepts) to inform the elimination of waste on construction projects. The ultimate intention is to identify the most important types and causes of waste in construction and outline the principal causal relations between them. This is not a straightforward process: the relationships form a complex network of chains and cycles of waste. Waste is defined as the use of more resources than needed, or an unwanted output from production. A conceptual schema of Previous Production Stage > Production Waste > Effect Waste is proposed and applied to the causal analysis of two major types of waste: material waste and making do.