Over recent years, the independent adoption of lean construction and building information modeling (BIM) has shown improvements in construction industry efficiency. Because these approaches have overlapping concepts, it is thought that their synergistic adoption can bring many more benefits. Today, implementing the lean–BIM theoretical framework is still challenging for many companies. This paper conducts a comprehensive review with the intent to identify prevailing interconnected lean and BIM areas. To this end, 77 papers published in AEC journals and conferences over the last decade were reviewed. The proposed weighting matrix showed the most promising interactions, namely those related to 4D BIM-based visualization of construction schedules produced and updated by last planners. The authors also show evidence of the lack of a sufficiently integrated BIM–Last Planner System® framework and technologies. Thus, we propose a new theoretical framework considering all BIM and LPS interactions. In our model, we suggest automating the generation of phase schedule using joint BIM data and a work breakdown structure database. Thereafter, the lookahead planning and weekly work plan is supported by a field application that must be able to exchange data with the enterprise resource planning system, document management systems, and report progress to the BIM model.

Building Information Modeling (BIM) arrives in great strength in France and in Europe. This process has been mainly recognized for its capacity to energize the building market by sustainable means and the digitization of the current work system. For the SMEs (a business needs to have fewer than 249 employees to be considered an SME), this vast development site proves to be a difficult shift to implement but one that is not to missed in order to gain competitiveness and be able to compete with markets that remained until now undiscovered. Being able to keep updated on the BIM in the view to understand its strategic stakes and to track its development, expansion, and regulatory framework in France will enable you to decide more efficiently on the strategy of BIM you wish to implement in your business. By defining the current state of your business and by setting targets and timeframes, you undertake a management change. Employees and stakeholders are the key elements of success of the BIM implementation. In order to assess the progress of the BIM maturity in the SMEs, a survey has been given out to several French stakeholders thus allowing us to have a good general vision of the innovation in the SMEs. The results of the survey conducted as part of this article, highlights a real enthusiasm from the participants of this sector, but with some concern and questioning.

Over the last decade, the construction industry has suffered from various issues affecting the planning processes, team management, and decision-making during the design phase. Today, the concepts of Lean construction and Building Information Modeling (BIM) overlap and bring solutions to all phases of a construction project. Numerous studies have shown that leveraging BIM data through Lean principles can significantly improve the overall management of a project. However, the literature is still limited to optimizing the design phase to anticipate any deviation before the start of the work. This article aims to provide an updated review of the interaction between BIM and Lean in the design phase. The study is based on a systematic review of 61 articles selected using the Systematic Literature Review (SLR) approach. The obtained results allowed for the analysis of different Lean methods and tools that interact with BIM. Digitizing these methods and using them together is necessary to facilitate their application in a construction project. Finally, our study provides recommendations for researchers and professionals by identifying future scientific challenges.

The challenge of improving the efficiency of the different phases of a building or infrastructure life demands considerations of innovative technologies such as Augmented Reality (AR) and Virtual Reality (VR). During this last decade, AR/VR systems for construction started to be emerged. These applications aim to virtualize or augment in real time the content of the Building Information Modeling (BIM) in order to support continuous improvement. To ensure the maturity of these applications, implementing a maturity model is needed. Based on literature, several maturity models for BIM have been proposed. However, it stays generic and needs to be adapted to the AR and VR technologies in the BIM context. To that end, we started in this paper by proposing an adapted AR/VR maturity model for BIM that aims to evaluate the maturity of these technologies according to the BIM lifecycle. This model has been conceived based on a mapping between three existing maturity models corresponding to AR, VR and BIM technologies from the most adapted existing works that deal with our goal. As a result of this mapping, three maturity levels have been identified and a detailed description of each level has been established. This model will be proposed to construction companies in order to evaluate their maturities on the use of AR/VR technologies.

Despite the great potential of LPS and BIM to improve construction project productivity, the full integration of these modern production and information management systems at the data processing level is not yet achieved. After matching the literature to empirical studies in a Constructive Research Approach, it emerged that very few studies have investigated how buildings’ data could be preserved and continuously evolve during the project lifecycle. Accordingly, we underline the potential role of data warehousing in rendering operational data as a strategic asset for decision making. These findings motivate the present research, which aims to capitalize on quantity surveying data in order to automate the generation of M & E installation schedules. This paper first introduces the system functional requirements. Then, it proposes a conceptual scheme for the planning data mart (a data warehouse subset dedicated to planning subject area). Furthermore, we shed light on the M & E fragnet standardization procedure and how data have been processed. Finally, we present the current software developments to demonstrate the feasibility of this concept.