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Simulation has attracted increasing attention in lean production research as a response to address the complexities of the production environment and difficulties of dealing with changes within a system. Considerable growth of using simulation to facilitate lean acceptance and implementation has been observed across different projects and sectors. However, a thorough review of the development and use of simulation in lean production research is limited.

This study aims to address this gap by reviewing 311 journal papers published in the past two decades on this specific research area and identify the state-of-the-art development and propose future research directions.

The review shows that current studies related to simulation in lean production research can be categorised into two major research streams, namely, simulation assisted lean facilitation and evaluation, and simulation-based lean education and training. Under the first research stream, a total of 19 application areas have been identified which applied both lean and simulation in their studies. The evolution of the simulation techniques used in these studies has been analysed as well. Meanwhile, four types of simulation games have been identified in the stream of simulation-based lean education and training and the impact and applicability of the different simulation and games have been discussed. A framework for engaging lean and simulation is suggested based on the review of the existing studies. The analysis in both streams also highlights the importance of stakeholder engagement and the utilisation of information technologies for future studies.

The findings of this study are expected to provide useful references for the future development and application of simulation in lean production research.

This paper conducted a broad and extensive review of simulation integrated lean production research. An in-depth examination of the retrieved papers was conducted through a structured and quantitative analysis to understand the current body of knowledge.

This paper covers the development of a novel defect model for concrete highway bridges. The proposed defect model is intended to facilitate the identification of bridge’s condition information (i.e. defects), improve the efficiency and accuracy of bridge inspections by supporting practitioners and even machines with digitalised expert knowledge, and ultimately automate the process.

The research design consists of three major phases so as to (1) categorise common defect with regard to physical entities (i.e. bridge element), (2) establish internal relationships among those defects and (3) relate defects to their properties and potential causes. A mixed-method research approach, which includes a comprehensive literature review, focus groups and case studies, was employed to develop and validate the proposed defect model.

The data collected through the literature and focus groups were analysed and knowledge were extracted to form the novel defect model. The defect model was then validated and further calibrated through case study. Inspection reports of nearly 300 bridges in China were collected and analysed. The study uncovered the relationships between defects and a variety of inspection-related elements and represented in the form of an accessible, digitalised and user-friendly knowledge model.

The contribution of this paper is the development of a defect model that can assist inexperienced practitioners and even machines in the near future to conduct inspection tasks. For one, the proposed defect model can standardise the data collection process of bridge inspection, including the identification of defects and documentation of their vital properties, paving the path for the automation in subsequent stages (e.g. condition evaluation). For another, by retrieving rich experience and expert knowledge which have long been reserved and inherited in the industrial sector, the inspection efficiency and accuracy can be considerably improved.

The purpose of this research is to investigate a new approach with its supporting building information modelling (BIM) + augmented reality (AR) tool to enhance architectural visualisation in building life cycle. Traditional approaches to visualise architectural design concentrate on static pictures or three-dimensional (3D) scale models which cause problems, such as expensive design evolution, lack of stakeholders’ communication and limited reusability. The 3D animated fly-throughs still occur on a computer screen in two-dimensions and seem cold and mechanical, unless done with advanced production software.

The method of this research included case study and interview. It was, first, stated, from the building process perspective, how the BIM + AR for Architectural Visualisation System (BAAVS) was realised by integrating two types of visualisation techniques: BIM and AR, and four stages of building life cycle. Then the paper demonstrated four case studies to validate the BAAVS. Finally, four interviews were made with each case manager and team members to collect feedback on utilising BAAVS technology. Questions were asked in the areas of benefits, drawbacks and technical limitations with respect to BAAVS.

Feedback from the stakeholders involved in the four cases indicated that BAAVS was useful and efficient to visualise architectural design and communicate with each other.

This paper demonstrates BAAVS that integrated BIM and AR into architectural visualisation. The system supports an innovative performance that allows: designers to put virtual building scheme in physical environment; owners to gain an immersive and interactive experience; and property sellers to communicate with customers efficiently.

Lean approach has overcome the boundaries of the automotive and manufacturing industry and has achieved many different sectors of the economy, including services. In this context, this paper aims to investigate the applicability of value stream mapping (VSM) tool in processes of the oil and gas chain. Also, this paper investigates if there is a specific framework currently being used by organizations belonging to this chain to map the value stream of its processes.

A detailed systematic review of the literature is done by using a set of relevant keywords based on peer-reviewed journal articles and conference papers available in the Scopus database, analyzing data from 2012 to 2017. Content analysis methodology involving a four-step process (identification, screening, eligibility and inclusion) suggested by Moher et al. (2009) was adopted for this study.

The number of studies in literature on VSM applicability to the oil and gas chain processes is low when compared to studies regarding the application of lean tools and methods in general in this area. Also, there is no specific framework that has been used by the oil and gas chain companies to carry out the VSM, which is a research gap that can be further explored.

Sample size for this research consists of 42 studies, thereby limiting the generalizability of the research studies. However, the analysis presented in this paper was based only on Scopus database, which is a remarkable and broad base, which provided robustness to the data found.

Practicing managers of oil and gas chain who are planning to transform their processes can use the VSM for it. Researchers can explore the research gap found in this study and develop a specific framework to implement VSM in the oil and gas chain processes.

This is the first paper to evaluate the VSM tool applicability to the oil and gas chain processes based on an systematic literature review and understand if this is possible and if there is a specific framework to carry out this task.