Browsing by Author "Barkokebas, Beda"
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- ItemCan Advanced Work Packaging Become a Lean Method?(2023) Sepulveda Solari, Italo Gerald; Alarcón Cárdenas, Luis Fernando; Barkokebas, BedaAdvanced Work Packaging (AWP) is rapidly becoming a popular methodology to improve efficiency in construction projects. It is an innovative approach to project management that focuses on the planning, organization, and control of construction tasks on the job site is based on the idea that by organizing work effectively and reducing lead times, it is possible to maximize efficiency and productivity in construction. Nevertheless, Lean Construction (LC) practitioners identified significant shortcomings in AWP such as the lack of attention to buffers while arguing that this methodology is not effective in a practical setting. In this context, this research presents a literature review identifying the criticism of LC practitioners to AWP while identifying similarities and possible synergies where both approaches can complement each other to render better results during the delivery of construction projects. This research identifies the implementation of the Last Planner System® (LPS®) as means to address significant AWP shortcomings identified by LC practitioners while taking advantage of AWP’s structured approach to better apply LC concepts. Therefore, the identified synergies and combination of both approaches will contribute to more efficient processes and improvement of construction practices.
- ItemDigitalization-based process improvement and decision-making in offsite construction(Elsevier B.V., 2023) Barkokebas, Beda; Martinez P.; Bouferguene A.; Hamzeh F.; Al-Hussein M.The evaluation of process improvements measures in offsite construction shop floors often relies on experts' opinion, with limited use of empirical data gathered by sensors in real-time. To address this issue, there is a need for methods that integrate expert's tacit knowledge with robust data analysis techniques. This paper describes the application of exploratory data analysis techniques to evaluate improvement suggestions proposed by expert's, supported by data collected by sensors on the shop floor and building information models. The presented method involves a quantitative and qualitative digitalization-based approach where improvement suggestions are modelled and validated though machine learning algorithms and hypothesis testing. The contribution of this study is a method that combines real-time data, building information models, and knowledge modeling from experts to evaluate process improvement on offsite construction shop floors
- ItemFlexible Robotic Production in Off-Site Construction: A Lean Approac(2023) Cardenas Castaneda, Jennifer Alejandra; Barkokebas, Beda; Martínez, Pablo; Ahmad, RafiqThe integration of robotics into flexible manufacturing systems (FMS) has been identified as a potential strategy for increasing modular construction flexibility. The purpose of this paper is to present a conceptual framework for investigating the relationship between FMS and robotics in modular construction. The framework proposes that by incorporating robotics into FMS, prefabricated building component manufacturing systems will gain flexibility. The two key variables of the framework are robotics (as the independent variable) and FMS (as the dependent variable). Moderator variables such as controlled environment and variability are also considered, as are mediator variables such as real-time adjustments, productivity, equipment utilization, set-up times, varying speeds, and reduced manpower. The purpose of this paper is to set the theoretical foundation for further studies on robotics integration into FMS in modular construction. The paper concludes with a discussion of the proposed implications of the framework for modular construction practitioners and researchers.
- ItemImproving Premanufacturing Phases in Off-Site Construction Through a Digitalization Approach(2023) Barkokebas, Beda; Ost, Felipe; Mourgues Alvaréz, Claudio Enrique; Saruhashi, LissaThe integration of digitalization and building information modelling (BIM) has been lauded as a cornerstone to improve processes and enhance communication across the construction industry. Nevertheless, the implementation of digitalization approaches has suffered due to the lack of methods and processes uncertainties, particularly in the case of off-site construction (OSC) companies where its premanufacturing phases (design, planning, and procurement) differ significantly from traditional construction. This research presents a case study of a digitalization-based workflow to reduce the duration and increase accuracy of premanufacturing phases. To that end, a digitalization plan is developed using value stream maps, supported by Monte Carlo simulation, to identify the waste of current practices and propose suitable improvement measures. Afterwards, a digitalization-based workflow is developed and implemented to exchange data between BIM models and other systems. After one year and a half of implementation, the proposed workflow reduced the duration of tasks in 92.31% while providing an average of 12.24% more accurate bill of materials compared to the previous approach. As such, the contribution of this study is twofold: first, a lean-based method to implement digitalization in OSC companies considering its particularities and inherited process uncertainties; and second, an improved process for OSC premanufacturing phases