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Several different simulation techniques, such as discrete event simulation (DES), system dynamics (SD) and agent-based modelling (ABM), have been used to model complex construction systems such as construction processes and project management practices; however, these techniques do not take into account the subjective uncertainties that exist in many construction systems. Integrating fuzzy logic with simulation techniques enhances the capabilities of those simulation techniques, and the resultant fuzzy simulation models are then capable of handling subjective uncertainties in complex construction systems. The objectives of this chapter are to show how to integrate fuzzy logic and simulation techniques in construction modelling and to provide methodologies for the development of fuzzy simulation models in construction. In this chapter, an overview of simulation techniques that are used in construction is presented. Next, the advancements that have been made by integrating fuzzy logic and simulation techniques are introduced. Methodologies for developing fuzzy simulation models are then proposed. Finally, the process of selecting a suitable simulation technique for each particular aspect of construction modelling is discussed.

The overarching objective of this research is to integrate the Lean Six Sigma (LSS) framework with computer simulation to improve the production efficiency of a light-emitting diode (LED) manufacturing factory.

Recently, the idea of taking advantage of the benefits of Six Sigma and simulation models together has led both industry and the academy towards further investigation and implementation of these methodologies. From this perspective, the present research will illustrate the effectiveness of using LSS methodology in a real factory environment by using the combination of three simulation methods which are system dynamics (SD), discrete-event simulation (DES) and agent-based (AB) modelling.

The hybrid simulation method applied in this research was found to accurately mimic and model the existing real factory environment. The define, measure, analyse, control and improve (DMAIC)-based improvements showed that the applied method is able to improve machine utilization rates while balancing the workload. Moreover, queue lengths for several stations were shortened, and the average processing time was decreased by around 50%. Also, a weekly production increase of 25% was achieved while lowering the cost per unit by around 8%.

While the case study used was for a LED manufacturing system, the proposed framework could be implemented for any other existing production system. The research also meticulously presents the steps carried out for the development of the multi-method simulation model to allow readers to replicate the model and tailor it for their own case studies and projects. The hybrid model enables managers to navigate the trade-off decisions they often face when choosing advanced production output ahead of continuous improvement practices. The adoption of methodologies outlined in this paper would attain improvements in terms of queue lengths, utilization, reduced costs and improved quality and efficiency of a real, small factory. The findings suggest improvements and create awareness among practitioners for the utilization of quality tools that will provide direct benefits to their companies. Although the multi-method simulation is effective, a limitation of the current study is the lack of micro details within each station. Furthermore, the results are all based on one specific case study which is not enough to suggest and generalized findings.

This research combines the use of the three main hybrid simulation paradigms (SD, DES and AB) in a unified framework DMAIC methodology. Choosing the right models in DMAIC is important, challenging and urgently necessary. Also, this paper shows empirical evidence on its effectiveness.

The purpose of this paper is to conduct a survey on research in fabric and cloth simulation using mass spring model. Also in this paper some of the common methods in process of fabric simulation in mass spring model are discussed and compared.

This paper reviews and compares presented mesh types in mass spring model, forces applied on model, super elastic effect and ways to settle the super elasticity problem, numerical integration methods for solving equations, collision detection and its response. Some of common methods in fabric simulation are compared to each other. And by using examples of fabric simulation, advantages and limitations of each technique are mentioned.

Mass spring method is a fast and flexible technique with high ability to simulate fabric behavior in real time with different environmental conditions. Mass spring model has more accuracy than geometrical models and also it is faster than other physical modeling.

In the edge of digital, fabric simulation technology has been considered into many fields. 3D fabric simulation is complex and its implementation requires knowledge in different fields such as textile engineering, computer engineering and mechanical engineering. Several methods have been presented for fabric simulation such as physical and geometrical models. Mass spring model, the typical physically based method, is one of the methods for fabric simulation which widely considered by researchers.

In recent times, the idea of taking advantage of the benefits of simulation techniques and Six Sigma discipline altogether has led various organizations towards implementation of simulation tools within Six Sigma methodology. The purpose of this study is to provide a more comprehensive literature review on the topic exploring how this amalgamation could work both in theory and practice. This precisely entailed finding dependable studies that shows how Six Sigma (DMAIC) Methodology can be enhanced by the three prevalent simulation techniques; Agent-Based (AB), Discrete-Events (DE), System Dynamics (SD).

A systematic literature review was considered more fitting in research because it involves rigorous and well-defined approach compared to other forms of literature review. In this case, the literature was comprehensive, well-encompassing and involved finding Six Sigma and Simulations literatures from reputable scholarly databases. The outcome of these reviews was the identification of a set of key finding compiled and classified by topics. The study follows an inductive approach and utilises a meta-synthesis review technique.

As numerous studies assert, simulation techniques including AB, DE and SD are applicable tools in almost every stage of DMAIC, especially the Analyse, Improve and Control phases, because of their capability to test and identify potential bottlenecks and improvement areas. Findings show that the simulation tools such as CLDs, Group Model Building, Dynamic Balance Scorecards and Cost of poor quality all have the potential to add value to a Six Sigma methodology.

The findings of this study highlight the importance of further inquiry in this area of study. The finding of this study suggests that although the study on the integration of Six Sigma and simulations is increasing, empirical evidence on its effectiveness is still limited. Therefore, this study suggests more roadmaps and investigations aimed at merging Six Sigma methodology and various simulation technique. Moreover, studies that centre on hybrid or multi-method simulations within Six Sigma are also urgently necessitated.

This study aims to optimize the manufacturing process to improve the manufacturing quality, costs and delivering time with the help of multiscale multiphysics modelling and simulation. Multiscale multiphysics-based modelling and simulations are receiving more and more interest by research community and the industry particularly in the context of increasing demands for manufacturing high precision complex products and understanding the intrinsic complexity in associated manufacturing processes.

In this paper, some modelling and analysis techniques using multiscale multiphysics modelling are presented and discussed.

Furthermore, the possibility of adopting the multiscale multiphysics modelling and simulation to develop the virtual machining system is evaluated, and further supported with an industrial case study on abrasive flow machining (AFM) of integrally bladed rotors using the techniques and system developed.

With the development of multiscale multiphysics-based modelling and simulation, it will enable effective and efficient optimisation of manufacturing processes and further improvement of manufacturing quality, costs, delivery time and the overall competitiveness.

Business renovation, the effective utilisation of information technology and the role of business process modelling and simulation, are all vital in supply chain integration projects. This paper aims to show through a combination of these methods how the performance of the supply chain can be improved with the renovation and integration of processes at various tiers in the chain and by the sharing of information between companies.

Simulation‐based methodology for measuring the benefits of the creation and renovation of business process models combines the methodology of developing process models and its simulation with the simulation of supply and demand. A procurement process in the oil/retail petrol industry is examined in a case study.

Using the proposed methodology, different business process models can be investigated and simulated. The benefits for each company involved in the presented case are substantial and can be estimated through a simulation. Substantial benefits in costs, quality and lead times were identified, however, their distribution is not symmetric. Inter‐organisational IS and applied technology were enablers for supply chain integration. However, organisational changes and new business models were prerequisites for obtaining those benefits.

The process approach to supply chain integration presents a mechanism that can be applied to any industry. It represents a systematic methodological business renovation approach involving cost cuts, quality improvements and lead‐time improvements. The costs of supply chain integration projects were not studied. The benefits should be measured against the cost of testing the economic feasibility of such projects.

The effective utilisation of business process modelling and a simulation of the necessary business renovation are shown. The novel combination of business process and demand/supply simulation enables an estimation of changes in lead‐times, process execution costs, quality of the process and inventory costs. Although the methodology is presented through a case study of the oil/retail petrol industry, it can also be used to estimate the benefits and monitor supply chain integration projects in other industries.

Integrating construction and site layout planning in mechanized tunnel infrastructure projects is essential due to the mutual impacts of construction planning and site layout decisions. Simulation can incorporate site layout planning and construction planning of tunneling projects in a unified environment. However, simulation adoption by industry practitioners has remained relatively limited due to the special skills required for building and using simulation models. Therefore, this paper aims to create a simple-to-use simulation tool that supports site layout and construction operation planning of tunneling projects. This tool intends to promote the simulation application in site layout planning.

The current paper proposes simulation as a decision support tool (DST) to provide an integrated environment for modeling tunnel construction operations, site layout and capturing the mutual impacts. A special purpose simulation (SPS) tool was customized and developed for typical mechanized tunneling projects, by tunnel boring machines, to facilitate building the model and allow access to users with limited simulation knowledge.

The results show that the developed SPS tool is of great assistance to construction industry practitioners to analyze a variety of site layout and construction plan scenarios and make informed decisions based on its comprehensive and intuitive outputs.

The main contribution of this research is to promote simulation application in site layout planning of tunneling projects through the development of a simple-to-use tool, which has sufficient details for site layout planning and constraints. The developed DST enables planners to make decisions simultaneously on the site layout, other construction planning variables and identify the most efficient plan.

The purpose of this paper is twofold: first, to discuss key challenges associated with the use of either simulation or real-world application of intelligent autonomous vehicles (IAVs) in supply network operations; and second, to provide a theoretical and empirical evidence-based methodological framework that supports the integrated application of conceptualisation, simulation, emulation and physical application of IAVs for the effective design of digital supply networks.

First, this study performs a critical review of the extant literature to identify major benefits and shortcomings related to the use of either simulation modelling or real-word application of physical IAVs. Second, commercial and bespoke software applications, along with a three-dimensional validation and verification emulation tool, are developed to evaluate an IAV’s operations in a conceptual warehouse. Third, a commercial depth-sensor is used as a test bed in a physical setting.

The results demonstrate that conceptual and simulation modelling should be initially used to explore alternative supply chain operations in terms of ideal performance while emulation tools and real-world IAV test beds are eminent in validating preferred digital supply chain design options.

The provided analysis framework was developed using literature evidence along with experimental work and research experience, without consulting any industry experts. In addition, this study was developed based on the application of a single physical device application as a test bed and, thus, the authors should further progress with the testing of a physical IAV in an industrial warehouse.

The study provides bespoke simulation modelling and emulation tools that can be useful for supply chain practitioners in effectively designing network operations.

This work contributes in the operations management field by providing both a multi-stage methodological framework and a practical “toolbox” for the proactive assessment and incorporation of IAVs in supply network operations.

This paper focuses on a conceptual methodology for an integrated simulation model dubbed as dynamic simulation modelling system (DSMS) for proactive and optimal decision making within a project management framework. Due to the uncertainties in project environment, the technical and operational functionality of a facility needs to be assessed during development and operation phases of the project. The simulation model is used for optimising the investment decisions vis‐à‐vis evaluation of functionalities on project facilities in early stages of the project. Project life cycle objective functions (LCOFs) are employed as a set of decision criteria throughout the project’s life. The discussion is being extended on the need for setting up an integrated and user‐friendly model to encompass the processes in the entire life cycle of the project. Details of the system are described and a hypothetical case study is used to demonstrate its capabilities. Possible extensions are then outlined. The C++ programming language in association with the object‐oriented database management system is used to achieve the aforementioned objectives.