An integrated simulation model for site layout planning of tunnelling projects

Overlooking site layout in the planning phase of construction projects leads to loss of productivity and incurs extra costs. In tunneling projects, site layout has a significant impact on material flow and tunneling operations, particularly on congested sites. In addition, construction planning decisions can influence the efficiency of the layout. This paper proposes simulation as a decision making tool to model tunnel construction operations and site layout, and capture their mutual influences. To facilitate building the simulation model, even for users with limited simulation knowledge, a special purpose simulation (SPS) tool was customized and developed. This simulation tool provides an integrated environment to model the parameters of different disciplines including site layout, material procurement, tunnel operations and logistics. The developed tool is of great assistance for the planners to make decisions simultaneously on site layout and other construction planning parameters, and find the most cost-efficient plan

Material and facility layout planning in construction projects using simulation

Layout planning for construction projects comprises two tasks: facility layout planning (FLP) and material layout planning (MLP), which has significant impacts on project cost and time. FLP specifies where to position temporary facilities on the site, and MLP determines the position of the material in the storage yard. This study focuses on MLP and describes a simulation-based method to improve material yard layout. In this method, simulation is employed for modeling the material handling process to evaluate material handling time. Due to the broad domain of possible solutions, simulation is integrated with genetic algorithm to heuristically search for a near optimum material layout with the least haulage time. The implementation of the proposed method is demonstrated in a case study which shows the superiority of the developed method over conventional methods. This paper also discusses how the results of this research can contribute to FLP

Hybrid approach of discrete event simulation integrated with location search algorithm in a cells assignment problem: a case study

[EN] This paper presents a case study describing a cell assignment problem in an assembly facility. These cells receive parts from external suppliers, and sort and sequence these parts to feed the final assembly line. Therefore, to each cell are associated important inbound and outbound flows generating hundreds of material handling equipment movements along the facility, impacting the traffic density and causing eventually safety issues in the plant. Following an important plant redesign, cells have been relocated, and the plant managers need to decide how to manage the new logistic flows. To that aim, a hybrid approach encompassing mathematical optimization and discrete event simulation (DES) is proposed. This approach allows us to reduce complexity by decomposing the design into two phases. The first phase deals with the problem of generating cell¿s assignment alternatives by using a heuristic method to find good quality solutions. Then, a DES software is used to dynamically evaluate the performance of the solutions with respect to operational features such as traffic congestion and intensity. This second phase provides interesting managerial insights on the manufacturing system from both quantitative and qualitative aspects related to in-plant safety and traffic.Saez-Mas, A.; García Sabater, JJ.; García Sabater, JP.; Maheut, J. (2020). Hybrid approach of discrete event simulation integrated with location search algorithm in a cells assignment problem: a case study. Central European Journal of Operations Research. 28(1):125-142. https://doi.org/10.1007/s10100-018-0548-5S125142281Anjos MF, Vieira MVC (2017) Mathematical optimization approaches for facility layout problems: the state-of-the-art and future research directions. Eur J Oper Res 261(1):1–16. https://doi.org/10.1016/j.ejor.2017.01.049Battini D, Boysen N, Emde S (2013) Just-in-time supermarkets for part supply in the automobile industry. 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Int J Simul Model 15(2):223–235. https://doi.org/10.2507/IJSIMM15(2)3.327Dehghanimohammadabadi M, Keyser TK (2017) Intelligent simulation: integration of SIMIO and MATLAB to deploy decision support systems to simulation environment. Simul Model Pract Theory 71:45–60. https://doi.org/10.1016/j.simpat.2016.08.007Ficko M, Palcic I (2013) Designing a layout using the modified triangle method, and genetic algorithms. Int J Simul Model 12(4):237–251. https://doi.org/10.2507/IJSIMM12(4)3.244Gamberi M, Manzini R, Regattieri A (2009) An new approach for the automatic analysis and control of material handling systems: integrated layout flow analysis (ILFA). Int J Adv Manuf Technol 41(1–2):156–167. https://doi.org/10.1007/s00170-008-1466-9Gould O, Colwill J (2015) A framework for material flow assessment in manufacturing systems. J Ind Prod Eng 32(1):55–66. https://doi.org/10.1080/21681015.2014.1000403Hasda RK, Bhattacharjya RK, Bennis F (2016) Modified genetic algorithms for solving facility layout problems. Int J Interact Des Manuf (IJIDeM) 11(3):1–13. https://doi.org/10.1007/s12008-016-0362-zImran M, Kang C, Hae Lee Y, Zaib J, Aziz H (2017) Cell formation in a cellular manufacturing system using simulation integrated hybrid genetic algorithm. Comput Ind Eng 105:123–135. https://doi.org/10.1016/j.cie.2016.12.028Iqbal M, Hashmi MSJ (2001) Design and analysis of a virtual factory layout. J Mater Process Technol 118(1–3):403–410. https://doi.org/10.1016/S0924-0136(01)00908-6Jainury SM, Ramli R, Ab Rahman MN, Omar A (2014) Integrated Set Parts Supply system in a mixed-model assembly line. Comput Ind Eng 75(1):266–273. https://doi.org/10.1016/j.cie.2014.07.008Kanduc T, Rodic B (2016) Optimisation of machine layout using a force generated graph algorithm and simulated annealing. Int J Simul Model 15(2):275–287. https://doi.org/10.2507/IJSIMM15(2)7.335Kang J (2001) A new trend of parts supply system in Korean automobile industry; the case of the modular production system at Hyundai Motor Company. In: Proceedings of the fifth Russian-Korean international symposium on science and technology, 2001. KORUS '01. IEEE, Tomsk, Russia, Russia. https://doi.org/10.1109/KORUS.2001.975268Kim J, Yu G, Jang YJ (2016) Semiconductor FAB layout design analysis with 300-mm FAB data: “is minimum distance-based layout design best for semiconductor FAB design?”. Comput Ind Eng 99:330–346. https://doi.org/10.1016/j.cie.2016.02.012Krishnan KK, Jithavech I, Liao H (2009) Mitigation of risk in facility layout design for single and multi-period problems. Int J Prod Res 47(21):5911–5940. https://doi.org/10.1080/00207540802175337Ku M-Y, Hu MH, Wang M-J (2011) Simulated annealing based parallel genetic algorithm for facility layout problem. Int J Prod Res 49(6):1801–1812. https://doi.org/10.1080/00207541003645789Kulturel-Konak S (2017) A matheuristic approach for solving the dynamic facility layout a matheuristic approach for problem solving the dynamic facility layout problem. Proc Comput Sci 108(June):1374–1383. https://doi.org/10.1016/j.procs.2017.05.234Leveson N (2004) A new accident model for engineering safer systems. Saf Sci 42(4):237–270. https://doi.org/10.1016/S0925-7535(03)00047-XNegahban A, Smith JS (2014) Simulation for manufacturing system design and operation: literature review and analysis. J Manuf Syst 33(2):241–261. https://doi.org/10.1016/j.jmsy.2013.12.007Prajapat N, Tiwari A (2017) A review of assembly optimisation applications using discrete event simulation. Int J Comput Integr Manuf 30(2–3):215–228. https://doi.org/10.1080/0951192X.2016.1145812Saez-Mas A, Garcia-Sabater JP, Morant-Llorca J (2018) Using 4-layer architecture to simulate product and information flows in manufacturing. Int J Simul Model 17(1):30–41. https://doi.org/10.2507/IJSIMM17(1)408Seebacher G, Winkler H, Oberegger B (2015) In-plant logistics efficiency valuation using discrete event simulation. Int J Simul Model 14:60–70. https://doi.org/10.2507/IJSIMM14(1)6.289Singh RR, Sharma SPK (2006) A review of different approaches to the facility layout problems. Int J Adv Manuf Technol 30(5–6):425–433. https://doi.org/10.1007/s00170-005-0087-9Tompkins J, White J, Bozer Y, Tanchoco J (2003) Facilities planning. Wiley, New YorkTugnoli A, Khan F, Amyotte P, Cozzani V (2008) Safety assessment in plant layout design using indexing approach: implementing inherent safety perspective. Part 1—guideword applicability and method description. J Hazard Mater 160(1):100–109. https://doi.org/10.1016/j.jhazmat.2008.02.089Zhang M, Batta R, Nagi R (2009) Modeling of workflow congestion and optimization of flow routing in a manufacturing/warehouse facility. 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Cuckoo search algorithm for construction site layout planning

A novel metaheuristic optimization algorithm based on cuckoo search algorithm (CSA) is presented to solve the construction site layout planning problem (CSLP). CSLP is a complex optimization problem with various applications, such as plant layout, construction site layout, and computer chip layout. Many researchers have investigated the CSLP by applying many algorithms in an exact or heuristic approach. Although both methods yield a promising result, technically, nature-inspired algorithms demonstrate high achievement in successful percentage. In the last two decades, researchers have been developing a new nature-inspired algorithm for solving different types of optimization problems. The CSA has gained popularity in resolving large and complex issues with promising results compared with other nature-inspired algorithms. However, for solving CSLP, the algorithm based on CSA is still minor. Thus, this study proposed CSA with additional modification in the algorithm mechanism, where the algorithm shows a promising result and can solve CSLP cases.publishedVersionPeer reviewe

Construction Site Layout Planning Using a Simulation-Based Decision Support Tool

Background: Site layout plan is one of the important decisions to be made in the planning phase of each construction project as it can significantly impact on-site transportation, construction logistics and safety. This decision could be complicated due to the uncertainties inherent in construction projects and the complex relationships between the influencing factors and decision variables. Methods: To improve site layout planning, this study aims to develop a simulation-based decision support tool (DST) that enables planners to consider: 1) construction uncertainties, 2) construction resources (i.e., material, equipment and workers), 3) site layout constraints, and 4) mutual impacts between site layout and construction plan variables, for site layout planning of construction projects. Results: The developed DST visualizes the site layout plan within a simulation environment, and provides seamless interactions between the site layout model and the simulation model. These capabilities facilitate planning construction site layout using simulation by establishing two-way information flows between the site layout and simulation components, which can further promote application of simulation in construction site layout planning. Usefulness and practicality of the proposed DST is demonstrated in site layout planning of a steel erection project. Conclusions: Using this DST can reduce some common wastes in construction projects and the cost associated with them, including on-site transportation, material handling and storage, and waiting time for the material arrival

Stochastic Simulation of Construction Methods of Multi-purpose Utility Tunnels

The traditional method of installing underground utilities, which is based on burying them under the roads, has been used for many decades. Repeated excavations related to this method cause many problems, which can significantly increase the actual costs as well as social costs. Multi-purpose Utility Tunnels (MUT) are a good alternative for buried utilities. Although MUTs are more expensive than the traditional method, social cost savings can make them more practical. Different factors should be investigated to determine if MUTs can be an economical and practical alternative. The construction method is one of the most important factors that should be carefully assessed to have a successful MUT project and reduce its impact on the surrounding area. Simulation can be used for investigating the different construction methods of MUTs. In this research, two stochastic discrete event simulation models depicting two MUT construction methods (i.e., microtunneling and cut-and-cover) are developed. The purpose of these models is to analyze the duration and cost of the MUT projects. Also, 4D simulation models of these methods are developed for constructability assessment of these projects. The conclusions of this research are as follows: (1) the duration of C&C method is more sensitive than microtunneling to the changes in tunnel diameter; (2) the cost of microtunneling method is more sensitive than C&C to changes in tunnel diameter; (3) in average, microtunneling is 52% more expensive and 66% faster than C&C; (4) the impact of the microtunneling on the surrounding area is less than the C&C

Parametric freeform-based construction site layout optimization

Traditional approaches to the construction site layout problem have been focused mainly on rectilinear facilities where the importance proximity measures are mainly based on Cartesian distances between the centroids of the facilities. This is a fair abstraction of the problem; however it ignores the fact that many facilities on construction sites assume non-rectilinear shapes that allow for better compaction within tight sites. The main focus of this research is to develop a new approach of modeling site facilities to surpass limitations and inefficiencies of previous models and to ensure a more realistic approach to construction site layout problems. A construction site layout optimization model was developed that can suit both static and dynamic site layouts. The developed model is capable of modeling any rectilinear and non-rectilinear site shapes, especially splines, since it utilizes a parametric modeling software. The model also has the ability to mimic the “dynamic” behavior of the objects’ shapes through the introduction and development of three different algorithms for dynamic shapes; where the geometrical shapes representing site facilities automatically modify their geometrical forms to fit in strict areas on site. Moreover, the model provides different proximity measures and distance measurement techniques rather than the normal centroidal Cartesian distances used in most models. The new proximity measures take into consideration actual movement between the facilities including any passageways or access roads on site. Furthermore, the concept of selective zoning was introduced and a corresponding algorithm was provided; where the concept significantly enhances optimization efficiency by minimizing the number of solutions through selection of pre-determined movement zones on site. Soft constraints for buffer zones around the site facilities were developed as well. The site layout modeling was formulated on commercial parametric modeling tools (Rhino® and Grasshopper®) and the optimization was performed through genetic algorithms. After each of the algorithms was verified and validated, a case study of a real dynamic site layout planning problem was made to validate the comprehensive model combining all of the modules together. Different proximity measures and distance measurement techniques were considered, along with different static and dynamic geometrical shapes for the temporary facilities. The model produced valid near-optimum solutions, a comparison was then made between the layout that is produced with the model and the layout that would have been produced by other models to demonstrate the capabilities and advantages of the produced model

Construction Site-Layout Optimization Considering Workers' Behaviors Around Site Obstacles, Using Agent-Based Simulation

The majority of construction projects, especially large ones, experience time delays, cost overruns, productivity loss, and/or accidents. This is particularly so in case of congested and disorganized sites that contain obstacles that affect workers’ productivity and safety. Effective site layout planning, therefore, is one of the most important project management tasks, and has a significant impact on all aspects of construction, including safety, productivity, site operations, and ultimately time and cost. Site layout planning is a complex process that determines the best location for the needed site facilities (e.g., workshops, storage areas, equipment, etc.) needed to execute the project, so that productivity and safety are optimized. Despite the many simulation and optimization models in the literature for site layout planning, they mostly consider the site location without the low-level details of the workers’ movements within site, particularly around site obstacles. This research aims at developing a construction site-layout planning framework that uses Agent-Based Modelling and Simulation (ABMS) technology to perform a micro-level analysis of workers’ movements and behaviors on site, to study the impact on site productivity and safety. For practicality, this research considers variety of productivity-hindering and safety-hindering obstacles on site. The model also considers two types of workers’ behaviors in their movement around site obstacles: avoider, and aggressive. Given any site layout with any number of resources of different behaviors, the ABMS simulation quantifies the site overall productivity and accident/injury potential. To optimize the site layout, the framework integrates an optimization procedure that determines the optimum site layout that maximizes productivity and safety. A sensitivity analysis is also incorporated to examine the impact of obstacle type and workers’ behavioral characteristics. The results of two case studies prove that the framework is a valuable tool for analyzing and assessing site productivity and safety, and for providing decision support for project managers in establishing site regulations and rewards for positive workers’ behaviors. This research is expected to help construction companies deliver projects with less time and cost, and help to reduce accidents on complex sites

Tag des Baubetriebs 2010 - Tagungsbeiträge "Modellierung von Prozessen zur Fertigung von Unikaten" : Forschungsworkshop zur Simulation von Bauprozessen

Am 25. März 2010 veranstaltete die Professur Baubetrieb und Bauverfahren im Rahmen der jährlich stattfindenden baubetrieblichen Tagungsreihe gemeinsam mit der Arbeitsgruppe „Unikatprozesse“ in der Fachgruppe „Simulation in Produktion und Logistik“ (SPL) im Rahmen der Arbeitsgemeinschaft Simulation – ASIM einen ganztägigen Workshop mit dem Titel: „Modellierung von Prozessen zur Fertigung von Unikaten“. Viele Bauprozesse sind dadurch gekennzeichnet, dass sie Unikatcharakter besitzen. Unikate sind durch prototypische Einmaligkeit, Individualität, vielfältige Randbedingungen, einen geringen Grad an Standardisierung und Wiederholungen gekennzeichnet. Das erschwert die realitätsnahe Modellierung zur Simulation sogenannter Unikatprozesse. Dieser Besonderheit widmet sich die überwiegende Zahl der Tagungsbeiträge, die in diesem Band widergegeben sind