Adaptive Simulation-Based Concept for Construction Logistics

2011

Logistic processes have a large impact on the planning and execution of large-scale or inner-city construction projects. A common way to analyze different logistic scenarios is the application of discrete-event simulation in order to proof the feasibility of time schedules and identify bottlenecks. The data preparation is one of the main challenges during the simulation of construction logistic processes because of the unique characteristics. Especially, in early planning phases only elemental information about activities, deliveries, and resources are available. In this paper an innovative concept to extract and prepare input data for logistics simulation in early planning phases is presented. The so-called Mefisto container is used to integrate essential project data. In the next step, the project data is analyzed and prepared by an additional software tool, the so-called SiteSimEditor. Based on the extracted and prepared data a simulation model can be generated by using configura...

This paper addresses the problem of manufacturing systems and their associated sub-assemblies and/or raw materials. A manufacturing system is a set of policies that monitors and controls finished products and raw materials. It determines how much of each item should be manufactured or be kept in warehouses, when low items should be replenished, and how many items should be assembled or be ordered when replenishment is needed. Practical manufacturing systems rarely optimize or even represent very precise descriptions of realistic situations. The art of model design is to develop commonsense approximations that give enough information to facilitate managerial decision making. A system with a high degree of intelligence is more robust and able to perform better performance in terms of lower cost and higher efficiency. The integration concept of manufacturing processing has enjoyed increased popularity among researchers and manufacturers. Integrated manufacturing system is a set of mathematical models and policies that monitors and controls raw items, subassemblies, and finished products. Although such systems provide a better utilization of resources they have a number of drawbacks due to the complexity of real-world problems. Using intelligent simulation techniques will lead to better automated systems. The framework allows the complex simulation model to be manageable for the purpose of adaptation to the changing environment variables. Moreover, the framework employs a material handling request-driven approach in order to implement both push and pull flows of production loads. The framework performed a steady state simulation to furnish top management with a clear understanding of the cost associated with warm up period. The steady state simulation also provides top managements with clear picture of how to make their production line more efficient in terms of profits as well as enabling to remove any processes that are overly complicated.

2021 Winter Simulation Conference (WSC), 2021

Building construction is a one-of-a kind production with complexity caused by interdependencies between logistical-and construction-operation processes. Especially the finishing phase involves numerous trades who install a wide variety of materials and have to share logistical resources. Traditional planning approaches based on analytical tools and experience gained from historical data fall short in providing the support needed to evaluate different logistical strategies. Therefore, the present work aims at developing a user-friendly simulation model that considers both material supply and waste removal through a third-party logistics partner (TPLP). The process interdependencies are investigated using data from a real hotel building project. A kitting solution is evaluated as an alternative, using consolidation centers to reduce material handling on site. Comparing the supply-and reverse logistics of these alternatives, kitting appears to be more costly however the model does not capture potential improvements in performance of construction operations and coordination of processes.

Computers & Industrial Engineering, 1989

2016

Multidisciplinary Aspects of Production Engineering

Optimization of production logistics processes through the use of simulation tools brings a lot of benefits to a production company, and thus significantly reduces production costs. Increasing competition resulting from the use of production automation to increase productivity has increased the complexity of production systems that can only be analysed by simulation. Production logistics performs management functions such as planning, motivating, organising and controlling. It does not deal with technological processes, but the organisation of physical delivery and displacement of components and information in the system. An important feature of production logistics is combining supply logistics with distribution logistics. If the production logistics is properly organised, it provides access to all materials and components of a given product during the implementation of a specific order. Simulation tools ensure continuity and rhythm of production after it is started, as well as con...

Zeszyty Naukowe Politechniki Częstochowskiej Zarządzanie, 2019

The article presents the concept of modern simulation systems applicable in the analysis of the logistics chain configuration. The main goal of the article is to present advanced possibilities of using various methods of simulation of a logistic system, or to determine the appropriateness of introducing changes in the configuration of a logistics chain or the assessment of already prepared solutions for given logistics processes. The article contains a description of information technologies that can be used in simulation, including specialized simulation programs, spreadsheets, languages and simulation interfaces etc. The article presents the basic issues related to the creation of a logistics project simulation, as well as the possibilities of the FlexSim 3D Simulation software, which easily allows to map complex logistic processes. The simulation, including the data generated during its implementation on individual logistic processes, allows the selection of the most advantageous and optimization of the solutions used so far in a given process. The article presents an example of simulation of logistics issues in the production process and examples are presented to explain the cognitive appeal of this method based on the use of computer technology and FlexSim 3D Simulation software.

2013

The following paper describes the use of simulation models to analyze a common production scenario in manufacturing plants: many assembly lines producing specific families of items in a large variety of versions; following handling and transport system, evaluated to be effective, costless, with an adequate capacity to be not the bottleneck of the whole system, and integrated with a storage/sorting system to decoupling the assembly phase and the following ones as completion/test and expedition phase, included recovery and reform of the expedition lot. To analyze a system like this, a simulation model has been developed with a flexible AGVs transport system, a Transit Point Warehouse acted by AS/RS, used also as sorting media. The size of the warehouse incoming bay, number of warehouse sub allocation zones or aisles, the capacity of all queues, all control logics for AGV’s have been evaluated in a pre-modeling phase, and then evaluated by the model.

Applied Computer Science, 2012

This paper deals with computer simulation of manufacturing systems. It contains the basic simulation theory and principles of a simulation project management. Furthermore the authors introduced the idea of parametric simulation model, followed by special application areas of simulation, e.g. scheduling, emulation, metamodelling. The paper discusses the possibility to utilize a cloud computing technology in simulation. The case example of the application of simulation by the optimization of real production system concludes the working part of paper. The final part summarizes benefits and recommendations.