What is the Advantage and Disadvantage of Simulation Lawn Manufacturer

Digital twin technology has been growing in popularity within the engineering and IT community over the past several years. The concept originated in the early s, but today, digital twin is one of the most talked about and innovative forms of emerging technology.

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Digital twins are digitized representations of real-life objects, systems, and/or processes. They can provide significant insight on how something will perform if implemented in the physical world. Using real time data and simulation, digital twin technology follows a product or system throughout its lifecycle and supports engineers in making informed decisions about the physical parts and systems it represents.

Digital Twin Pros

Digital twins can benefit the engineering industry greatly as they have the capacity to better future parts and systems, expedite time to market, store knowledge, and better connect information.

Forward-Thinking Technology

Digital twin is a forward-thinking technology and creates the ability for high-speed change down the road. Having a body of data that represents a real-world object or process is helpful as it can better inform engineers when designing future parts and systems. A digital twin can provide valuable insight into current state operation, but it really elevates engineering practice when it&#;s used to predict future scenarios or iterate design possibilities without doing a physical build.

Faster Development

Along with creating the ability for high-speed change, digital twin technology generates faster development, prototyping, and testing processes. Once digital twins have been created and are on file, engineers can reference that information when starting new projects as opposed to starting from scratch. Having a library of reference models readily available can act as a huge time save.

Codifies Tacit Knowledge

Digital twin technology can act as a more complete archive for easily lost knowledge. Every year, valuable information is lost as people retire and leave the workforce. When tacit knowledge is forgotten, it makes design and manufacturing processes more difficult and time consuming as engineers are forced to build projects from the ground up and relearn from experience.

Complete modeling of system interactions and usage scenarios within a digital twin construct can be a more thorough and sophisticated method for documenting knowledge and insights from previous projects. Engineers will have the ability to store valuable information within digital twins that can be tracked, traced, and referenced by others at later times.

Better Connects Information

Delivering a digital twin requires a complete connection between engineering processes and information. Actions or documentation that live outside of the raw engineering data or Product Lifecycle Management (PLM) system can become disconnected from the bigger picture. This often happens to data created in early project phases. The process of building an accurate digital twin demands that these data sets be connected to the rest of the system, and that any changes to these data sets drive corresponding changes throughout the rest of the system.

When implemented properly, the digital twin will inform the engineer of relevant information outside of the PLM system and automatically flow down the changes and implications of that information to the rest of the system.

Digital Twin Cons

While digital twins can offer worthwhile advantages, there are challenges to getting the technology off the ground and managing it through lifecycle phases.

Digital Infrastructure

One of the biggest challenges associated with digital twins has to do with the digital infrastructure that is required. For digital twin technology to work, a model based environment is needed. This can be a tough obstacle to overcome as interoperable assets are complex. If an organization is not already operating in a digital environment, they will need to create one.

To create an ecosystem for digital twins to thrive in, an organization needs a fully integrated software environment. This is important because all software must work in sync, and data must easily transfer throughout the systems that manage the digital twin&#;s lifecycle.

Creating the right environment is difficult. Most companies operate using a patchwork of software and tools that were not designed to be fully compatible. It is possible to create these integrations, but it takes time and resources.

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Maintenance

Once a digital twin is created, it must be maintained. Over the course of a lifecycle, physical objects will deviate from their digital twin due to several factors such as operating conditions, age, wear and tear, etc. If the digital twin is not maintained and able to keep up with changes that occur within the physical version, it will no longer be an accurate representation of the physical asset, and the overall purpose of the digital twin is defeated.

It is difficult to maintain a digital asset. Many digital twin efforts fail because the digital assets don&#;t receive the same maintenance effort as the physical ones. The digital twin requires consistent upkeep, significant observation, and time to document all real-time changes. If done properly, the digital twin should provide insight into the effects of operating conditions before the physical twin experiences them.

Are Multiple Digital Twins Needed?

When creating a digital twin for an object, one consideration that must be made is if a digital twin is needed for every configuration or serial number. To determine if one or multiple digital twins will be needed, engineers must decide how much detail and information they want back from the physical object to feed into the digital asset.

Take a lawn mower for an example. While it&#;s safe to assume each person who owns the same lawn mower uses it to cut grass, there will likely be differences in the way the mower is used from one person to another. Those differences could include variation in climate/weather conditions, time increments the mower is run, etc. It is important to account for the differences because they could impact how the object deviates from the digital twin overtime.

Engineers must determine how to account for the differences in how each individual product is used. While it is unrealistic to create and manage digital twins for every product configuration, engineers may be able to meet in the middle and create digital twins for specific climates that account for environmental and operating conditions.

Do the Pros Outweigh the Cons?

Digital twin technology is currently a fantasy to some degree as the benefits are not truly understood within the engineering industry because digital twin technology has not been widely implemented at a high level. The most successful cases of the technology are when the digital asset is created first and the physical twin is derived after. Engineers are working to figure out how to connect all the dots and overcome obstacles to make the technology work as well as it can. It is likely that there is a lot of untapped potential and huge advantages to digital twin that have not been discovered yet.

Right now, the cons to digital twin make the technology tough to implement at full capacity. However, if an organization can overcome the obstacles, they will greatly benefit. To learn more about digital twin technology and how it can benefit your organization click here.

E. Zankoul, H. Khoury and R. Awwad.

ABSTRACT

One of the most common operations to any construction project is earthwork. In fact, most, if not all, construction projects begin with earthwork activities. These activities require heavy equipment, are generally quite costly and consume a considerable amount of time. On another hand, the construction industry is becoming increasingly competitive over the years, whereby the need to continuously find ways to improve construction performance. In order to address the aforementioned adversities, this paper takes the initial steps and presents work targeted at efficiently managing logistics of earthwork operations in the construction field, namely cut and fill processes, and hauling activities. This dynamic and complex problem, which entails a lot of parameters and variables, is addressed in detail through creating two simulation models, a Discrete-Event Simulation (DES) model and an Agent-Based Simulation (ABS) one, using the multi-method simulation software AnyLogic 7.1. The purpose behind this study is twofold: (1) capturing and visualizing the interaction among the different resources or entities in an earthmoving operation and defining the weak links in order to improve the efficiency of such activities onsite, and (2) comparing DES and ABS approaches and evaluating the advantages and drawbacks of each when modeling earthmoving operations. Results of both approaches are presented and analyzed with regard to improving performance of earthmoving operations, followed by a discussion of the application and effectiveness of using each of the presented simulation approaches in modeling construction activities.

Introducrion

Information Computer Technology (ICT) tools have been increasingly developing which is enhancing their use in the field of construction. For instance, simulation modeling and visualization are often used at the stage of planning to improve construction performance and efficiency. Different types of simulation approaches have been used to mimic construction operations among which Discrete Event Simulation (DES) ranks as the most widely used one. A newer simulation approach, Agent Based Modeling (ABM), emerged later in the s. In construction, one of the most common and expensive activities to any project is earthwork operations, which explains the necessity of simulating and analyzing such processes which provides insight to achieve cost savings and higher operation efficiency.

Previous research efforts aimed at comparing DES and ABM in different fields such as Operations Research and the implementation of new management policies. These studies conclude that each simulation modeling type has its advantages and its disadvantages and selecting a type should depend on the problem and scenario modeled [1] [2] [3]. Other studies have focused on modeling earthwork operations using DES approach [4] [5]. As for ABM, although it is still not widely used in construction, some papers used it to study construction labor productivity on site [6], to estimate the productivity of bored piles [7], or even to model earthmoving operations [8]. However, in the case of the latter, the model focused mainly on managing logistics, spatial time clashes and safety.

In this paper, two models are created to simulate earthwork operations, one following the discrete-event method and the other using ABM approach. The two models are accompanied with a 3D animation for validation purposes and are tested on a case study to compare the results. Then, the advantages and disadvantages of each simulation approach are highlighted with respect to earthwork operations. Finally, the potential of combining both approaches into a multi-method model is discussed.

Figure 1: Case Study Road Network Layout

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