Modeling the World
The interconnected nature of today’s economy continuously brings disruptions to traditional business models. For this reason it’s wise to keep an eye on tech development. After all, it’s technology that was named the main determinant of humanity’s future welfare.
In the previous entry we looked at the issue of digital transformation and its defining aspect – the use of computer modeling to enhance our business operations. The more and better data available, the more precisely we can model something, which in turn allows us to predict the way things will change or behave in future.
Over the past decade machine learning and artificial intelligence developments as well as real time access to IoT sensors have raised computer modeling to the next level, allowing us to model not only theoretically, but iteratively. By using the talents of data science on information flowing from the sensors, we can create what’s known as digital twins – real-time replicas of what exist in reality.
A digital twin is a dynamic software model of physical assets, processes, people, places, systems, or devices, which uses physics data on how the components of the entity operate, respond to and interact with the environment. Data, bridging the real and digital world, is transferred flawlessly, allowing the virtual model to exist simultaneously with the physical entity. Thanks to the fast expanding body of data, such models can be continuously updated, allowing for more extended analyses.
Next Generation Computer Modeling
Digital twins’ usage varies from analyses and simulation of real world conditions, responding to changes, efficiency assessment, design, to maintenance, and many other applications, and there’s potential for literally billions of things to be represented by their digital twins. As a result of this, the use of digital twins is increasingly becoming a business imperative in many industries, as in case of the automotive industry, where they allow to design a product, simulate it and be able to test and validate its capabilities before the physical prototype of the product is built. All this to enable efficiency increases in manufacturing process and daily operations. At this point, the technology behind digital twins has expanded to include buildings, aircraft engines, container ships, and cities. One of the more ambitious plans with the use of this technology is The UK government’s plan to create a digital twin of its entire national infrastructure to prepare for future challenges.
One of the projects where we have implemented the digital twin concept is a delivery optimization system, designed to determine the most cost-effective routes, named Deliver-M8. It’s a software intended for fleet operations optimization in two structurally analogous sub-areas of the TSL sector: first and last mile delivery (FMD & LMD).
A demo version showing how the system works is available as a public site: deliverM8.com, where you can register and enter information on your organization’s logistics assets, such as: vehicle fleet, drivers and their working times, type of cargo, number of warehouses and their capacity, as well as customers’ availability, maximum time delay, and other variables, key for your operations. At your request the system will generate the most optimal delivery routes along with time schedules for your drivers within the time limits you set for it. Thanks to our API this information can be easily integrated with your other systems.
Say you are a dispatcher at a parcel warehouse with packages of different sizes and weights addressed to various locations in the city. You have a number of drivers working different shifts, and a number of vehicles at your disposal, plus a lot of places to visit. This and other input data is processed by the system, which offers the possibility of defining such constraints as the time window each recipient is available for delivery, the maximum delay time, and many other. Deliver-M8 assigns appropriate trucks to the drivers and plans the loading of packages in each car in the correct order. By clicking “Calculate plan” you can generate an optimal route for each driver.
Routes for individual trucks are divided on the map by color, you also see the drivers’ schedules broken down by hours. You can send the plan to each driver via email or a text message with a link. There’s a smartphone application that the driver can install as well, which asks them for their location, and shows them on the real-time web dashboard for dispatchers as a truck icon. The location is refreshed while driving, allowing you, the dispatcher, to see where the cars are at all times.
Our proprietary version of optimization algorithms implemented in Deliver-M8 allowed us to offer a very unique feature, i.e. dynamic balancing, which enables decisions to be made in real time in response to a logistics crisis. Upon clicking on the link they received from the dispatcher, the driver sees all their delivery addresses in a chronological order. At any point during the workday they are able to send feedback to the system using the application, noting visited addresses and unavailable customers, or postponement in the delivery.
Deliver-M8 allows you to compare the feedback data with the original plan and detect if the registered disruptions threaten to change its outcome in real time. You can modify the plan at any point, including while the drivers are on the road. If you decide to change the original plan, the system generates a new one, taking into account real-time traffic information for which it queries external websites, as well as sends a new schedule to the drivers.
The above are examples of a broad range of Deliver-M8’s features, which go beyond the basics of route planning. Deliver-M8 is available for the FMD/LMD sector in a Software as a Service (SaaS) model, allowing for tests at an inexpensive cost and implementation either as a SaaS software with minor modifications, or as an in-house solution. To find out more about Deliver-M8 you can contact us at firstname.lastname@example.org.
Advanced Developments Possible
The digital twin concept is one of many new technologies changing the current business landscape. Applied to route optimization and paired with high-end machine learning algorithms it transfers into a powerful logistical tool, having potential to save your business time and money. As mentioned before, it is received with open arms far and wide – from the medical and insurance to security industries. As the concept is inseparably linked with IoT, endless influx of data will ensure its further deployment, and continuous advance of artificial intelligence and machine learning will safeguard more and more diverse appliances of digital twins in future.
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