Following the activities that SMILE-DIH is conducting in assisting companies (SMEs and Midcaps), under the two calls relating to the European Change2Twin, we can record the achievable objectives considered more or less relevant by candidates who aim to adopt a Digital Twin, as a tool capable of rapidly increasing business ambitions.
Below is a list of the purposes for which the companies involved are thinking of adopting it, with the opinion expressed alongside (very relevant, relevant and meno less relevant than the others) to be interpreted as a priority for implementation in the short term.
Virtual design (less relevant)
Model-based systems engineering, including analysis and design, ensures that product and process requirements are met as it allows for high degrees of seamless integration, testing, verification and validation. The Design Twin concept offers simulation as a tool to be used during design to generate data that will further improve the product design process. Furthermore, thanks to rapid prototyping, by running the design in an operational context, errors in the prototype can be detected early. But the maximum perceived value of virtual design is obtained from “parametric design” which allows the generation of projects based on parameters instead of having to necessarily create them all over again.
Keywords: Total Cost of Ownership (TCO of own assets) and Diversity of the product / service portfolio
Customer involvement (very relevant)
An interactive view of the system and its capabilities allows customers to understand how a product / solution can meet their needs and how it is used. In the phases of promotion, marketing, pre-sale it is possible to have a visual model of the product so that potential customers can see the result obtained in advance. In the customer engagement stage, you can allow them to modify the model and see how this affects costs, performance, etc. In the Make2Order phase it is possible to allow him to directly govern the steps, such as: 1) create his own model, 2) immediately check what he will get and at what price, 3) allow him to execute a job and immediately trigger the production process.
Keywords: Increase in market shares and Customer satisfaction
Virtual production (less relevant)
The verification of the on-site implementation of a production system, compared to its design carried out in the digital twin, usually allows to detect faults or anomalies only at the time of commissioning. But simulation can even allow for virtual commissioning where the correct settings can be discovered before the machine is fully installed at the customer. It is also possible to virtually identify unsuitable parts or parts that, as often happens in real situations, can be installed incorrectly.
Keyword: First Time Yield (FTY)
Engineering feedback (less relevant)
The Digital Twin can acquire the characteristics of use to inform the engineering / design / technical office of the need to change designs, or how to change the design technique, or highlight operational risks. Process engineering simulation allows modeling of the process and its relevant key parameters in order to see in advance how the process can be improved. The concept of Process Insights combined with that of Data Science allows you to exploit the analysis to discover new mechanisms in the current process.
Keyword: First Time Yield (FTY)
Monitoring (relevant)
The monitoring of the operation of a system by the digital twin allows, for example, to detect anomalies, performance degradation, etc. Anomaly detection is achieved by comparing the model output to the actual output of the real device. Any discrepancies may indicate that something non-compliant is happening. This determines the overall effectiveness of the equipment / equipment (OEE) and an overview of all equipment and related indicators.
Keywords:Total Cost of Ownership (TCO of own assets) and Overall effectiveness of the equipment (OEE)
Optimization and quality improvement (very relevant)
Performing the process control phases with a digital twin allows you to optimize the operations of a system, significantly gaining in terms of performance and efficiency. There are at least ten functionalities that can be implemented with a Digital Twin: 1) process mining, capable of generating actual processes by analyzing data and comparing them with official processes; 2) a new way of managing the preparation of work / orders, generating work instructions instead of designing them manually; 3) the generation of machine instructions automatically instead of creating them manually; 4) the adoption of optimization strategies that use models / simulations to discover new or unusual ones; 5) the improvement of coordination in the management of the plant, maintaining control and understanding which improvements to apply in specific situations; 6) the possibility of correctly predicting the right materials / settings / instructions / programming to be used to create a new product right from the start; 7) the possibility of dynamically adopting solutions and / or settings to be able to change approach in real time according to the situation of the product / machine / material; 8) the possibility of producing in a modular way, such as, for example, being able to change only the tool to a machine without having to completely reprogram it to produce two different objects; 9) the possibility of controlling the quality of products with the “zero defects” method is obtained from a virtual and predictive model capable of adapting the process control to guarantee the quality to be obtained; 10) the possibility of offering support to the operator, thanks to the use of models and simulations designed to generate instructions so that the person in charge of processing can make the best use of the machine.
Keywords: Return / reject rate and productivity, Replacement time, Overall effectiveness of the equipment (OEE)
Programming (very relevant)
Being able to organize workflows based on actual data and insights provided by the digital twin means planning with the help of a model that can predict how long it takes to finish each activity, optimizing the order of activities in time to maximize the amount of activities performed.
Keyword: Throughput
Diagnosis (very relevant)
The investigation of the cause or nature of a fault condition, situation or problem in the physical system can be facilitated by reasoning on the data collected and sent in real time within the digital twin. This will make it easier to identify if and when faults occur and how to diagnose them as it gains greater speed in identifying the causes. In the case of multiple machines for parallel production, a comparison can be obtained between the various machines to establish which of them are performing better than others.
Keywords:Total Cost of Ownership (TCO of own assets), Overall effectiveness of the equipment (OEE), Downtime due to maintenance (MTBF/MTTR/MDT), Response time
Preventive maintenance (very relevant)
Physical system maintenance and servicing can also be inferred and displayed in the digital twin to reduce the likelihood of failure based on the observed system state. We talk about predictive maintenance when there is a virtual model that allows you to evaluate a certain state in real time and able to indicate when the level of operation may fall below the predetermined minimum and capable of indicating which measures must be taken to restore. the correct level of operation.
Keywords: Total Cost of Ownership (TCO at the customer), Overall effectiveness of the equipment (OEE), Downtime due to maintenance (MTBF/MTTR/MDT), Response time
Smart logistics (very relevant)
Logistics processes can be visualized in a digital twin, which can then be adapted to the data in real time according to different needs and options. Having a virtual twin of the supply chain allows to model its behavior and makes predictions possible according to market behavior and / or associated risks. In the logistics field, it is useful to have a model that helps to plan how materials or products are to be transported in and out of the factory. Knowing the capabilities of the different machines and / or other factories in the production chain, with the Digital Twin it is possible to generate automated plans to understand which parts of the production process should be carried out (by whom or where). Even the preparation of the factory layout can be a virtual model, in order to better plan changes, better position the work islands and optimize supplies.
Keywords: Profitability (such as gross profit margin), Return on investment, Throughput
Intelligent systems (relevant)
The Digital Twin can allow systems to dynamically adapt to their environment, state or activity and potentially learn how to best do it. The digital twin is therefore a key part of system control. In this way it will be possible to introduce concepts such as: 1) servitization, which consists of proposing / selling a product as a service, ie placing on the market an intelligent device capable of reporting on itself; 2) propose a twin of the device, i.e. sell the twin together with the product to allow the customer to use the model for their own specific purposes; 3) propose a twin of the material and that is to sell information together with the material (such as quality information) to allow the user to better apply the material in his specific process.
Keywords: New services (sale of additional services based on the product twin), Change business model, Profitability