Digital twin | EPFL Graph Search

A digital twin is a digital representation of an intended or actual real-world physical product, system, or process (a physical twin) that serves as the effectively indistinguishable digital counterpart of it for practical purposes, such as simulation, integration, testing, monitoring, and maintenance. The digital twin has been intended from its initial introduction to be the underlying premise for Product Lifecycle Management and exists throughout the entire lifecycle (create, build, operate/support, and dispose) of the physical entity it represents. Since information is granular, the digital twin representation is determined by the value-based use cases it is created to implement. The digital twin can and does often exist before there is a physical entity. The use of a digital twin in the creation phase allows the intended entity's entire lifecycle to be modeled and simulated. A digital twin of an existing entity may be used in real-time and regularly synchronized with the correspon

A generic methodology and a digital twin for zero defect manufacturing (ZDM) performance mapping towards design for ZDM

Foivos Psarommatis Giannakopoulos

Over recent years, the manufacturing industry has seen constant growth and change. From one side, it has been affected by the fourth industrial revolution (Industry 4.0). From the other side, it has had to enhance its ability to meet higher customer expectations, such as producing more customized products in a shorter time. In the contemporary competitive market of manufacturing, quality is a criterion of primary importance for winning market share. Quality improvement must be coupled with a concern for high performance. One of the most promising concepts for quality control and improvement is called zero defect manufacturing (ZDM), which utilizes the benefits of Industry 4.0 technologies. ZDM imposes the rule that any event in the production process should have a counter-action to mitigate it. In light of this, the current research developed a methodology the manufacturer can use to correctly select or design appropriate ZDM strategies and equipment to implement at each manufacturing stage. This methodology consists of several steps. The first step is to conduct several simulations using a dynamic scheduling tool with specific data sets to develop a digital twin (DT). The data sets are created using the Taguchi design of experiments methodology. The DT model is created for use in predicting the results of the developed scheduling tool without actually using said tool. Using the DT, multiple ZDM parameter-combination sets can be created and plugged into the model. This process generates ZDM performance maps that show the effect of each ZDM strategy at each manufacturing stage under different control parameters. These maps are intended to provide information for comparing different ZDM-oriented equipment to help manufacturers reach a final decision on correct and efficient ZDM implementation or to assist in the design phase of a ZDM strategy implementation.

2021

A dynamic scheduling tool and a methodology for creating digital twin of manufacturing systems for achieving Zero Defect Manufacturing

Foivos Psarommatis Giannakopoulos

Nowadays manufacturing environment is highly volatile and rapidly changing as the need of products is increasing exponentially, due to the fact that Product Life Cycle is shortened and therefore more products are required to be manufactured or remanufactured. On top of that, these production requirements have "created" the need for more efficient, productive and eco-friendly planning and scheduling. For that purpose manufactures have started adopting the Zero Defect Manufacturing (ZDM) paradigm which has a goal of eliminating defected parts and therefore achieving higher efficiency, eco-friendliness and lower production costs. There are four ZDM strategies that are interconnected with each other: detection, repair, prediction and prevention. The current research work focus on the development of a dynamic Scheduling tool combined with an intelligent Decision Support System (DSS) that takes into consideration the ZDM strategies for eliminating defected parts during production. The purpose of creating this type of tool is twofold: a) provide to the manufacturers a scheduling tool that operates based on the ZDM objectives and b) use the tool for creating a map based on product manufacturing properties for choosing the right and most efficient ZDM strategies at the right production stage. Finally, in order for the tool to implement the ZDM concept, it will include algorithms that can predict when a defect will occur in order to prevent it.

EPFL2021

A generic methodology and a digital twin for zero defect manufacturing (ZDM) performance mapping towards design for ZDM

Foivos Psarommatis Giannakopoulos

2021