Digital Twin – A Tool for Project Management in Manufacturing

Characterization of the information system integrated to the construction project management systems

“…Digital tools in the field of project management are useful to optimize the development of the line of work [ 19 , 20 ] and allow characterizing it within the so-called industry 4.0 [ 21 ]. The use of technological equipment contributes to minimizing errors, increasing speed and accuracy, if they are properly used [ 8 , 22 ]. The evolution of information systems has implemented simulation techniques that contribute to significantly reduce constructions’ errors from their initial design phases [ 23 ].…”

“…However, it is certainly idealized for use in every phase of the project life cycle. This methodology contributes to the improvement of information processing, better communication flow [ 11 ], data interoperability throughout the work team, and provides the opportunity to have a common language available to all at any time; allows being aware of project changes in real time and performing verifications before implementation, whether it is convenient or not, according to its principle of inference detection [ 22 ]; and also contributes to improve the sustainability of the project [ 33 , 34 ]. The methodology is used in a very limited way [ 35 ].…”

“…LC is a philosophy that promotes the reduction of waste such as rework, unnecessary movements, duplication of operations [ 38 ], and contributes to promote collaborative work [ 39 ]. Thus, it saves time and costs [ 22 ]. It's a philosophy that seeks to increase value in the processes for the customer [ 11 , 40 ], among its tools there are: Just in Time, Kanban, Last Planner System, value stream, integrated delivery of projects.…”

Joint Offering Evaluation Framework for Assessing the Feasibility and Business Value of a Digital Twin Use Case

“…[60][61][62][63] These viewpoints should be considered to select proper methods and tools to serve the challenge of industrial business on the selected level, for example, for operations on the factory floor, 64 sustainability assessment, 63 supply chain management, 60,61 or project management. 65 Thus, the engineering of a useful DT requires a combination of competences as well as implementation skills. DT always are connecting engineering knowledge to business knowledge via enabling technologies such as IT, IoT, data analytics, AI, AR, VT, blockchains, cloud-edge collaboration, etc.…”

“…There are several design viewpoints to consider while engineering a DT such as (i) the time frame: history, on‐line, real‐time or forecast, (ii) the foundation of the model: physics, data or hybrid, (iii) the purpose: monitoring, controlling, simulation, optimization or prediction, (iv) intelligence: descriptive, diagnostic, predictive or prescriptive analytics, (v) user interface: dashboard, 2D or 3D visualization, augmented or virtual reality or even metaverse, (vi) the object: a product, an assembled product, a machine, a set of machines or a process, (vi) the life cycle phase of the object, (vii) model generation method: manual or automated, and (viii) the end user: manager, operator, maintenance etc., to mention few 60–63 . These viewpoints should be considered to select proper methods and tools to serve the challenge of industrial business on the selected level, for example, for operations on the factory floor, 64 sustainability assessment, 63 supply chain management, 60,61 or project management 65 . Thus, the engineering of a useful DT requires a combination of competences as well as implementation skills.…”