The Digital Twin (DT) concept has rapidly gained acceptance. More recently it has become clear that just as a DTs support product, they can also represent the activities needed to design, execute, and manage projects. DTs bring a remarkable potential to bring complex projects to market successfully and to support after-market phases including training, maintenance, repair and retirement.
Project Design is a method that brings DTs to project management based on realistic and reliable project models, forecasts, and ongoing instrumentation. In Project Design, the digital twin represents not only the products, services, and processes being created, but also the project teams and their activities. In other words, the project itself is recognized as a system. Digital models are extended to include people and organization in addition to product and process. Feedback and feedforward with automated flows are a critical characteristic of DTs leading to better attention, decisions, and actions by teams. Three cases are shown which demonstrate Project Design with digital models, digital projections, and digital shadows of complex projects.
These cases show a collaborative environment in which teams build models which capture the project as a sociotechnical system. The models integrate three fundamental contributing architectures: products, processes, and organization (PPO). While building the model, a view emerges of the relationships amongst these three which, in turn, promotes shared awareness of the project across teams. The model-building likewise shapes mental models as teams explore the impact of changes, variation in assumptions, architectural options, and other real-world execution parameters.
An analytics engine, in this case an agent-based simulator, generates project forecasts which act as digital projections. The forecasts are more realistic than classic methods, as the simulations include the project’s uncertain demands, behaviors, feasibility, and coordination in dynamic interaction. A wide range of feasible project variants with schedules, costs, quality, and utilization are generated by simulation and compared to targets. Teams rapidly assess trade-offs, risks, what-if scenarios and contingencies. The model is adjusted: teams expanded or reduced, dependencies changed, activities added or removed, roles and responsibilities tuned, concurrency increased, worksites changed, etc. The project teams learn quickly how changes in their own roles, commitments, and priorities systemically impact the project results. As the project proceeds, estimates to completion including alternate paths forward are rapidly and easily analyzed.
A long-lasting benefit of Project Design is that the DT is used over the project lifetime. A digital shadow evolves with the actual project as refinements and contingencies arise, immediately yielding new forecasts of quality, schedule and cost. Instrumentation of scope, interfaces, and teamwork brings significant new feedback to maintain alignment of the project model with the actual project. The model also acts as digital thread across the model’s connected PPO and across changes in the project over time, promoting persistence for practical leverage of information in future projects.
Recent research advances in instrumentation and analytics, including placement of non-intrusive sensors across project elements and teamwork, rapidly reveal the health of the project and chances for success. Taking advantage of these techniques, new insights are yielded on teamwork as innovation and complex problem-solving across various industrial and government project domains.
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Interestingly, research in manufacturing and HCI have shown repeatedly that over-automation of a sociotechnical system in dynamic environments can lead to decreased performance. Human attention withers, learning slows, and quality drops.