Towards prescriptive maintenance with digital triplet

Prescriptive maintenance is critical for product or asset life cycle management in the circular economy. Unlike predictive maintenance, it can forecast future conditions or statuses and recommend or offer a specific solution. While digital twins have found their applications in predictive maintenance, digital triplets, the next generation of digital twins, will contribute to prescriptive maintenance. Digital triplets enable decision-making with generative and explainable AI to interrogate the digital twin data, including more situation information and optimized outcomes under different scenarios. This paper proposes digital triplets for prescriptive maintenance and identifies the technical challenges and opportunities for implementation. This paper also describes and discusses future research directions for digital triplets.