With the advent of new generation information technologies in industry and product design, the big data-driven product design era has arrived. However, the big data-driven product design mainly places emphasis on the analysis of physical data rather than the virtual models, in other words, the convergence between product physical and virtual space is usually absent. Digital twin, a new emerging and fast growing technology which connects the physical and virtual world, has attracted much attention worldwide recently. This paper presents a new method for product design based on the digital twin approach. The development of product design is briefly introduced first. The framework of digital twin-driven product design (DTPD) is then proposed and analysed. A case is presented to illustrate the application of the proposed DTPD method.

Poor deep tumor penetration and incomplete intracellular drug release remain challenges for antitumor nanomedicine application in clinical settings. Herein, a nanomedicine (RLPA‐NPs) is developed that can achieve prolonged blood circulation, deep tumor penetration, active‐targeting of cancer cells, endosome/lysosome escape, and intracellular selectivity self‐amplified drug release for effective drug delivery. The RLPA‐NPs are constructed by encapsulation of a pH‐sensitive polymer octadecylamine‐poly(aspartate‐1‐(3‐aminopropyl) imidazole) (OA‐P(Asp‐API)) and a ROS‐generation agent, β‐Lapachone (Lap), in micelles assembled by the tumor‐penetration peptide internalizing RGD (iRGD)‐modified ROS‐responsive paclitaxel (PTX)‐prodrug. iRGD could promote RLPA‐NPs penetration into deep tumor tissue, and specific targeting to cancer cells. After internalization by cancer cells through receptor‐mediated endocytosis, OA‐P(Asp‐API) can rapidly protonate in the endosome's acidic environment, resulting in RLPA‐NPs escape from the endosome through the “proton sponge effect”. At the same time, the RLPA‐NPs micelle disassembles, releasing Lap and PTX‐prodrug. Subsequently, the released Lap could generate ROS, consequently amplifying and accelerating PTX release to kill tumor cells. The in vitro and in vivo studies demonstrated that RLPA‐NPs can significantly improve the therapeutic effect compared to control groups. Therefore, RLPA‐NPs are a promising nanoplatform for overcoming multiple physiological and pathological barriers to enhance drug delivery.

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Automation, driven by informatics, enables manufacturing companies to increase productivity and meet market demands for cost-effective and high-quality products. However, many manufacturing operations across industry verticals continue to be manual even today. One such example is the manual assembly of the final trim and wheels in an automotive production line where there is heavy reliance on human decision-making pertaining to when, where and how to install components on and inside a constantly moving vehicle body. The main aim of this work is to develop a rule-based decision support system that will enable an automation solution to make human-like decisions in moving assembly operations. The wheel loading operation is chosen as a case study and a decision support framework and tool is developed and successfully tested using multiple assembly scenarios generated from experimental data provided by gaming interface sensors installed on the laboratory-based shopfloor. The resulting decision support system has the potential to enable the automation of moving assembly operations in various sectors of the manufacturing industry.