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PurposeThe Physical Internet (PI) application in a supply chain is explored by automakers to achieve a digital supply chain to challenge timely delivery while maintaining high customised production at the lowest operating cost.Design/methodology/approachA bi-objective mixed integer model is formulated, where production is performed in multistage manufacturing systems (MMS) and then delivered in a two-level distribution system. Next, a hybrid iterative method algorithm is developed to solve the practical-scale problem within an admissible time. Finally, PI's benefits on production and supply chain operation are discussed through extensive computational experiments in different supply chain configurations.FindingsThree significant findings are obtained. First, PI can achieve a comparable or better service level, while the cost is always lower. Second, PI can improve the utilisation of production and transportation resources. Third, with a more complex supply chain and a higher production cost or truck fixed cost, PI's advantages over traditional supply chain become more vigorous, but the increase in orders will weaken it.Practical implicationsThe auto enterprise should adopt a PI-enabled supply chain (PI-SC), especially with the increase of network complexity and specific cost factors.Social implicationsImportance should be attached to the PI-SC to make customers better involved in the supply chain.Originality/valueFirst, the application of PI in the existing plant is described. Second, MMS production with multi-mode transportation is jointly scheduled. Third, the decision support of the PI-SC is provided for auto enterprises.

Bilayer hydrogels are attracting tremendous attention for their capability to integrate several different functions on the two sides of the gel, that is, imparting the gel with Janus characteristics, which is highly desired in many engineering and biomedical applications including soft actuators, hydrogel patches, and wearable electronics. However, the preparation process of the bilayer materials usually involves several complicated steps and is time-consuming, while the interfacial bonding is another main concern. Here, a simple and versatile method is proposed to obtain bilayer hydrogels within just one step based on the method of introducing viscosity contrast of the precursors for different layers. The bilayer structure can be well maintained during the whole preparation process with a constrained interfacial molecular exchange to ensure the strong bonding strength. The key requirements for forming distinct bilayer structures in situ are studied and discussed in detail. Bilayer hydrogels with different chemical designs are prepared via this strategy to tailor the good distribution of desired functions for soft actuators, wound healing patches, and wearable electronics. We believe that the strategy illustrated here will provide new insights into the preparation and application of bilayer materials.

PurposeThe purpose of this paper is to propose an innovative integration method based on decision-theoretic rough set and the extended VlseKriterijuska Optimizacija I Komoromisno Resenje (VIKOR) methods to address the resilient-sustainable supplier selection and order allocation (SS/OA) problem.Design/methodology/approachSpecifically, a two-stage approach is designed in this paper. First, the decision-theoretic rough set is employed to calculate the rough number for coping with the subjective uncertainty of data and assigning the weights for a resilient-sustainable evaluation criterion. On this basis, the supplier resilient-sustainable performance is ranked in combination with the extended VIKOR method. Second, a novel multi-objective optimization model is proposed that applies an improved genetic algorithm to select the resilient-sustainable supplier and allocate the corresponding order quantity under a multi-tier supplier network.FindingsThe results reveal that joint consideration of resilience and sustainability is essential in the SS/OA process. The method proposed in this study based on decision-theoretic rough sets and the extended VIKOR method can handle imprecise information flexibly, reduce information loss and obtain acceptable solutions for decision-makers. Numerical cases validate that this integrated approach can combine resilience and sustainability for effective and efficient SS/OA.Practical implicationsThis paper provides industry managers with a new perspective on SS/OA from a resilience and sustainability perspective as a basis for best practices for industry resilience and sustainability. The proposed method helps to evaluate the resilient-sustainable performance of potential suppliers, which is applicable to solving real-world SS/OA problems and has important practical implications for the resilient-sustainable development of supply chains.Originality/valueThe two interrelated priorities of resilience and sustainability have emerged as key strategic challenges in SS/OA issues. This paper is the first study of this issue that uses the proposed integrated approach.

Bond exchange in a typical dynamic covalent polymer network allows access to macroscopic shape reconfigurability, but the network architecture is not altered. An alternative possibility is that the network architecture can be designed to switch to various topological states corresponding to different material properties. Achieving both in one network can expand the material scope, but their intrinsically conflicting mechanisms make it challenging. We design a dynamic covalent network that can undergo two orthogonal topological transformations, namely transesterification on the branched chains and olefin metathesis on the mainframe. This allows independent control of the macroscopic shape and molecular architecture. With this design, we illustrate a bottlebrush network with programmable shape and spatially definable mechanical properties. Our strategy paves a way to on-demand regulation of network polymers.

Endowing the animals with agile actions, natural muscle functions as a soft actuator, which is powered by chemical reactions of metabolism and controlled by electrical nerve-signals. Inspired by natural muscle, various types of soft chemical machines (SCM) have been recently developed, possessing advantages of light weight, fast actuation, compact integration, high power and low noise. In this paper, we propose a composite structure as a soft chemical engine (SCE), which is driven by the chemical decomposition of hydrogen peroxide ( H 2 O2). The SCE directly converts chemical energy into mechanical work, achieving excellent performance of large actuation ( ∼ 33% volume expansion) and fast response ( ∼ 1 s). We advance the SCE with excellent performance to a soft chemical machine (SCM) with well-controlled functions, as a mechatronic control system. The soft robot possesses robust control with untethered operation and stable actuating cycles. We develop a model for the locomotion mechanisms, revealing that optimized mechatronic controls can significantly enhance the performance of SCM.

Compared to robots and devices made of rigid components, soft robots and flexible devices driven by soft active materials possess various advantages including high adaptability under extreme environment and compatibility with a human. Dielectric elastomer (DE) membrane, which is commonly used in building soft actuators, can achieve large actuation by the combined loadings of voltage-induced Maxwell stress and fluidic pressures (pneumatic and hydraulic pressure). This paper proposes a pneumatic–hydraulic coupled electromechanical actuator (PHCEA), which exhibits strong coupling effect of electromechanical actuation (the Maxwell stress on DE membrane), pneumatic and hydraulic pressures. Considering the moving boundary and state transition, a computational model has been developed to investigate the coupling behaviors of the PHCEA. The numerical result by this model is in accordance with the experimental measurements. The combination of experimental data and the theoretical result indicates that the state transition and moving boundary separate the potential region of electrical breakdown and mechanical damage. This model can be utilized as a practical method to characterize the performance and guide the design of soft devices. The experimental setup and computational method of the PHCEA bring new insights into the fabrication and characterization of soft robots, adaptive optics, and flexible bio-medical devices. The PHCEA possesses wide applications in underwater robots, soft muscles, and microfluidics systems. It can serve as the gas bladder of soft swimming robots, the soft actuator of hydraulic–pneumatic coupling systems, and the gas–liquid valve of flexible microfluidics systems.

Soft chemo-mechanical (SCM) machines convert chemical energy into mechanical energy. They have the advantages of fast actuation and compliant deformation and possess wide applications in soft robots and flexible smart devices. Using experiments and theoretical modeling, this paper investigates the chemo-mechanical energy flows and the energy conversion cycle in the pressure and volume (P–V) plane of an SCM machine consisting of a soft membrane and cylindrical chambers. The machine generates 16.1 mJ of mechanical energy per cycle. We study heat dissipation as the key issue affecting the conversion efficiency. The states of the conversion cycle calculated from mechanical modeling fit well with those measured experimentally. The design principles and the theoretical methods can be used to guide the fabrication and characterization of SCM actuators and robots.