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This study aims to investigate supply network (SN) resilience capabilities across the organizational, supply chain (SC) and industry levels by drawing on the complex adaptive systems (CASs) theory and the social–ecological perspective of resilience. An empirically grounded framework operationalizes the concept of social–ecological resilience by expounding resilience capabilities across phases of the CAS adaptive cycle.

This research uses a qualitative multiple case study approach. It draws on the case of the Australian Defence Manufacturing SN (ADM SN) during COVID-19 disruptions. A total of 28 interviews with senior decision makers from 17 companies, complemented by 5 interviews with the Australian Defence SC organizations and secondary data analysis, support the findings.

Individual organizations’ SC visibility and flexibility enabled by effective risk management and collaboration enhance the ability of the SN to anticipate and prepare for disruption. At the same time, the strength of SC relationships reduces resilience. SN disruption response velocity is enabled by inventory redundancy, process flexibility at the organizational level and visibility and collaboration at the SC level. Institutional support at the national industry level, development of value-adding capabilities and manufacturing process flexibility at the organizational level enhances the SN’s ability to re-organize. The transition from hierarchical to decentralized collaborative governance enhances SN resilience.

From a practitioner’s perspective, the findings highlight the need to embrace a broader view of SC beyond immediate tiers. Decision-makers in multinational companies must recognize the long-term impact of their procurement decisions on the supplier ecosystem. Developing local supplier capabilities rather than relying on established global SCs will pay off with future resilience. It, however, demands substantial investment and radical changes across all SC tiers. The lesson for smaller firms is not to over-rely on the existing relationships with supply partners. Although trust-based relationships and collaboration are essential, over-commitment can be counterproductive during global disruptions. With a lack of visibility and control over the SC, operational flexibility is critical for small firms to adapt to shifts in supply and demand.

To the best of the authors’ knowledge, this empirical research is one of the first attempts to operationalize the social–ecological perspective of SN resilience. Evidence-based theoretical propositions contribute to the emerging conversation about the CAS nature of resilience by demonstrating the multi-level effects of resilience capabilities.

The purpose of this paper is to introduce a variable distance pneumatic gripper with embedded flexible sensors, which can effectively grasp fragile and flexible objects.

Based on the motion principle of the three-jaw chuck and the pneumatic “fast pneumatic network” (FPN), a variable distance pneumatic holder embedded with a flexible sensor is designed. A structural design plan and preparation process of a soft driver is proposed, using carbon nanotubes as filler in a polyurethane (PU) sponge. A flexible bending sensor based on carbon nanotube materials was produced. A static model of the soft driver cavity was established, and a bending simulation was performed. Based on the designed variable distance soft pneumatic gripper, a real-time monitoring and control system was developed. Combined with the developed pneumatic control system, gripping experiments on objects of different shapes and easily deformable and fragile objects were conducted.

In this paper, a variable-distance pneumatic gripper embedded with a flexible sensor was designed, and a control system for real-time monitoring and multi-terminal input was developed. Combined with the developed pneumatic control system, a measure was carried out to measure the relationship between the bending angle, output force and air pressure of the soft driver. Flexible bending sensor performance test. The gripper diameter and gripping weight were tested, and the maximum gripping diameter was determined to be 182 mm, the maximum gripping weight was approximately 900 g and the average measurement error of the bending sensor was 5.91%. Objects of different shapes and easily deformable and fragile objects were tested.

Based on the motion principle of the three-jaw chuck and the pneumatic FPN, a variable distance pneumatic gripper with embedded flexible sensors is proposed by using the method of layered and step-by-step preparation. The authors studied the gripper structure design, simulation analysis, prototype preparation, control system construction and experimental testing. The results show that the designed flexible pneumatic gripper with variable distance can grasp common objects.

Photovoltaic (PV) systems are experiencing exponential growth due to environmental concerns, unlimited and ubiquitous solar energy, and starting-to-make-sense panel costs. Alongside designing more efficient solar panels, installing solar trackers and special circuitry for optimizing power delivery to the load according to a maximum power point tracking (MPPT) algorithm are other ways of increasing efficiency. However, it is critical for any efficiency increase to account for the power consumption of any amendments. Therefore, this paper aims to propose a novel tracker while using MPPT to boost the PV system's actual efficiency accounting for the involved costs.

The proposition is an experimental pneumatic dual-axis solar tracker using light-dependent resistor (LDR) sensors. Due to its embedded energy storage, the pneumatic tracker offers a low duty-cycle operation leading to tracking energy conservation, fewer maintenance needs and scalability potential. While MPPT assures maximum load power delivery, the solar PV's actual delivered power is calculated for the first time, accounting for the solar tracking and MPPT power costs.

The experiments' results show an increase of 37.6% in total and 35.3% in actual power production for the proposed solar tracking system compared to the fixed panel system, with an MPPT efficiency of 90%. Thus, the pneumatic tracking system offers low tracking-energy consumption and good actual power efficiency. Also, the newly proposed pneumatic stimulant can significantly simplify the tracking mechanism and benefit from several advantages that come along with it.

To the best of the authors’ knowledge, this work proposes, for the first time, a single-motor pneumatic dual-axis tracker with less implementation cost, less frequent operation switching and scalability potential, to be developed in future works. Also, the pneumatic proposal delivers high actual power efficiency for the first time to be addressed.

The purpose of this paper is to gain an in-depth understanding into the research progress, hot spots and future trends in smart gripping technology in the field of apparel smart manufacturing.

This work scrutinised the current research status of the five automatic grasping methods for garment fabrics including the pneumatic suction grasping, the electrostatic grasping, the intrusive grasping and the dexterous grasping. Specifically, the principles, characteristics, main devices and the impact on garment production were discussed.

In particular, soft finger of the dexterous grasping method has good flexibility and adaptability in the process of fabric grasping, which provides a new solution for garment production automation. Up to now, the reviewed method in general exhibit good grasping speed, high grasping stability and flat grasping process. However, in the face of complex fabric materials which are thin and flexible and do not return their original shapes when deformed in practical applications, the gripper for automatic fabric grasping need new technological breakthroughs in the positioning accuracy, grab efficiency and flexible grasping.

The outcomes offered an overview of the research status and future trends of the automatic grasping methods for garment fabrics in the field of apparel intelligent manufacturing. It could not only provide scholars with convenience in identifying research hot spots and building potential cooperation in the follow-up research but also assist beginners in searching core scholars and literature of great significance.

This paper presents Quick Changeover Design (QCD), which is a structured methodological approach for Original Equipment Manufacturers to drive and support the design of machines in terms of rapid changeover capability.

To improve the performance in terms of set up time, QCD addresses machine design from a single-minute digit exchange of die (SMED). Although conceived to aid the design of completely new machines, QCD can be adapted to support for simple design upgrades on pre-existing machines. The QCD is structured in three consecutive steps, each supported by specific tools and analysis forms to facilitate and better structure the designers' activities.

QCD helps equipment manufacturers to understand the current and future needs of the manufacturers' customers to: (1) anticipate the requirements for new and different set-up process; (2) prioritize the possible technical solutions; (3) build machines and equipment that are easy and fast to set-up under variable contexts. When applied to a production system consisting of machines subject to frequent or time-consuming set-up processes, QCD enhances both responsiveness to external market demands and internal control of factory operations.

The QCD approach is a support system for the development of completely new machines and is also particularly effective in upgrading existing ones. QCD's practical application is demonstrated using a case study concerning a vertical spindle machine.

It is well known in the mining industry that the increase in failures and breakdowns is due mainly to a poor maintenance policy for the equipment, in addition to the difficult access that specialized personnel have to combat the breakdown, which translates into more machine downtime. For this reason, this study aims to propose a remote assistance model for diagnosing and repairing critical breakdowns in mining industry trucks using augmented reality techniques and data analytics with a quality approach that considerably reduces response times, thus optimizing human resources.

In this work, the six-phase CRIPS-DM methodology is used. Initially, the problem of fault diagnosis in trucks used in the extraction of material in the mining industry is addressed. The authors then propose a model under study that seeks a real-time connection between a service technician attending the truck at the mine site and a specialist located at a remote location, considering the data transmission requirements and the machine's characterization.

It is considered that the theoretical results obtained in the development of this study are satisfactory from the business point of view since, in the first instance, it fulfills specific objectives related to the telecare process. On the other hand, from the data mining point of view, the results manage to comply with the theoretical aspects of the establishment of failure prediction models through the application of the CRISP-DM methodology. All of the above opens the possibility of developing prediction models through machine learning and establishing the best model for the objective of failure prediction.

The original contribution of this work is the proposal of the design of a remote assistance model for diagnosing and repairing critical failures in the mining industry, considering augmented reality and data analytics. Furthermore, the integration of remote assistance, the characterization of the CAEX, their maintenance information and the failure prediction models allow the establishment of a quality-based model since the database with which the learning machine will work is constantly updated.

This paper aims to assess the impact of electrifying the environmental control system (ECS) and ice protection system (IPS), the primary pneumatic system consumers in a conventional commercial transport aircraft, on aircraft weight, range, and fuel consumption.

The case study was carried out on Airbus A321-200 aircraft. Design, modelling and analysis processes were carried out on Pacelab SysArc software. Conventional and electrical ECS and IPS architectures were modelled and analysed considering different temperature profiles.

The simulation results have shown that the aircraft model with ±270 VDC ECS and IPS architecture is lighter, has a more extended range and has less relative fuel consumption. In addition, the simulation results showed that the maximum range and relative fuel economy of all three aircraft models increased slightly as the temperature increased.

Considering the findings in this paper, it is seen that the electrification of the conventional pneumatic system in aircraft has positive contributions in terms of weight, power consumption and fuel consumption.

The positive contributions in terms of weight, power consumption and fuel consumption in aircraft will be direct environmental and economic contributions.

Apart from the conventional ECS and IPS of the aircraft, two electrical architectures, 230 VAC and ±270 VDC, were modelled and analysed. To see the effects of the three models created in different temperature profiles, analyses were done for cold day, ISA standard day and hot day temperature profiles.

Multisited ethnography has primarily been portrayed as a challenge for the following field-worker, with the researcher taking the central role and neglecting research participants also experiencing a multisited nature of their work. The authors argue that literature on multisited ethnography merely discusses multisitedness as a methodological theme. In correspondence, the authors propose to think of multisitedness not just as a methodological theme but also as an empirical theme.

The authors contend etic and emic perspectives to address multisitedness empirically, which enables researchers to compare and contrast the multisited topic of inquiry in academic “outsider” terms with the etic analysis and considering the perspective of the research participants' multisited experiences using the emic perspective. To show the fruitfulness of discussing multisitedness using the complementary etic and emic analysis, the authors present the example of Mennonite entrepreneurial activities in Belize, a heterogeneous group of migrants that established themselves as successful traders and entrepreneurs.

Through an etic multisited ethnographic perspective, the authors compare and contrast four communities of Mennonites in terms of their entrepreneurial activities, technology and energy use. Through an emic perspective, the authors demonstrate how Mennonites, while preferring an in-group focus, navigate their multisited entrepreneurial activities, which require interaction with the outside world.

The authors highlight the value of combining etic–emic reflections to acknowledge and include the multisited nature of many social phenomena as experienced by the research participants.

The purpose of this article is to solve the issue that apple-picking robots are easily interfered by branches or other apples near the target apple in an unstructured environment, leading to grasping failure and apple damage.

This study introduces the system units of the apple-picking robot prototype, proposes a method to determine the apple-picking direction via 3D point cloud data and optimizes the path planning method according to the calculated picking direction.

After the field experiments, the average deviation of the calculated picking direction from the desired angle was 11.81°, the apple picking success rate was 82% and the picking cycle was 11.1 s.

This paper describes a picking control method for an apple-picking robot that can improve the success and reliability of picking in an unstructured environment and provides a basis for automated and mechanized picking in the future.

The brake controller is a key component of the locomotive brake system. It is essential to study its safety.

This paper summarizes and analyzes typical faults of the brake controller, and proposes four categories of faults: position sensor faults, microswitch faults, mechanical faults and communication faults. Suggestions and methods for improving the safety of the brake controller are also presented.

In this paper, a self-judgment and self-learning dynamic calibration method is proposed, which integrates the linear error of the sensor and the manufacturing and assembly errors of the brake controller to solve the output drift. This paper also proposes a logic for diagnosing and handling microswitch faults. Suggestions are proposed for other faults of brake controller.

The methods proposed in this paper can greatly improve the usability of the brake controller and reduce the failure rate.