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Current flexible printed circuit (FPC) assembly relies heavily on manual labor, limiting capacity and increasing costs. Small FPC size makes automation challenging as terminals can be visually occluded. The purpose of this study is to use 3D tactile sensing to mimic human manual mating skills for enabling sensing offset between FPC terminals (FPC-t) and FPC mating slots (FPC-s) under visual occlusion.

The proposed model has three stages: spatial encoding, offset estimation and action strategy. The spatial encoder maps sparse 3D tactile data into a compact 1D feature capturing valid spatial assembly information to enable temporal processing. To compensate for low sensor resolution, consecutive spatial features are input to a multistage temporal convolutional network which estimates alignment offsets. The robot then performs alignment or mating actions based on the estimated offsets.

Experiments are conducted on a Redmi Note 4 smartphone assembly platform. Compared to other models, the proposed approach achieves superior offset estimation. Within limited trials, it successfully assembles FPCs under visual occlusion using three-axis tactile sensing.

A spatial encoder is designed to encode three-axis tactile data into feature maps, overcoming multistage temporal convolution network’s (MS-TCN) inability to directly process such input. Modifying the output to estimate assembly offsets with related motion semantics overcame MS-TCN’s segmentation points output, unable to meet assembly monitoring needs. Training and testing the improved MS-TCN on an FPC data set demonstrated accurate monitoring of the full process. An assembly platform verified performance on automated FPC assembly.

Owing to the finite nature of the boundary of the line (BOL), the conventional method, involving the strong matching of single-variety parts with storage locations at the periphery of the line, proves insufficient for mixed-model assembly lines (MMAL). Consequently, this paper aims to introduce a material distribution scheduling problem considering the shared storage area (MDSPSSA). To address the inherent trade-off requirement of achieving both just-in-time efficiency and energy savings, a mathematical model is developed with the bi-objectives of minimizing line-side inventory and energy consumption.

A nondominated and multipopulation multiobjective grasshopper optimization algorithm (NM-MOGOA) is proposed to address the medium-to-large-scale problem associated with MDSPSSA. This algorithm combines elements from the grasshopper optimization algorithm and the nondominated sorting genetic algorithm-II. The multipopulation and coevolutionary strategy, chaotic mapping and two further optimization operators are used to enhance the overall solution quality.

Finally, the algorithm performance is evaluated by comparing NM-MOGOA with multi-objective grey wolf optimizer, multiobjective equilibrium optimizer and multi-objective atomic orbital search. The experimental findings substantiate the efficacy of NM-MOGOA, demonstrating its promise as a robust solution when confronted with the challenges posed by the MDSPSSA in MMALs.

The material distribution system devised in this paper takes into account the establishment of shared material storage areas between adjacent workstations. It permits the undifferentiated storage of various part types in fixed BOL areas. Concurrently, the innovative NM-MOGOA algorithm serves as the core of the system, supporting the formulation of scheduling plans.

The purpose of this paper is to investigate the process of fused filament fabrication (FFF) of a compliant gripper (CG) using thermoplastic polyurethane (TPU) material. The paper studies the applicability of different CG designs and the efficiency of some design parameters.

After reviewing a number of different papers, two designs were selected for a number of exploratory experiments. Using design of experiments (DOE) techniques to identify important design parameters. Finally, the efficiency of the parts was investigated.

The research finds that a simpler design sacrifices some effectiveness in exchange for a remarkable decrease in production cost. Decreasing infill percentage of previous designs and 3D printing them, out of TPU, experimenting with different parameters yields functional products. Moreover, the paper identified some key parameters for further optimization attempts of such prototypes.

The cost of conducting FFF experiments for TPU increases dramatically with product size, number of parameters studied and the number of experiments. Therefore, all three of these factors had to be kept at a minimum. Further confirmatory experiments encouraged.

This paper addresses an identified need to investigate applications of FFF and TPU in manufacturing functional efficient flexible mechanisms, grippers specifically. While most research focused on designing for increased performance, some research lacks discussion on design philosophy, as well as manufacturing issues. As the needs for flexible grippers vary from high-performance grippers to lower performance grippers created for specific functions/conditions, some effectiveness can be sacrificed to reduce cost, reduce complexity and improve applicability in different robotic assemblies and environments.

This study aims to investigate how to identify and address production levelling problems in assembly lines utilising an intensive manual workforce when higher productivity levels are urgently requested to meet market demands.

A mixed-methods approach was used in the research design, integrating case study analysis, interviews and qualitative/quantitative data collection and analysis. The methodology implemented also introduces to the literature on operational performance a novel combination of data analysis methods by introducing the use of the Natural Language Understanding (NLU) methods.

First, the findings unveil the impacts on operational performance that transportation, limited documentation and waiting times play in assembly lines composed of an intensive workforce. Second, the paper unveils the understanding of the role that a limited understanding of how the assembly line functions play in productivity. Finally, the authors provide actionable insights into the levelling problems in manual assembly lines.

This research supports industries operating assembly lines with intensive utilisation of manual workforce to improve operational performance. The paper also proposed a novel conceptual model prescriptively guiding quick and long-term improvements in intensive manual workforce assembly lines. The article assists industrial decision-makers with subsequent turnaround strategies to ensure higher efficiency levels requested by the market.

The paper offers actionable findings relevant to other manual assembly lines utilising an intensive workforce looking to improve operational performance. Some of the methods and strategies examined in this study to improve productivity require minimal capital investments. Lastly, the study contributes to the empirical literature by identifying production levelling problems in a real context.

The purpose of this paper is to enhance the performance of robots in peg-in-hole assembly tasks, enabling them to swiftly and robustly accomplish the task. It also focuses on the robot’s ability to generalize across assemblies with different hole sizes.

Human behavior in peg-in-hole assembly serves as inspiration, where individuals visually locate the hole firstly and then continuously adjust the peg pose based on force/torque feedback during the insertion process. This paper proposes a novel framework that integrate visual servo and adjustment based on force/torque feedback, the authors use deep neural network (DNN) and image processing techniques to determine the pose of hole, then an incremental learning approach based on a broad learning system (BLS) is used to simulate human learning ability, the number of adjustments required for insertion process is continuously reduced.

The author conducted experiments on visual servo, adjustment based on force/torque feedback, and the proposed framework. Visual servo inferred the pixel position and orientation of the target hole in only about 0.12 s, and the robot achieved peg insertion with 1–3 adjustments based on force/torque feedback. The success rate for peg-in-hole assembly using the proposed framework was 100%. These results proved the effectiveness of the proposed framework.

This paper proposes a framework for peg-in-hole assembly that combines visual servo and adjustment based on force/torque feedback. The assembly tasks are accomplished using DNN, image processing and BLS. To the best of the authors’ knowledge, no similar methods were found in other people’s work. Therefore, the authors believe that this work is original.

The pivotal aspect of aircraft assembly lies in precise measurement accuracy. While a solitary digital measuring tool suffices for analytical and small surfaces, it falls short for extensive synthetic surfaces like aircraft fuselage panels and wing spars. The purpose of this study is to develop a “combined measurement method” (CMM) that enhances measurement quality and expands the evaluative scope, addressing the limitations posed by singular digital devices in meeting measurement requirements across various aircraft components.

The study illustrated the utilization of the CMM by combining a laser tracker and a portable arm-measuring machine. This innovative approach is tailored to address the intricate nature and substantial dimensions of aircraft fuselage panels. The portable arm-measuring machine performs precise scans of panel components, while common points recorded by the laser tracker undergo coordinate conversion to reconstruct the fuselage panel’s shape. The research outlines the CMM’s measurement procedure and scrutinizes the data processing technique. Ultimately, the investigation yields a deviation vector matrix and chromatogram deviation distribution, pivotal in achieving enhanced measurement precision for the novel CMM device.

The use of CMM noticeably enhances fuselage panel assembly accuracy, concurrently reducing assembly time and enhancing efficiency compared to conventional measurement systems.

The research’s practical implication lies in revolutionizing aircraft assembly by mitigating accuracy issues through the innovative digital CMM for aircraft synthetic structure type product (aircraft fuselage panel). This ensures safer flights, reduces rework and enhances overall efficiency in the aerospace industry.

Introducing a new aircraft assembly accuracy compensation method through digital combined measurement, pioneering improved assembly precision. Also, it enhances aerospace assembly quality, safety and efficiency, offering innovative insights for optimized aviation manufacturing processes.

This study aims to address the issue of random movement and non coordination between docking mechanisms and locking mechanisms, and proposes a comprehensive dynamic docking control architecture that integrates perception, planning, and motion control.

Firstly, the proposed dynamic docking control architecture uses laser sensors and a charge-coupled device camera to perceive the pose of the target. The sensor data are mapped to a high-dimensional potential field space and fused to reduce interference caused by detection noise. Next, a new potential function based on multi-dimensional space is developed for docking path planning, which enables the docking mechanism based on Stewart platform to rapidly converge to the target axis of the locking mechanism, which improves the adaptability and terminal docking accuracy of the docking state. Finally, to achieve precise tracking and flexible docking in the final stage, the system combines a self-impedance controller and an impedance control algorithm based on the planned trajectory.

Extensive simulations and experiments have been conducted to validate the effectiveness of the dynamic docking system and its control architecture. The results indicate that even if the target moves randomly, the system can successfully achieve accurate, stable and flexible dynamic docking.

This research can provide technical guidance and reference for docking task of unmanned vehicles under the ground conditions. It can also provide ideas for space docking missions, such as space simulator docking.

The study aims to ascertain the influence of solder conductive particle types and substrate widths on the current carrying capability of flex-on-board (FOB) assemblies. By comparing Sn58Bi and SAC305 particles and varying substrate widths, the research sought to provide insights into the stability and performance of solder joints under different scenarios, particularly in high-power applications.

The study used a comprehensive design/methodology, encompassing the investigation of solder conductive particle types (Sn58Bi and SAC305) and substrate widths on the current carrying capability of FOB assembly. Stable solder joints were obtained by manipulating the curing speed of anisotropic conductive films for both particle types. Various tests were conducted, including current carrying capability assessments under differing conditions.

The study revealed that larger substrate widths yielded higher current carrying capability due to increased contact area and reduced contact resistance. Notably, solder joints remained stable beyond the solder melting temperature due to encapsulation by cured epoxy resin. SAC305 solder joints exhibited superior current carrying capability over Sn58Bi in continuous high-voltage conditions. The results emphasized the stability of SAC305 solder joints and their suitability for robust interconnections in high-power FOB assemblies.

This study contributes by offering a comprehensive assessment of the impact of solder particle types and substrate widths on solder joint performance in FOB assemblies. The finding that SAC305 joints outperform Sn58Bi under continuous high-voltage conditions adds significant value. Moreover, the observation of stable solder joints beyond solder melting temperature due to resin encapsulation introduces a novel aspect to solder joint reliability. These insights provide valuable guidance for designing robust and high-performance interconnections in demanding applications.

Arthroscopic osteochondroplasty is a minimally invasive procedure that has been used to treat femoroacetabular impingement syndrome, leading to significant improvements in patients’ clinical outcomes and quality of life. However, some studies suggest that inadequate bone resection can substantially alter hip biomechanics. These modifications may generate different contact profiles and higher contact forces, increasing the risk of developing premature joint degeneration. To improve control over bone resection and biomechanical outcomes during arthroscopic osteochondroplasty surgery, this study aims to present a novel system for measuring femoroacetabular contact forces.

Following a structured design process for the development of medical devices, the steps required for its production using additive manufacturing with material extrusion and easily accessible sensors are described. The system comprises two main devices, one for measuring femoroacetabular contact forces and the other for quantifying the force applied by the assistant surgeon during lower limb manipulation. The hip device was designed for use within an arthroscopic environment, eliminating the need for additional portals.

To evaluate its performance, the system was first tested in a laboratory setup and later under in-service conditions. The 3D printing parameters were tuned to ensure the watertighness of the device and sustain the intraoperative fluid pressures. The final prototype allowed for the controlled measurement of the hip contact forces in real-time.

Using additive manufacturing and readily available sensors, the present work presents the first device to quantify joint contact forces during arthroscopic surgeries, serving as an additional tool to support the surgeon’s decision-making process regarding bone resection.

This paper aims to analyse the current state of research to identify the link between Lean Manufacturing and Industry 4.0 (I4.0) technologies to map out different research themes, to uncover research gaps and propose key recommendations for future research, including lessons to be learnt from the integration of lean and I4.0.

A systematic literature review (SLR) is conducted to thematically analyse and synthesise existing literature on Lean Manufacturing–I4.0 integration. The review analysed 60 papers in peer-reviewed journals.

In total, five main research themes were identified, and a thematic map was created to explore the following: the relationship between Lean Manufacturing and I4.0; Lean Manufacturing and I4.0 implication on performance; Lean Manufacturing and I4.0 framework; Lean Manufacturing and I4.0 integration with other methodologies; and application of I4.0 technologies in Lean Manufacturing. Furthermore, various gaps in the literature were identified, and key recommendations for future directions were proposed.

The integration of Lean Manufacturing and I4.0 will eventually bring many benefits and offers superior and long-term competitive advantages. This research reveals the need for more analysis to thoroughly examine how this can be achieved in real life and promote operational changes that ensure enterprises run more sustainably.

The development of Lean Manufacturing and I4.0 integration is still in its infancy, with most articles in this field published in the past two years. The five main research themes identified through thematic synthesis are provided in the original contribution. This provides scholars better insight into the existing literature related to Lean Manufacturing and I4.0, further contributing to defining clear topics for future research opportunities. It also has important implications for industrialists, who can develop more profound and richer knowledge than Lean and I4.0, which would, in turn, help them develop more effective deployment strategies and have a positive commercial impact.