Assembly Of Components Research Articles

Fatigue properties of riveted joints under different hole perpendicularity errors and squeeze forces.

Riveting is the most important method of joining sheet metal and is widely used in the assembly of aircraft components. The perpendicularity error of the holes is unavoidable during automatic drilling and riveting, which has a significant impact on the quality of the assembly. In this paper, the effects of hole perpendicularity error and squeeze force on the interference fit size, interface contact state, microstructure morphology, fatigue life, and fracture form of riveted joints were investigated experimentally. The results show that the interference fit size increases with a greater tilt angle. When the tilt angle is 0°, the rivet shank is in close contact with the inner and outer sheets, and there is no obvious gap at the interface between the rivet and the sheets. As the tilt angle increases to 2° and 4°, a gap appears at the interface of regions 1, 2, and 3, while the rivet shank at region 4 is in close contact with the outer sheet. The fatigue life decreases when the tilt angle increases from 0° to 4°. For the same tilt angle, the fatigue life of riveted joints with a 0° tilt direction is higher than that of riveted joints with a 180° tilt direction. Increasing the squeeze force can to some extent reduce the adverse effect of the tilt angle on the fatigue life. The hole perpendicularity error does not affect the failure form, while the squeeze force has a significant effect on the failure form of the specimens. RESEARCH HIGHLIGHTS: The fatigue life of riveted joints decreases as the tilt angle increases. The size of the interfacial gap increases with increasing tilt angle. Higher fatigue life at 0° tilt direction than at 180° tilt direction. Increasing the squeeze force can somewhat reduce the negative effect of tilt angle on fatigue life.

An optimization model for just-in-time (JIT) delivery of precast components considering 3D loading constraints, real-time road conditions and assembly time

PurposeAlthough extensive research has been conducted on precast production, irregular component loading constraints have received little attention, resulting in limitations for transportation cost optimization. Traditional irregular component loading methods are based on past performance, which frequently wastes vehicle space. Additionally, real-time road conditions, precast component assembly times, and delivery vehicle waiting times due to equipment constraints at the construction site affect transportation time and overall transportation costs. Therefore, this paper aims to provide an optimization model for Just-In-Time (JIT) delivery of precast components considering 3D loading constraints, real-time road conditions and assembly time.Design/methodology/approachIn order to propose a JIT (just-in-time) delivery optimization model, the effects of the sizes of irregular precast components, the assembly time, and the loading methods are considered in the 3D loading constraint model. In addition, for JIT delivery, incorporating real-time road conditions in the transportation process is essential to mitigate delays in the delivery of precast components. The 3D precast component loading problem is solved by using a hybrid genetic algorithm which mixes the genetic algorithm and the simulated annealing algorithm.FindingsA real case study was used to validate the JIT delivery optimization model. The results indicated this study contributes to the optimization of strategies for loading irregular precast components and the reduction of transportation costs by 5.38%.Originality/valueThis study establishes a JIT delivery optimization model with the aim of reducing transportation costs by considering 3D loading constraints, real-time road conditions and assembly time. The irregular precast component is simplified into 3D bounding box and loaded with three-space division heuristic packing algorithm. In addition, the hybrid algorithm mixing the genetic algorithm and the simulated annealing algorithm is to solve the 3D container loading problem, which provides both global search capability and the ability to perform local searching. The JIT delivery optimization model can provide decision-makers with a more comprehensive and economical strategy for loading and transporting irregular precast components.

Experimental characterisation and statistical modelling of woven carbon fibre weld conductors for electrical resistance welding of thermoplastic composites

Resistance welding of high-performance thermoplastic composites is a promising joining technique for the structural assembly of aerospace components. Knowledge of the weld conductor resistance as a function of its dimensions, as well as external boundary conditions such as contact preparation and pressure, can be used to scale welding parameters. This paper presents a comprehensive review on the weld conductor contact preparation, length, width and contact pressure dependent resistance with respect to the Toray 5HS T300JB carbon woven prepreg 281 gsm fibre architecture. The study is based on a 4-wire resistance measurement of the carbon fibre fabric weld conductors and was conducted to provide a solid basis for defining the weld conductor’s resistance, considering the dependence on length, width and contact pressure. The experimentally determined resistance values were approximated using linear and non-linear regression functions and combined into a general formulation with respect to the investigated carbon fibre fabric architecture. The least squares fit of experimental versus model data confirmed a very high model confidence. Thus, the model allows a simplified transfer of electrical properties for process pre-design and scaling considering weld conductors with the same fibre architecture.

A rapid oriented detection method of virtual components for augmented assembly

Augmented assembly provides intuitive assembly guidelines to the assembly operators. With assembly tasks developing toward diversification, the position of virtual components that are superimposed on the real environment may change frequently and virtual components have different length-diameter ratios and overlap each other. However, existing object detection methods are time consuming and hardly separate virtual components in dense for augmented assembly. Therefore, this paper proposes a rapid oriented detection method based on swift oriented detection region-based convolutional network (SODR-CNN) for virtual components in augmented assembly. Specifically, a dual channel selection (DCS) structure is designed to extract spatial features by reducing redundant computation and memory access. Further, the novel backbone network, rapid network (RapidNet), is proposed building upon the DCS, which can decrease the inference latency of SODR-CNN. Finally, the comprehensive experiments demonstrate that the RapidNet achieves lower inference latency than comparison backbone networks, which means that the SODR-CNN achieves superior inference latency and detection accuracy. Moreover, intuitive evaluation experiments are carried out, in which the effectiveness of the proposed method is further verified by searching for several virtual components in a real environment.

Optimization of Component Assembly in Automotive Industry

Abstract This article is devoted to the positioning of glued parts by robots in the process of manufacturing automotive headlights, with the possibility of generalization to the mutual positioning of any 3D object. The authors focused on the description of the mathematical method that leads to the optimization of the robot arm setting and ensures the closest contact of the glued parts. The contact surfaces of the two joined parts are, in the ideal case, identical in shape and their optimal alignment is considered to best align the position of the nominal points on the base part with the position of the control (measured) points on the part manipulated by the robot.

High Temperature Ternary Chloride Molten Salt Pump

A ternary chloride (MgCl2-NaCl-KCl) molten salt pump has been developed to operate up to 720°C. The design is the result of a thermal, structural and material study of critical components. The vertical overhung pump incorporates first of a kind salt-wetted hydrodynamic bearings. Several bearing material pairings were tested which include: colmonoy grades, stellite grades, and a novel NiWC-based alloy (i.e. HybrimetTM NiWC3b) used as a High Velocity Oxygen Fuel (HVOF) coating. The coating withstands the corrosion effects of the molten salt, and is also used to protect a 316L stainless steel pump reservoir. The pump bowl assembly components are made of Inconel 625. A Nitrogen flushed carbon ring seal is used to keep salt vapors from interacting with external ambient air. Preliminary testing shows a promising pump design for use in the Concentrating Solar Power Gen 3 systems and sets the ground for further development of the HybrimetTM NiWC3b as a competitive alternative to available superalloys.

Co-Design of Mechanical and Vibration Properties of a Star Polygon-Coupled Honeycomb Metamaterial

Based on the concept of component assembly, a novel star polygon-coupled honeycomb metamaterial, which achieves a collaborative improvement in load-bearing capacity and vibration suppression performance, is proposed based on a common polygonal structure. The compression simulation and experiment results show that the load-bearing capacity of the proposed metamaterial is three times more than that of the initial metamaterial. Additionally, metal pins are attached and particle damping is applied to the metamaterial to regulate its bandgap properties; the influence of configuration parameters, including the size, number, position, and material of the metal pins, on bandgaps is also investigated. The results show that the bandgap of the proposed metamaterial can be conveniently and effectively regulated by adjusting the parameters and can effectively suppress vibrations in the corresponding frequency band. Particle damping can be used to continuously adjust the frequency of the bandgap and further enhance the vibration suppression capacity of the metamaterial in other frequency bands. This paper provides a reference for the design and optimization of metamaterials.

Boosting Oxygen Reduction at Pt(111)|Proton Exchange Ionomer Interfaces through Tuning the Microenvironment Water Activity.

A proton exchange ionomer is one of the most important components in membrane electrode assemblies (MEAs) of polymer electrolyte membrane fuel cells (PEMFCs). It acts as both a proton conductor and a binder for nanocatalysts and carbon supports. The structure and the wetting conditions of the MEAs have a great impact on the microenvironment at the three-phase interphases in the MEAs, which can significantly influence the electrode kinetics such as the oxygen reduction reaction (ORR) at the cathode. Herein, by using the Pt(111)|X ionomer interface as a model system (X = Nafion, Aciplex, D72), we find that higher drying temperature lowers the onset potential for sulfonate adsorption and reduces apparent ORR current, while the current wave for OHad formation drops and shifts positively. Surprisingly, the intrinsic ORR activity is higher after properly correcting the blocking effect of Pt active sites by sulfonate adsorption and the poly(tetrafluoroethylene) (PTFE) skeleton. These results are well explained by the reduced water activity at the interfaces induced by the ionomer/PTFE, according to the mixed potential effect. Implications for how to prepare MEAs with improved ORR activity are provided.

Splenic proteome profiling in response to Marek’s disease virus strain GX0101 infection

Marek’s disease virus (MDV) strain GX0101 was the first reported field strain of recombinant gallid herpesvirus type 2 (GaHV-2). However, the splenic proteome of MDV-infected chickens remains unclear. In this study, a total of 28 1-day-old SPF chickens were intraperitoneally injected with chicken embryo fibroblast (CEF) containing 2000 PFU GX0101. Additionally, a control group, consisting of four one-day-old SPF chickens, received intraperitoneal equal doses of CEF. Blood and various tissue samples were collected at different intervals (7, 14, 21, 30, 45, 60, and 90 days post-infection; dpi) for histopathological, real-time PCR, and label-free quantitative analyses. The results showed that the serum expressions of MDV-related genes, meq and gB, peaked at 45 dpi. The heart, liver, and spleen were dissected at 30 and 45 dpi, and their hematoxylin-eosin staining indicated that virus infection compromised the normal organizational structure at 45 dpi. Particularly, the spleen structure was severely damaged, and the lymphocytes in the white medulla were significantly reduced. Furthermore, liquid chromatography-mass spectrometry (LC-MS) and label-free techniques were used to analyze the difference in splenic proteome profiles of the experimental and control groups at 30 and 45 dpi. Proteomic analysis identified 1660 and 1244 differentially expressed proteins (DEPs) at 30 and 40 dpi, respectively, compared with the uninfected spleen tissues. According to GO analysis, these DEPs were involved in processes such as organelle organization, cellular component biogenesis, cellular component assembly, anion binding, small molecule binding, metal ion binding, cation binding, cytosol, nuclear part, etc. Additionally, KEGG analysis indicated that the following pathways were linked to MDV-induced inflammation, apoptosis, and tumor: Wnt, Hippo, AMPK, cAMP, Notch, TGF-β, PI3K-Akt, Rap1, Ras, Calcium, NF-κB, PPAR, cGMP-PKG, Apoptosis, VEGF, mTOR, FoxO, TNF, JAK-STAT, MAPK, Prion disease, T cell receptor, and B cell receptor. We finally screened 674 DEPs that were linked to MDV infection in spleen tissue. This study improves our understanding of the MDV response mechanism in the spleen.

Automating Robotic Micro-Assembly of Fluidic Chips and Single Fiber Compression Tests Based-on Θ Visual Measurement With High-Precision Fiducial Markers

At small scales, automating robotic tasks such as assembly, force/displacement characterization, positioning, etc., appear to be particularly limited. This is due to the lack of sufficiently performing and easy-to-implement multi-degrees-of-freedom measurement systems able to measure the relative pose between micro-parts. In order to address this issue, a measurement method based on High-Precision fiducial markers (named HP code) is proposed. This measurement method combines a periodic pattern (providing high resolution by phase-based computation) with more regular QR codes (bringing versatile implementations and a quick detection). The design and method to efficiently locate these HP codes are presented in this paper. Experimental investigations demonstrate ultra-high resolution: <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$2$</tex-math> </inline-formula> nm and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$5$</tex-math> </inline-formula> <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\upmu$</tex-math> </inline-formula> rad along <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$X,Y$</tex-math> </inline-formula> and <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\Theta$</tex-math> </inline-formula> respectively (i.e. one thousandth of a pixel typically). The method is designed to be scalable as well as self-calibrated and to provide high robustness and high versatility. Two typical challenging applications in the field of microrobotics are automated to demonstrate these disruptive performances and the easy-to-implement capability of the method: (1) the automated assembly of two micro-fluidic chips through visual servoing with an achieved positioning accuracy below <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$50$</tex-math> </inline-formula> nm, and (2) the automated micromechanical characterization of single fibers achieved by the integration of HP codes into a compliant structure enabling simultaneous micro-force and displacement sensing capabilities. These achievements highlight the versatility of the method and open the door to the rapid automation of high-quality robotic tasks at the micro scale. <italic xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink">Note to Practitioners</i> —The motivation for this work/study is based on the fact that many application areas are extensively orienting towards microrobotic systems to perform precise tasks with versatility. However, at the micro scale, many disturbances such as the effects of climate change strongly affect this precision. This problem is amplified by the fact that sensors cannot be easily integrated, either by lack of space or by the lack of measurement systems available. Vision-based approaches are widespread at this scale and appear very promising to measure the relative pose between micro-parts. Nevertheless, existing vision-based approaches like digital image correlation are both scale and texture dependent. Due to the lack of space, they are also difficult to use in practice at small scales for high resolution measurement. The main contribution of this paper lies in the capability to achieve ultra-high resolution measurements. For that, a structure based on High-Precision fiducial markers (named HP codes) is proposed and requires few and simple settings while achieving very high resolution both in position and orientation, typically down to one thousandth of a pixel and a few micro radians, respectively. It provides an off-the-shelf solution, versatile, easy to implement and achieves high resolution measurements in the plane (XY <inline-formula xmlns:mml="http://www.w3.org/1998/Math/MathML" xmlns:xlink="http://www.w3.org/1999/xlink"> <tex-math notation="LaTeX">$\Theta$</tex-math> </inline-formula> ). HP codes are applicable to a wide range of applications such as tracking of a component/part of a mobile or deformable system, visual servoing of microrobots, positioning of samples, assembly of components or even mechanical characterization. A free distribution of the library is available online at https://projects.femto-st.fr/ vernier/.

Edge Computing Framework for Enhanced Robotic Adaptivity in Line-Less Mobile Assembly Systems

In response to the shortage of skilled workers and the increasing diversity of products and variants, integrating adaptive and flexible mobile manipulators into line-less mobile assembly systems (LMAS) stands out as a promising solution. To fully benefit from these robotic systems in LMAS, offloading computationally intensive tasks from mobile manipulators to edge computing systems is essential. This offloading of computational tasks not only lightens the processing load on individual robots but also enhances AI based perception, improving the overall system capabilities in dynamic manufacturing environments. Achieving these goals requires a robotic edge computing framework that serves as the key to flexible and adaptive mobile manipulation in LMAS. To construct such an edge computing framework, a comprehensive set of building blocks is required. These building blocks include a powerful edge system with high processing power, sensor-equipped mobile manipulators with the ability to perceive the environment, and a robust edge-to-robot connectivity. A comprehensive software stack, including software modules for localization and navigation in dynamic assembly environments, AI perception for precise pose estimation of assembly components, and motion planning for interaction between manipulators and assembly components, is crucial. Furthermore, virtualization techniques, a comprehensive deployment strategy, and a detailed description of robot hardware, site, and resources are essential. The proposed edge computing framework presents a solution that addresses mobile manipulators in LMAS and paves the way towards advanced industrial automation. Through implementation in a research assembly environment, the realized proof-of-concept showcased the feasibility of the proposed edge computing framework in a real-world pick-and-place scenario, highlighting its potential to enhance adaptivity and flexibility. There is a potential to refine and expand the framework to accommodate a broader range of industrial applications and streamline diverse manufacturing processes through the integration of mobile manipulators and edge computing within industrial settings.

Online Adaptive Method for Obtaining High-Precision Spherical Joint Positions With the Lower Internal Force Assembly of Large-Scale Aircraft Components

Online Adaptive Method for Obtaining High-Precision Spherical Joint Positions With the Lower Internal Force Assembly of Large-Scale Aircraft Components

An Approach for Expulsion Predicting in Resistance Spot Welding

Resistance Spot Welding (RSW) plays a pivotal role in the assembly of automotive body components. During the process, undesirable expulsions can occur, which compromise the quality of the welds and lead to cost-intensive manual rework. In the presented approach, we train Machine Learning (ML) and Deep Learning (DL) models to predict a probability for the occurrence of expulsions for future spot welds. Our approach is based on a real-world data set that stems from the dynamic and complex environment of a series production line. This, in contrast to laboratory data, ensures the applicability of the proposed method in an industrial setting. Our best-performing model is able to predict expulsion with an accuracy of 95.41%. This allows an adjustment of the process before the expulsion occurs, reducing rework, production costs, and time.

Co-encapsulation of organic polymers and inorganic superparamagnetic iron oxide colloidal crystals requires matched diffusion time scales.

Nanoparticles (NPs) that contain both organic molecules and inorganic metal or metal oxide colloids in the same NP core are "composite nanoparticles" which are of interest in many applications, particularly in biomedicine as "theranostics" for the combined delivery of colloidal diagnostic imaging agents with therapeutic drugs. The rapid precipitation technique Flash NanoPrecipitation (FNP) enables continuous and scalable production of composite nanoparticles with hydrodynamic diameters between 40-200 nanometers (nm) that contain hydrophobic superparamagnetic iron oxide primary colloids. Composite NPs co-encapsulate these primary colloids (diameters of 6 nm, 15 nm, or 29 nm), a fluorescent dye (600 Daltons), and poly(styrene) homopolymer (1800, 50 000, or 200 000 Daltons) with NPs stabilized by a poly(styrene)-block-poly(ethylene glycol) (1600 Da-b-5000 Da) block copolymer. Nanoparticle assembly in FNP occurs by diffusion limited aggregation of the hydrophobic core components followed by adsorption of the hydrophobic block of the stabilizing polymer. The hydrodynamic diameter mismatch between the collapsed organic species and the primary colloids (0.5-5 nm versus 6-29 nm) creates a diffusion-aggregation time scale mismatch between components that can lead to nonstoichiometric co-encapsulation in the final nanoparticles; some nanoparticles are composites with primary colloids co-encapsulated alongside organics while others are devoid of the primary colloids and contain only organic species. We use a magnetic capture process to separate magnetic composite nanoparticles from organic-only nanoparticles and quantify the amount of iron oxide colloids and hydrophobic fluorescent dye (as a proxy for total hydrophobic polymer content) in the magnetic and nonmagnetic fractions of each formulation. Analysis of the microstructure in over 1100 individual nanoparticles by TEM imaging and composition measurements identifies the conditions that produce nonstoichiometric composite NP populations without co-encapsulated magnetic iron oxide colloids. Stoichiometric magnetically responsive composite NPs are produced when the ratio of characteristic diffusion-aggregation time scales between the inorganic primary colloid and the organic core component is less than 30 and all NPs in a dispersion contain organic and inorganic species in approximately the same ratio. These rules for assembly of colloids and organic components into homogeneous composite nanoparticles are broadly applicable.

Protein assemblies in the Arabidopsis thaliana chloroplast compartment.

Equipped with a photosynthetic apparatus that uses the energy of solar radiation to fuel biosynthesis of organic compounds, chloroplasts are the metabolic factories of mature leaf cells. The first steps of energy conversion are catalyzed by a collection of protein complexes, which can dynamically interact with each other for optimizing metabolic efficiency under changing environmental conditions. For a deeper insight into the organization of protein assemblies and their roles in chloroplast adaption to changing environmental conditions, an improved complexome profiling protocol employing a MS-cleavable cross-linker is used to stabilize labile protein assemblies during the organelle isolation procedure. Changes in protein:protein interaction patterns of chloroplast proteins in response to four different light intensities are reported. High molecular mass assemblies of central chloroplast electron transfer chain components as well as the PSII repair machinery react to different light intensities. In addition, the chloroplast encoded RNA-polymerase complex was found to migrate at a molecular mass of ~8 MDa, well above its previously reported molecular mass. Complexome profiling data produced during the course of this study can be interrogated by interested readers via a web-based online resource (https://complexomemap.de/projectsinteraction-chloroplasts).

Coordination and optimization decision of assembly building supply chain under supply disruption risk

Assembly buildings, in the context of the low-carbon transformation of the construction industry, achieve superior outcomes in terms of carbon emission reduction, enhancement of building uniformity, and optimization of resource utilization as compared to traditional buildings. However, the supply chain for assembly building is marked by a significant susceptibility to risk and a need for timely fulfillment of requirements. This paper examines the risk of disruption and capacity limitations in the assembly building supply chain resulting from supply disruptions. It establishes a three-tier supply chain for assembly buildings, including primary component suppliers, backup suppliers, assembly manufacturers, and retailers. The study compares the optimal decision-making and coordination strategies of the supply chain members under centralized, decentralized, and joint agreements. The supply chain dual-source procurement decision coordination model is constructed by incorporating capacity constraints and analyzing the effects of supply disruption probability, repurchase coefficient, revenue sharing coefficient, cost, and other parameters on the expected profits of the supply chain members using arithmetic simulation. Research has indicated that when the likelihood of a disturbance occurring rises, the anticipated financial gain for the main provider decreases, while the predicted financial gain for the secondary supplier increases. The implementation of a collaborative agreement between the assembly maker and the parts backup provider would result in much greater anticipated profits compared to the decentralized decision-making approach. The impact of the revenue sharing coefficient on the predicted earnings of retailers and assembly manufacturers is more significant compared to the repurchase coefficient. The selection bias between NA and NB techniques under capacity constraints mostly arises from the assertiveness of the wholesale asking prices of inexpensive component suppliers, leading assembly manufacturers to increasingly prefer the NA option. This paper's research successfully achieves the contractual coordination of the assembly building supply chain, enhances the resilience of the assembly building supply chain, and promotes the long-term sustainable development of the assembly building supply chain.

ЗАСТОСУВАННЯ ПРИНЦИПІВ ЦИРКУЛЯРНОЇ ЕКОНОМІКИ ПРИ ВИРОБНИЦТВІ АВТОМОБІЛІВ: ДОСВІД ПРОВІДНИХ ЄВРОПЕЙСЬКИХ АВТОКОНЦЕРНІВ

This article is part of a study of the trend of changes in the automotive industry, other industries, logistics and electricity that is currently taking place in the world and is significantly changing the global economy. It reflects modern approaches to automotive production based on environmental protection throughout the entire car production cycle – from manufacturing to waste recycling and reuse of materials, i.e. the implementation of circular economy principles. These processes are in line with the general trend of reducing CO2 emissions to zero from both the use of transport and its production and disposal. To this end, leading European automakers are already implementing zero-waste and carbon-free production. This article examines how to achieve this and what methods are most effective. The challenge is to identify the most effective methods of zero-carbon car production to reduce CO2 emissions during production. After all, the automotive industry has many production, logistics and ancillary processes that have an impact on the environment. This diversity of raw materials is compounded by the wide range of parts they are used in. In addition, automotive production requires the assembly of components. All of these processes require significant energy consumption to operate plants that emit significant carbon emissions. Therefore, sustainability in the automotive industry is achieved through a large number of innovations and implementations. The purpose of the article is to study the main methods of production of passenger cars of such brands as Audi, BMW, Mercedes-Benz, Renault, Skoda, Volvo, and to analyse the most efficient methods that ensure carbon-free production. Conclusions were drawn on the effectiveness of these methods and the most advanced and efficient ones were identified. The study shows that leading automakers can achieve carbon-free production in the coming years to meet the EU's commitments to reduce its carbon footprint under the Fit for 5 programme. This is achieved through the use of energy-saving technologies, green energy, and recycling of used materials.

"Literature Review: Customer Relationship In New Product Development"

Meeting customer expectations are vital for any firm to grow. Engaging the customers in any new product development provides customer satisfaction and connects to the society. Based on the necessity, customer engagement can be made online through social media or in person. However, involving customer’s, receiving their feedback on, and functioning the product attracts to many customers, users, and stakeholders. Having good customer interaction does not mean the customers stick to the brand or the product. A continuous effort must be made by the consumers to have a strong connect with the customers to enhance the growth of the business. There are many variables for consumers to drive on this customer interaction and it varies from each customer. Customers should feel overwhelmed with the time, money and effort spent in purchasing the product. Customer engagement and involvement in any new product development process is crucial. For the product to be launched as per the schedule, meeting the customer requirements needs good support from supplier’s as they play an important role in supplying the components for assembly into the product. A good customer supplier relation helps in strengthening the firm’s performance, delivering a quality product with subsided transactional cost. Many studies have been made keen on the customer relationship on new product development, therefore many researchers proposed that customer satisfaction could be considered as the major component for a successful launch of a product to market. The study in this paper provides a thorough review of customer relationship with supplier and their interaction with consumers on a new product development and how companies adapt suitable approaches to engage and involve customers.

Transcriptional alterations of the resistant potato genotype ‘Cruza 148’ in response to Ralstonia solanacearum infection

AbstractRalstonia solanacearum, a highly destructive phytopathogen causing bacterial wilt disease, poses a substantial risk to the potato value chain, putting global food security at risk and impeding potato production. ‘Cruza 148’, a locally adapted potato genotype, has been reported to exhibit resistance when cultivated in areas with a background of bacterial wilt occurrences. This study aimed to acquire a deeper understanding of the factors influencing resistance and susceptibility in ‘Cruza 148’ and ‘Shangi’ potato genotypes respectively. To achieve this, RNA‐seq was deployed to detect DEGs in ‘Cruza 148’ and ‘Shangi’ potato genotypes at 6 h, 24 h, 48 h, and 72 h post‐inoculation with Ralstonia solanacearum. A total of 54.2% of the DEGs were upregulated and 45.8% were downregulated in the roots of the ‘Cruza 148’ potato genotype, while 45.5% and 54.5% of DEGs were upregulated and downregulated in the roots of the susceptible potato genotype ‘Shangi’ respectively. The gene ontology (GO) enrichment analysis indicated that the ‘Cruza 148’ genotype consistently displayed the ‘defence response’ category throughout every stage of infection. The analysis of enriched GO terms revealed 225 terms, with 132 related to biological processes, 16 linked to cellular components and 12 linked to molecular functions. The ‘Cruza 148’ genotype had the highest gene counts in peptide metabolic processes and cellular component assembly, while the ‘Shangi’ genotype had the greatest number of gene counts that responded to chemicals and cellular component assembly. Defence genes identified, included leucine‐rich repeat protein, MYB transcription factor, glucan endo‐1,3‐beta‐glucosidase, serine/threonine‐protein kinase, ethylene‐responsive transcriptional coactivator and disease resistance protein, which could help explain the mechanisms and pathways of resistance to R. solanacearum. This study presents a fundamental understanding of the transcriptional alterations that occur during pathogen interactions with potato. It will also assist in identifying potential useful genes induced during the resistance and susceptibility processes.

Contact-based pose detection method for small components to optimise the digital twin-driven robotic assembly process

The robotic assembly has become pivotal in manufacturing, demanding precise pose detection of assembly components for efficient operations. This paper presents a contact-based pose detection method tailored for digital twin-based optimisation for the robotic assembly process, focusing on small component assembly challenges. The proposed technique achieves robust pose estimation by leveraging a strain gauge load cell-based calibration method. Experimental validation demonstrates close alignment between induced and measured errors, showcasing the efficacy of the method in mitigating assembly challenges. Despite minor deviations, the approach outperforms traditional vision-based methods, promising enhanced efficiency in robotic assembly tasks. Further refinement could bolster accuracy, fostering advanced robotic assembly capabilities.