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Abstract A key problem of the construction of fully electric aircraft is the limited energy density of battery packs. It is generally accepted that this can only be overcome via new, denser battery chemistry together with a further increase in the efficiency of power utilization. One appealing approach for achieving the latter is using laser-assisted filler-based joining technologies, which offers unprecedented flexibility for achieving battery cell connections with the least possible electrical loss. This contribution presents our results on the effect of various experimental and process parameters on the electrical and mechanical properties of the laser-formed bond.

Abstract This paper presents a machine learning application of the force/torque sensor in a human-robot collaborative manufacturing scenario. The purpose is to simplify the programming for physical interactions between the human operators and industrial robots in a hybrid manufacturing cell which combines several robotic applications, such as parts manipulation, assembly, sealing and painting, etc. A multiclass classifier using Light Gradient Boosting Machine (LightGBM) is first introduced in a robotic application for discriminating five different contact states w.r.t. the force/torque data. A systematic approach to train machine-learning based classifiers is presented, thus opens a door for enabling LightGBM with robotic data process. The total task time is reduced largely because force transitions can be detected on-the-fly. Experiments on an ABB force sensor and an industrial robot demonstrate the feasibility of the proposed method.

Abstract A large amount of heat generated in the engineering compartment in a hovering helicopter may lead to premature degradation of inner skin of its engine cowling and cause serious failure on the engine cowling. This study proposes a solution of improving heat resistance of the helicopter engine cowlings by replacing the currently used intumescent coating with a ceramic coating material, Cerakote C-7700Q. Oven and flame tests were designed and conducted to evaluate the heat resistance of Cerakote C-7700Q. The test results show that the currently used painting scheme of the engine cowlings failed the 220°C oven test while after replacing the epoxy seal coat with the Cerakote, the new painting system passed the 220°C test in regards to painting bubbling. Based on that, a new painting scheme with C-7700Q implemented was recommended.

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Abstract Knurling joint applied in assembled camshaft has developed rapidly in recent years, which have exhibited great advantages against conventional joint methods in the aspects of automation, joint precision, thermal damage, noise, and near net shape forming. Both quality of assembly process and joint strength are the key requirements for manufacturing a reliable assembled camshaft. In this article, a finite element predictive approach including three subsequent models (knurling, press-fit and torsion strength) has been established. Johnson-Cook material model has been used to simulate the severe plastic deformation of the material. The residual stress field calculated from the knurling process was transferred as initial condition to the press-fit model to predict the press-fit load. The predicted press-fit load, torque strength and displacement of cam profile before failure were calculated.

Abstract Heavy commercial vehicles play an important role in creating the trade and economic balance of countries. Also, the durability and safety of heavy commercial vehicles come to the fore. Heavy commercial vehicles consist of two parts. These are the chassis area with the equipment that allows the vehicle to move and the cabin section where the driver is located. The cabin area is the most important area that ensures the highest level of driver safety. Considering that the production of trucks is increasing day by day, it is inevitable for companies to increase their R&D activities in the field of cabin and cabin suspension systems for much safer, durable, and comfortable trucks. This study aims to determine the safe torque value of the fasteners and their assembly sequence of the Cab Suspension Console, which is one of the most important connection parts in a truck and which can cause a fatal accident by breaking.

Abstract Industry 4.0 is expected to revolutionize product development and, in particular, manufacturing systems. Cyber-physical production systems and digital twins of the product and process already provide the means to predict possible future states of the final product given the current production parameters. With the advent of further data integration coupled with the need for autonomous decision-making, methods are needed to make decisions in real time and in an environment of uncertainty in both the possible outcomes and in the stakeholders’ preferences over them. This article proposes a method of autonomous decision-making in data-intensive environments, such as a cyber-physical assembly system. Theoretical results in group decision-making and utility maximization using mixture distributions are presented. This allows us to perform calculations on expected utility accurately and efficiently through closed-form expressions, which are also provided.

Abstract Decision analysis (DA), a well-established discipline in business and engineering, is entering another domain of application due to the advent of Industry 4.0. DA enables optimal decisions by finding system parameters that maximize the utility, or in the presence of uncertainty the expected utility, from the attributes of a system. Whether there is a single decision maker or all decision makers have uniform preferences, determining risk behavior and the resulting utility is well developed in the existing literature. However, variability in preferences has not been satisfactorily addressed. This gap gains added significance in the face of the demands of Industry 4.0 where cyberphysical production systems must drive autonomous decision-making on the factory floor. The decisions must accommodate a distribution of customer and designer preferences, including production auditors within the organization.

Abstract During aircraft wing assembly, machined fiberglass shims are often used between mating parts to compensate for inherent geometric variability due to manufacturing. At present, fiberglass shims for large aerospace structures, such as shims attached to wing ribs, are manufactured either manually or by precision machining, both of which pose a challenge due to tight tolerance requirements and wide geometric variations in the aircraft structures. Relative to articulated arm industrial robots, gantry-style computer numerical control (CNC) machines are costly, consume large footprints, and are inflexible in the application. Therefore, industrial robots are viewed as potential candidates to replace these gantry systems to facilitate metrology, shim machining, and permanent joining of aircraft structure, with all these processes taking place in the assembly process step.

Abstract Additive manufacturing (AM) technologies can produce lighter parts; reduce manual assembly processes; reduce the number of production steps; shorten the production cycle; significantly reduce material consumption; enable the production of prostheses, implants, and artificial organs; and produce end-user products since it is used in many sectors for many reasons; it has also started to be used widely, especially in the field of aerospace. In this study, polylactic acid (PLA) was preferred for the antenna substrate because it is environmentally friendly, easy to recycle, provides convenience in production design with a three-dimensional (3D) printer, and is less expensive compared to other available materials. Copper (Cu) tape and graphene filament were employed for the antenna patch component due to their benefits.