Within manufacturing, measurements are used to make decisions related to product verification and process control. The selection of production machines and instruments involves a trade-off to achieve the required accuracy while minimizing cost. Similarly, deciding on the level of confidence at which products are rejected is a trade-off between the cost of rejecting acceptable parts and the cost of passing substandard products to the customer. These trade-offs can only be optimized if the uncertainties are fully understood. Currently multiple methodologies are used to understand uncertainties and variation within manufacturing, such as measurement systems analysis (MSA), statistical process control (SPC), and uncertainty evaluation. The industry lacks a unified approach that provides a complete understanding of uncertainty. This means that optimal decisions cannot be made to maximize the profitability of production systems. NOTE: SAE EDGE™ Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry. The goal of SAE EDGE™ Research Reports is to stimulate discussion and work in the hope of promoting and speeding resolution of identified issues. SAE EDGE™ Research Reports are not intended to resolve the issues they identify or close any topic to further scrutiny. Click here to access the full SAE EDGETM Research Report portfolio. https://doi.org/10.4271/EPR2019003

Currently, inaccuracies in machine tools are often not detected until after they have produced nonconforming parts, causing reworking or scrap. For high-value aerospace parts, a single rejected part is a significant cost. Low-value parts are often inspected less frequently, allowing many nonconforming parts to be produced before the issue is detected, also resulting in high cost. The alternative to relying on part inspection is to run frequent tests on the machine itself, but established calibration and health-check processes take between 20 minutes and several days. Emerging rapid and automated verification (RAV) processes enable machine tools to check their performance automatically in just a few minutes. These RAV processes can be performed frequently throughout the day, allowing machines to operate without human intervention for long periods of time. When an issue is detected, the machine may be able to recalibrate and then continue automatically. Where this is not possible, the machine stops and provides diagnostic information enabling the operator to efficiently get the machine back into production. For many machines, especially smaller ones, artifact probing is the most cost-effective and easily implemented method. Combined with probing of roughing cuts, it can also verify spindle and dynamic errors at the micrometer level. Inertial measurement has a lot of potential to provide continuous monitoring during operations, and significant research efforts are therefore justified to validate and improve diagnostic capability. Noncontact triple-probing of spheres can provide highly accurate RAV while also enabling some compensation to be achieved in a very rapid way. This equipment is costly when dedicated to each machine for RAV but may be justified for very high-value machines and processes. NOTE: SAE EDGE™ Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry. The goal of SAE EDGE™ Research Reports is to stimulate discussion and work in the hope of promoting and speeding resolution of identified issues. SAE EDGE™ Research Reports are not intended to resolve the issues they identify or close any topic to further scrutiny. https://doi.org/10.4271/EPR2020019

Increased production rates and cost reduction are affecting manufacturing in all mobility industry sectors. One enabling methodology that could achieve these goals in the burgeoning “Industry 4.0” environment is the optimized deterministic assembly (DA) approach. It always forms the same final structure and has a strong link to design-for-assembly and design-for-automation. The entire supply chain is considered, with drastic savings at the final assembly line level through recurring costs and lead-time reduction. Unsettled Technology Areas in Deterministic Assembly Approaches for Industry 4.0 examines the evolution of previous assembly principles that lead up to and enable the DA approach, related simulation methodologies, and undefined and unsolved links between these domains. Click here to access the full SAE EDGETM Research Report portfolio. https://doi.org/10.4271/EPR2021018

Cost reduction and increasing production rates are driving automation of aerospace manufacturing. Articulated serial robots may replace bespoke gantry automation or human operations. Improved accuracy is key to enabling operations such as machining, additive manufacturing (AM), composite fabrication, drilling, automated program development, and inspection. New accuracy standards are needed to enable process-relevant comparisons between robotic systems. Accuracy can be improved through calibration of kinematic and joint stiffness parameters, joint output encoders, adaptive control that compensates for thermal expansion, and feedforward control that compensates for hysteresis and external loads. The impact of datuming could also be significantly reduced through modeling and optimization. Highly dynamic end effectors compensate high-frequency disturbances using inertial sensors and reaction masses. Global measurement feedback is a high-accuracy turnkey solution, but it is costly and has limited capability to compensate dynamic errors. Local measurement feedback is a mature, affordable, and highly accurate technology where the robot is required to position or align relative to some local feature. Locally clamped machine tools are an alternative approach that can utilize the flexibility of industrial robots while also enabling high-quality machined surfaces. Hybrid high-accuracy control strategies will be required for many processes. NOTE: SAE EDGE™ Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry. The goal of SAE EDGE™ Research Reports is to stimulate discussion and work in the hope of promoting and speeding resolution of identified issues. SAE EDGE™ Research Reports are not intended to resolve the issues they identify or close any topic to further scrutiny. Click here to access the full SAE EDGETM Research Report portfolio. https://doi.org/10.4271/EPR2019010

Additive manufacturing (AM) is currently being used to produce many certified aerospace components. However, significant advantages of AM are not exploited due to unresolved issues associated with process control, feedstock materials, surface finish, inspection, and cost. Components subject to fatigue must undergo surface finish improvements to enable inspection. This adds cost and limits the use of topology optimization. Continued development of process models is also required to enable optimization and understand the potential for defects in thin-walled and slender sections. Costs are high for powder-fed processes due to material costs, machine costs, and low deposition rates. Costs for wire-fed processes are high due to the extensive postprocess machining required. In addition, these processes are limited to low-complexity features. Incremental improvements in all of these areas are being made, but a step change could potentially be achieved by hybrid processes, which use wire feedstock to deposit the bulk of the part and powder for fine detail. NOTE: SAE EDGE™ Research Reports are intended to identify and illuminate key issues in emerging, but still unsettled, technologies of interest to the mobility industry. The goal of SAE EDGE™ Research Reports is to stimulate discussion and work in the hope of promoting and speeding resolution of identified issues. SAE EDGE™ Research Reports are not intended to resolve the issues they identify or close any topic to further scrutiny. Click here to access the full SAE EDGETM Research Report portfolio. https://doi.org/10.4271/EPR2019008

In its entirety, automation is part of an integrated, multi-disciplinary product development process including the design, process, production, logistics, and systems approach—it depends on all these areas, but it also influences them as well. Automation in aerospace manufacturing is present throughout the entire supply chain, from elementary part manufacturing at suppliers up to final assembly, and a clear understanding of all the benefits (and drawbacks) of automation would help designers and engineers select the right designs for and levels of automation. The Right Level of Automation Within Industry 4.0 examines all impacts of automation that should be known by designers, manufacturers, and companies before investments in automation-related decisions are made—regardless of the which industry they work in. The process and the set of criteria discussed in this report will help decision makers select the right level of automation. Click here to access the full SAE EDGETM Research Report portfolio. https://doi.org/10.4271/EPR2022013

The aerospace manufacturing industry is, in many ways, one of the most sophisticated commercial manufacturing systems in existence. It uses cutting-edge materials to build highly complex, safety-critical structures and parts. However, it still relies largely upon human skill and dexterity during assembly. There are increasing efforts to introduce automation, but uptake is still relatively low. Why is this and what needs to be done? Some may point to part size or the need for accuracy. However, as with any complex issue, the problems are multifactorial. There are no right or wrong answers to the automation conundrum and indeed there are many contradictions and unsettled aspects still to be resolved. Unsettled Issues on the Viability and Cost-Effectiveness of Automation in Aerospace Manufacturing builds a comprehensive picture of industry views and attitudes backed by technical analysis to answer some of the most pressing questions facing robotic aerospace manufacturing. Click here to access the full SAE EDGETM Research Report portfolio. https://doi.org/10.4271/EPR2021005