The Factory of the Future

A brief history of aircraft production techniques is given. A flexible machining cell is then described. It is a computer controlled system capable of performing 4-axis machining part cleaning, dimensional inspection and materials handling functions in an unmanned environment. The cell was designed to: allow processing of similar and dissimilar parts in random order without disrupting production; allow serial (one-shipset-at-a-time) manufacturing; reduce work-in-process inventory; maximize machine utilization through remote set-up; maximize throughput and minimize labor

A flexible manufacturing system for lawnmower cutting cylinders

The thesis is concerned with the conception and design of a FLEXIBLE MANUFACTURING SYSTEM (FMS) for the automation of the manufacture of lawnmower cutting cylinders at Suffolk Lawnmowers Ltd. A review of FMS definitions, planning methods and current systems is carried out for the development of a suitable FMS configuration for the final stages of manufacture of grass cutting cylinders having 21 different design specifications. This involves examination of the capabilities of robotics and microcontrollers to automate the technologies used in cylinder production. The company's current manual batch production system is analysed to determine the suitable form and requirements of the FMS. This includes analyses of annual volumes, throughputs, batch sizes, product and process mixes. Long term objectives to automate the system are identified from which short term objectives are derived. The FMS recommended for immediate development encompasses the short term objectives for the welding, hardening, grinding and transfer processes of 8 cutting cylinder specifications. It is shown that the MIG (Argon/C02) are welding, progressive flame hardening and wide-face cylindrical grinding processes can be developed successfully to automate cylinder production. The recommended system integrates these processes into an FMS through the'automatic handling of cylinders (through three process routes) by a robotic manipulator utilising a double gripper. 'A robotic welding station, manually loaded, is also recommended. ' The system is controlled overall by a 32K microcontroller with the process machines individually controlled by programmahle logic controllers with up to 6K of memory each. The economic appraisal of the FMS indicates a 4.4 year payback based on direct labour and material cost savings. The company's application for grant aid to implement the FMS design has led to an offer of a Department of Industry grant to cover 50% of all capital and revenue costs. The grant of £166,943 reduces the payback period to 2.3 years

Improving robotic machining accuracy through experimental error investigation and modular compensation

Machining using industrial robots is currently limited to applications with low geometrical accuracies and soft materials. This paper analyzes the sources of errors in robotic machining and characterizes them in amplitude and frequency. Experiments under different conditions represent a typical set of industrial applications and allow a qualified evaluation. Based on this analysis, a modular approach is proposed to overcome these obstacles, applied both during program generation (offline) and execution (online). Predictive offline compensation of machining errors is achieved by means of an innovative programming system, based on kinematic and dynamic robot models. Real-time adaptive machining error compensation is also provided by sensing the real robot positions with an innovative tracking system and corrective feedback to both the robot and an additional high-dynamic compensation mechanism on piezo-actuator basis

In-process calibration of a non-destructive testing system used for in-process inspection of multi-pass welding

In multi-pass welding, there is increasing motivation to move towards in-process defect detection to enable real-time repair; thus avoiding deposition of more layers over a defective weld pass. All defect detection techniques require a consistent and repeatable approach to calibration to ensure that measured defect sizing is accurate. Conventional approaches to calibration employ fixed test blocks with known defect sizes, however, this methodology can lead to incorrect sizing when considering complex geometries, materials with challenging microstructure, and the significant thermal gradients present in materials during the inter-pass inspection period. To circumvent these challenges, the authors present a novel approach to calibration and introduce the concept of in-process calibration applied to ultrasonic Non-Destructive Testing (NDT). The new concept is centred around the manufacturing of a second duplication sample, containing intentionally-embedded tungsten inclusions, with identical process parameters as the main sample. Both samples are then inspected using a high-temperature robotic NDT process to allow direct comparative measurements to be established between the real part and the calibration sample. It is demonstrated that in-process weld defect detection using the in-process calibration technique can more reliably identify defects in samples which would otherwise pass the acceptance test using a traditional calibration

Robotic Training for the Integration of Material Performances in Timber Manufacturing

The research focuses on testing a series of material-sensitive robotic training methods that flexibly extend the range of subtractive manufacturing processes available to designers based on the integration of manufacturing knowledge at an early design stage. In current design practices, the lack of feedback information between the different steps of linear design workflows forces designers to engage with only a limited range of standard materials and manufacturing techniques, leading to wasteful and inefficient solutions. With a specific focus on timber subtractive manufacturing, the work presented in this thesis addresses the main issue hindering the utilisation of non-standard tools and heterogeneous materials in design processes which is the significant deviation between what is prescribed in the digital design environment and the respective fabrication outcome. To begin, it has been demonstrated the extent to which the heterogeneous properties of timber affect the outcome of the robotic carving process beyond the acceptable tolerance thresholds for design purposes. Resting on this premise, the devised strategy to address such a material variance involved capturing, transferring, augmenting and integrating manufacturing knowledge through the collection of real- world fabrication data, both by human experts and robotic sessions, and training of machine learning models (i.e. Artificial Neural Networks) to achieve an accurate simulation of the robotic manufacturing task informed by specific sets of tools affordances and material behaviours. The results of the training process have demonstrated that it is possible to accurately simulate the carving process to a degree sufficient for design applications, anticipating the influence of material and tool properties on the carved geometry. The collaborations with the industry partners of the project, ROK Architects (Zürich) and BIG (Copenhagen), provided the opportunity to assess the different practical uses and related implications of the tools in a real-world scenario following an open-ended and explorative approach based on several iterations of the full design-to-production cycle. The findings have shown that the devised strategy supports decision-making procedures at an early stage of the design process and enables the exploration of novel, previously unavailable, solutions informed by material and tool affordances