Robotic belt finishing with process control for accurate surfaces

The aerospace industry still relies on manual processes for finish applications, which can be a tedious task. In recent years, robotic automation has gained interest due to its flexibility and adaptability to provide solutions to this issue. However, these processes are difficult to automate, as the material removal rate can vary due to changes in the process variables. This work proposes an approach for automatically modeling the material removal process based on experimental data in a robotic belt grinding application. The methodology concerns the measurement of the removed mass of a test part during a finishing process using an automatic precision measurement system. Then, experimental models are used to develop a control algorithm for continuous material removal that maintains a uniform finishing process by regulating the robot’s feed rate. Next, the results for various experimental material removal models under different process conditions are presented, showing the process parameter’s influence on the removal capacity. Finally, the proposed control algorithm is validated, achieving a constant material removal rate.This research was funded by the EUROSTARS GRINDBOT project (grant number E!115077) and the Government of Navarre Doctorados Industriales program (grant number 0011-1408-2021-000021)

Geometrical Error Analysis and Correction in Robotic Grinding

The use of robots in industrial applications has been widespread in the manufacturing tasks such as welding, finishing, polishing and grinding. Most robotic grinding focus on the surface finish rather than accuracy and precision. Therefore, it is important to advance the technology of robotic machining so that more practical and competitive systems can be developed for components that have accuracy and precision requirement. This thesis focuses on improving the level of accuracy in robotic grinding which is a significant challenge in robotic applications because of the kinematic accuracy of the robot movement which is much more complex than normal CNC machine tools. Therefore, aiming to improve the robot accuracy, this work provides a novel method to define the geometrical error by using the cutting tool as a probe whilst using Acoustic Emission monitoring to modify robot commands and to detect surfaces of the workpiece. The work also includes an applicable mathematical model for compensating machining errors in relation to its geometrical position as well as applying an optimum grinding method to motivate the need of eliminating the residual error when performing abrasive grinding using the robot. The work has demonstrated an improved machining precision level from 50µm to 30µm which is controlled by considering the process influential variables, such as depth of cut, wheel speed, feed speed, dressing condition and system time constant. The recorded data and associated error reduction provide a significant evidence to support the viability of implementing a robotic system for various grinding applications, combining more quality and critical surface finishing practices, and an increased focus on the size and form of generated components. This method could provide more flexibility to help designers and manufacturers to control the final accuracy for machining a product using a robot system

Robotic Grinding Process of Turboprop Engine Compressor Blades with Active Selection of Contact Force

The work presents a robotic system for grinding the blades of a turboprop engine compressor. The proprietary conceptual solution includes a data acquisition system based on a robotic 3D scanner, a neural decision system and a robot performing a grinding process with force control. The contact force of the tool to the blade was assumed as a variable and controlled process parameter. A neural network was used to generate the contact force on the basis of measured machining allowances on the blade. A virtual grid of several dozen regularly spaced points was placed on the surface of the blade. The neural network was learned the allowance-force dependence for the selected points, making it possible to select the proper contact force on the surface to be machined. The developed algorithm for the process of robotic grinding of the blades takes into account the necessity of ongoing quality control of the processing and the introduction of corrections in the process

Research on Parametric Model for Surface Processing Prediction of Aero-Engine Blades

This paper presented a method for establishing a blade surface machining prediction model based on a parametric model. The abrasive grain state of the grinding tool was divided into initial wear stage, stable wear stage and sharp wear stage. Based on this, a parametric prediction model of engine blade surface material removal was established. In this paper, the simulation of blade surface machining was carried out. In this work, the blade was divided into several sections according to the direction from the blade root to the blade tip. A certain curve of the outer contour was fitted with a specific arc to reduce the calculation amount. Through a series of simulation calculations, the expressions of the above parametric prediction model were obtained, and several experiments were carried out to verify the feasibility of the prediction model, and the results were analyzed

Development of an integrated robotic polishing system

This thesis presents research carried out as part of a project undertaken in fulfilment of the requirements of Loughborough University for the award of Philosophical Doctorate. The main focus of this research is to investigate and develop an appropriate level of automation to the existing manual finishing operations of small metallic components to achieve required surface quality and to remove superficial defects. In the manufacturing industries, polishing processes play a vital role in the development of high precision products, to give a desired surface finish, remove defects, break sharp edges, extend the working life cycle, and meet mechanical specification. The polishing operation is generally done at the final stage of the manufacturing process and can represent up to a third of the production time. Despite the growth automated technology in industry, polishing processes are still mainly carried out manually, due to the complexity and constraints of the process. Manual polishing involves a highly qualified worker polishing the workpiece by hand. These processes are very labour intensive, highly skill dependent, costly, error-prone, environmentally hazardous due to abrasive dust, and - in some cases - inefficient with long process times. In addition, the quality of the finishing is dependent on the training, experience, fatigue, physical ability, and expertise of the operator. Therefore, industries are seeking alternative solutions to be implemented within their current processes. These solutions are mainly aimed at replacing the human operator to improve the health and safety of their workforce and improve their competitiveness. Some automated solutions have already been proposed to assist or replace manual polishing processes. These solutions provide limited capabilities for specific processes or components, and a lack of flexibility and dexterity. One of the reasons for their lack of success is identified as neglecting the study and implementing the manual operations. This research initially hypothesised that for an effective development, an automated polishing system should be designed based on the manual polishing operations. Therefore, a successful implementation of an automated polishing system requires a thorough understanding of the polishing process and their operational parameters. This study began by collaborating with an industrial polishing company. The research was focused on polishing complex small components, similar to the parts typically used in the aerospace industry. The high level business processes of the polishing company were capture through several visits to the site. The low level operational parameters and the understanding of the manual operations were also captured through development of a devices that was used by the expert operators. A number of sensors were embedded to the device to facilitate recording the manual operations. For instance, the device captured the force applied by the operator (avg. 10 N) and the cycle time (e.g. 1 pass every 5 sec.). The capture data was then interpreted to manual techniques and polishing approaches that were used in developing a proof-of-concept Integrated Robotic Polishing System (IRPS). The IRPS was tested successfully through several laboratory based experiments by expert operators. The experiment results proved the capability of the proposed system in polishing a variety of part profiles, without pre-existing geometrical information about the parts. One of the main contributions made by this research is to propose a novel approach for automated polishing operations. The development of an integrated robotic polishing system, based on the research findings, uses a set of smart sensors and a force-position-by-increment control algorithm, and transpose the way that skilled workers carry out polishing processes

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

Distributed Analytics Framework for Integrating Brownfield Systems to Establish Intelligent Manufacturing Architecture

Intelligent manufacturing otherwise called as smart manufacturing concentrates upon optimising production and processes by making full use of data available. It is regarded as a new manufacturing model where the entire product life cycle can be simplified using various smart sensors, data-driven decision-making models, visualisation, intelligent devices, and data analytics. In the Industry 4.0 era, Industrial Internet of Things (IIoT) architecture platform is required to streamline and secure data transfer between machines, factories, etc. When certain manufacturing industry is equipped with this platform, an intelligent manufacturing model can be achieved. In today’s factories, most machines are brownfield systems and are not connected to any IoT platforms. Thus they cannot provide data or visibility into their performance, health, and optimal maintenance schedules, which would have improved their operational value. This paper attempts to bridge this gap by demonstrating how brownfield equipment can be IIoT enabled and how data analytics can be performed at the edge as well as cloud using two simple use cases involving industrial robot on the abrasive finishing process. The focus of this paper is on how a scalable data analytics architecture can be built for brownfield machines at the edge as well as the cloud

Conformal polishing approach: Tool footprint analysis

Polishing process is one of the most critical manufacturing processes during a metal part production because it determines the final quality of the product. Free-form surface polishing is a handmade process with lots of rejected parts, scrap generation and time and energy consumption. Two different research lines are being developed: prediction models of the final surface quality parameters and an analysis of the amount of material removed depending on the polishing parameters to predict the tool footprint during the polishing task. This research lays the foundations for a future automatic conformal polishing system. It is based on rotational and translational tool with dry abrasive in the front mounted at the end of a robot. A tool to part concept is used, useful for large or heavy workpieces. Results are applied on different curved parts typically used in tooling industry, aeronautics or automotive. A mathematical model has been developed to predict the amount of material removed in function of polishing parameters. Model has been fitted for different abrasives and raw materials. Results have shown deviations under 20% that implies a reliable and controllable process. Smaller amount of material can be removed in controlled areas of a three-dimensional workpiece

Applying a 6 DoF robotic arm and digital twin to automate fan-blade reconditioning for aerospace maintenance, repair, and overhaul

The UK is home to several major air commercial and transport hubs. As a result, there is a high demand for Maintenance, Repair, and Overhaul (MRO) services to ensure that fleets of aircraft are in airworthy conditions. MRO services currently involve heavy manual labor. This creates bottlenecks, low repeatability, and low productivity. Presented in this paper is an investigation to create an automation cell for the fan-blade reconditioning component of MRO. The design and prototype of the automation cell is presented. Furthermore, a digital twin of the grinding process is developed and used as a tool to explore the required grinding force parameters needed to effectively remove surface material. An integration of a 6-DoF industrial robot with an end-effector grinder and a computer vision system was undertaken. The computer vision system was used for the digitization of the fan-blade surface as well as tracking and guidance of material removal. Our findings reveal that our proposed system can perform material removal, track the state of the fan blade during the reconditioning process and do so within a closed-loop automated robotic work cell