Five-Axis Machine Tool Condition Monitoring Using dSPACE Real-Time System

This paper presents the design, development and SIMULINK implementation of the lumped parameter model of C-axis drive from GEISS five-axis CNC machine tool. The simulated results compare well with the experimental data measured from the actual machine. Also the paper describes the steps for data acquisition using ControlDesk and hardware-in-the-loop implementation of the drive models in dSPACE real-time system. The main components of the HIL system are: the drive model simulation and input – output (I/O) modules for receiving the real controller outputs. The paper explains how the experimental data obtained from the data acquisition process using dSPACE real-time system can be used for the development of machine tool diagnosis and prognosis systems that facilitate the improvement of maintenance activities

Web-based CBR (case-based reasoning) as a tool with the application to tooling selection

Over the past few years, manufacturing companies have had to deal with an increasing demand for feature-rich products at low costs. The pressures exerted on their existing manufacturing processes have lead manufacturers to investigate internet-based solutions, in order to cope with growing competition. The decentralisation phenomenon also came up as a reason to implement networked-application, which has been the starting point for internet/intranet–based systems. Today, the availability of powerful and low cost 3D tools, database backend systems, along with web-based technologies, provides interesting opportunities to the manufacturing community, with solutions directly implementable at the core of their businesses and organisations. In this paper a web-based engineering approach is presented to developing a design support system using case-based reasoning (CBR) technology for helping in the decision-making process when choosing cutting tools. The system aims to provide on-line intelligent support for determining the most suitable configuration for turning operations, based on initial parameters and requirements for the cutting operation. The system also features a user-driven 3D turning simulator which allows testing the chosen insert for several turning operations. The system aims to be a useful e-manufacturing tool being able to quickly and responsively provide tooling data in a highly interactive way

Intelligent Machining Systems

Machining is one of the most widespread manufacturing processes and plays a critical role in industries. As a matter of fact, machine tools are often called mother machines as they are used to produce other machines and production plants. The continuous development of innovative materials and the increasing competitiveness are two of the challenges that nowadays manufacturing industries have to cope with. The increasing attention to environmental issues and the rising costs of raw materials drive the development of machining systems able to continuously monitor the ongoing process, identify eventual arising problems and adopt appropriate countermeasures to resolve or prevent these issues, leading to an overall optimization of the process. This work presents the development of intelligent machining systems based on in-process monitoring which can be implemented on production machines in order to enhance their performances. Therefore, some cases of monitoring systems developed in different fields, and for different applications, are presented in order to demonstrate the functions which can be enabled by the adoption of these systems. Design and realization of an advanced experimental machining testbed is presented in order to give an example of a machine tool retrofit aimed to enable advanced monitoring and control solutions. Finally, the implementation of a data-driven simulation of the machining process is presented. The modelling and simulation phases are presented and discussed. So, the model is applied to data collected during an experimental campaign in order to tune it. The opportunities enabled by integrating monitoring systems with simulation are presented with preliminary studies on the development of two virtual sensors for the material conformance and cutting parameter estimation during machining processes

Design and Validation of Hardware-in-the-Loop Testbed for Proximity Operations Payloads

The research presented here is a new testbed design for CubeSat and payload testing and development. This research demonstrates a low-cost, hardware-in-the-loop testing apparatus for use with university CubeSat programs for testing throughout the different levels of the development process. The average university CubeSat program undergoes very little hardware-in-the-loop testing. Most of the focus is the targeted towards performance testing and environmental testing which occur after completion the development process. This research shows that, for minimal schedule and cost impact, testing can occur early in the development process. The testbed presented here demonstrates suitable accuracy to be used for advanced mission testing and regularly throughout the process until completion. The testbed maintains a low-cost, modular design, and ease of integration into new and existing programs. In addition, some modifications and upgraders are suggested to further increase the performance of the testbed. The success of the testbed can be seen through the implementation of actual satellite telemetry with rendezvous and docking missions, the testbed performance, and the results of that experiment

Automated CNC Tool Path Planning and Machining Simulation on Highly Parallel Computing Architectures

This work has created a completely new geometry representation for the CAD/CAM area that was initially designed for highly parallel scalable environment. A methodology was also created for designing highly parallel and scalable algorithms that can use the developed geometry representation. The approach used in this work is to move parallel algorithm design complexity from an algorithm level to a data representation level. As a result the developed methodology allows an easy algorithm design without worrying too much about the underlying hardware. However, the developed algorithms are still highly parallel because the underlying geometry model is highly parallel. For validation purposes, the developed methodology and geometry representation were used for designing CNC machine simulation and tool path planning algorithms. Then these algorithms were implemented and tested on a multi-GPU system. Performance evaluation of developed algorithms has shown great parallelizability and scalability; and that main algorithm properties are required for modern highly parallel environment. It was also proved that GPUs are capable of performing work an order of magnitude faster than traditional central processors. The last part of the work demonstrates how high performance that comes with highly parallel hardware can be used for development of a next level of automated CNC tool path planning systems. As a proof of concept, a fully automated tool path planning system capable of generating valid G-code programs for 5-axis CNC milling machines was developed. For validation purposes, the developed system was used for generating tool paths for some parts and results were used for machining simulation and experimental machining. Experimental results have proved from one side that the developed system works. And from another side, that highly parallel hardware brings computational resources for algorithms that were not even considered before due to computational requirements, but can provide the next level of automation for modern manufacturing systems

INDUSTRIAL DEVICE INTEGRATION AND VIRTUALIZATION FOR SMART FACTORIES

Given the constant industry growth and modernization, several technologies have been introduced in the shop floor, in particular regarding industrial devices. Each device brand and model usually requires different interfaces and communication protocols, a technological diversity which renders the automatic interconnection with production management software extremely challenging. However, combining key technologies such as machine monitoring, digital twin and virtual commissioning, along with a complete communication protocol like OPC UA, it is possible to contribute towards industrial device integration on a Smart Factory environment. To achieve this goal, several methodologies and a set of tools were defined. This set of tools, as well as facilitating the integration tasks, should also be part of a virtual engineering environment, sharing the same virtual model, the digital twin, through the complete lifecycle of the industrial device, namely the project, simulation, implementation and execution/monitoring/supervision and, eventually, decommissioning phases. A key result of this work is the development of a set of virtual engineering tools and methodologies based on OPC UA communication, with the digital twin implemented using RobotStudio, in order to accomplish the complete lifecycle support of an industrial device, from the project and simulation phases, to monitoring and supervision, suitable for integration in Industry 4.0 factories. To evaluate the operation of the developed set of tools, experiments were performed for a test scenario with different devices. Other relevant result is related with the integration of a specific industrial device – CNC machining equipment. Given the variety of monitoring systems and communication protocols, an approach where various solutions available on the market are combined on a single system is followed. These kinds of all-in-one solutions would give production managers access to the information necessary for a continuous monitoring and improvement of the entire production process

Implementation of Digital Twin-based Virtual Commissioning in Machine Tool Manufacturing

Virtual commissioning is not a new concept; However, it is all the rage with the introduction of Industry 4.0, in the field of product lifecycle management, computer-aided design (CAD), computer-aided manufacturing (CAM), and within the industrial automation programming frameworks. Although, this is a very active area of research and innovation, these technologies have little implementation in the machine tool industry [11]. There is still no integrated simulation environment for virtual commissioning in the market. In this context, digitalisation is a key driver. The aim of this paper is to describe the practice of virtual commissioning in the machine tool manufacturing industry by identifying available solutions in the market and addressing the challenges faced within the machine tool sector. As a result, a digital twin based virtual commissioning solution has been developed at Danobatgroup, the leading machine tool builder in Spain, which is a step forward towards the digitalisation of machine tool manufacturing

Sim-to-Real Reinforcement Learning Framework for Autonomous Aerial Leaf Sampling

Using unmanned aerial systems (UAS) for leaf sampling is contributing to a better understanding of the influence of climate change on plant species, and the dynamics of forest ecology by studying hard-to-reach tree canopies. Currently, multiple skilled operators are required for UAS maneuvering and using the leaf sampling tool. This often limits sampling to only the canopy top or periphery. Sim-to-real reinforcement learning (RL) can be leveraged to tackle challenges in the autonomous operation of aerial leaf sampling in the changing environment of a tree canopy. However, trans- ferring an RL controller that is learned in simulation to real UAS applications is challenging due to the risk of crashes. UAS crashes pose safety risks to the operator and its surroundings which often leads to expensive UAS repairs. In this thesis, we present a Sim-to-Real Transfer framework using a computer numerical control (CNC) platform as a safer, and more robust proxy, before using the controller on a UAS. In addition, our framework provides an end-to-end complete pipeline to learn, and test, any deep RL controller for UAS or any three-axis robot for various control tasks. Our framework facilitates bi-directional iterative improvements to the simulation environment and real robot, by allowing instant deployment of the simulation learned controller to the real robot for performance verification and issue identification. Our results show that we can perform a zero-shot transfer of the RL agent, which is trained in simulation, to real CNC. The accuracy and precision do not meet the requirement for complex leaf sampling tasks yet. However, the RL agent trained for a static target following still follows or attempts to follow more dynamic and changing targets with predictable performance. This works lays the foundation by setting up the initial validation requirements for the leaf sampling tasks and identifies potential areas for improvement. Further tuning of the system and experimentation of the RL agent type would pave the way to autonomous aerial leaf sampling. Adviser: Carrick Detweile

DESIGN OF A CUSTOM SOFTWARE APPLICATION TO MONITOR AND COMMUNICATE CNC MACHINING PROCESS INFORMATION TO AID IN CHATTER IDENTIFICATION

In any manufacturing environment, it is important to be able to monitor the Computer Numerical Control (CNC) machining process so that high quality parts can be produced in the least amount of time in order to be profitable. This involves acquiring the proper parameters needed from the machine\u27s controller, which can prove to be difficult with proprietary machine tools that tend to limit access to the internal data collected by the controller. This closed approach to controller design also means that many technological advances that have recently become prevalent in society are not being adopted in the manufacturing industry, preventing the interoperability between hardware and software components and adding to the shortcomings in communicating the necessary machining parameters to machine operators. The project described in this thesis offers a solution to some of the communication, productivity, and part quality problems in the American manufacturing industry by providing a custom software application that integrates MTConnect, an emerging interoperable data communication standard, with proprietary data acquisition tools and custom sensors to monitor and communicate CNC machining process information. The application described in this thesis was designed to aid in the identification of chatter conditions to the machine operator and to other users to take action for chatter suppression and avoidance. Chatter is an undesirable phenomenon that can reduce part quality and increase tool wear. These consequences result in higher costs to replace damaged parts and tools as well as increasing the amount of machine downtime which can reduce a company\u27s overall productivity. Once chatter is detected in the audible frequency range, damage to the workpiece has already occurred. Therefore, an early identification and communication method with the machine tool is warranted to easily monitor the machine in the event of impending dynamic part damage. This application was developed to provide a means to monitor cutting conditions to reduce and prevent chatter in the machining process and to aid in analysis to avoid subsequent unstable operating conditions. Preserving part quality and productivity in manufacturing is also dependent on accurate information provided about the specific parts involved in the machining process. In addition to monitoring the process, this application facilitates the communication of part-specific information by improving the input and tracking of part numbers, and organizes the machining process information in a central location according to the specific part. Improving the part tracking process can aid in the organization of data to analyze the machining process for increased quality in future operations. The application can also be customized for other implementations, which can benefit many different industrial manufacturing facilities as well as academics in performing experimental research. It is important for the manufacturing industry and its partners in academia to be able to bridge the communication gap to increase the knowledge of the machining process and therefore manufacturing productivity and profitability

PYDAC: A DISTRIBUTED RUNTIME SYSTEM AND PROGRAMMING MODEL FOR A HETEROGENEOUS MANY-CORE ARCHITECTURE

Heterogeneous many-core architectures that consist of big, fast cores and small, energy-efficient cores are very promising for future high-performance computing (HPC) systems. These architectures offer a good balance between single-threaded perfor- mance and multithreaded throughput. Such systems impose challenges on the design of programming model and runtime system. Specifically, these challenges include (a) how to fully utilize the chip’s performance, (b) how to manage heterogeneous, un- reliable hardware resources, and (c) how to generate and manage a large amount of parallel tasks. This dissertation proposes and evaluates a Python-based programming framework called PyDac. PyDac supports a two-level programming model. At the high level, a programmer creates a very large number of tasks, using the divide-and-conquer strategy. At the low level, tasks are written in imperative programming style. The runtime system seamlessly manages the parallel tasks, system resilience, and inter- task communication with architecture support. PyDac has been implemented on both an field-programmable gate array (FPGA) emulation of an unconventional het- erogeneous architecture and a conventional multicore microprocessor. To evaluate the performance, resilience, and programmability of the proposed system, several micro-benchmarks were developed. We found that (a) the PyDac abstracts away task communication and achieves programmability, (b) the micro-benchmarks are scalable on the hardware prototype, but (predictably) serial operation limits some micro-benchmarks, and (c) the degree of protection versus speed could be varied in redundant threading that is transparent to programmers